The Oxford Handbook of the Sociology of Finance 9780199590162, 0199590168

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T H E OX F O R D H A N DB O OK O F

T H E SOCIOLOGY OF FI NA NCE

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THE OXFORD HANDBOOK OF

THE SOCIOLOGY OF FINANCE Edited by

KARIN KNORR CETINA and

ALEX PREDA

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3

Great Clarendon Street, Oxford, ox2 6dp, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries © Oxford University Press 2012 The moral rights of the author have been asserted First Edition published in 2012 Impression: 1 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer British Library Cataloguing in Publication Data Data available ISBN 978–0–19–959016–2 Printed in Great Britain by MPG Books Group, Bodmin and King’s Lynn

Acknowledgments This project draws on a wide range of empirical research, historical evidence, and conceptual analysis of finance. It was born from the conviction that the need for a specialized handbook of finance is particularly urgent today, in view of widespread and quite fundamental disagreements about whether finance and financial markets are a benevolent force or plague that works against equitable and just relationships in contemporary societies, whether they are still controlled by political oversight or rather rule politics, and about how the financial sphere really works and should be working. When there are such disagreements they reflect not only a general malaise with a sphere of activity that seems to have spiraled out of control, but also simply a lack of familiarity and knowledge. David Musson had the vision that academic publishers can do something to remedy this situation—they can help synthesize and formulate the available information. Even if we possess only pieces of the overall picture, assembling the pieces together in a handbook, we agreed, will contribute critically important information to the often very general public discussion—and it can stimulate detailed research by bringing clarity to what we know and what is missing from particular disciplinary perspectives. This handbook, then, could not have been realized without David Musson’s encouragement, patience, and insistence through all stages of the project. It could not have been realized, of course, without the enthusiastic agreement of all our contributors, who wrote the handbook chapters. They had to put up what must have seemed an endless stream of emails, phone calls, requests for revisions and changes at short notice—interspersed with long periods of silence, when chapters were processed. Our great thanks also go to our anonymous reviewers, from whose suggestions we learned much, and whose criticism and also appreciation of this undertaking helped shape this volume and every single chapter. Our reviewers’ guidance has made us better understand the significance of this project and the audiences to which it speaks, as well as the need to balance its structure in an appropriate way. Finally we also want to thank Emma Lambert from Oxford University Press who saw this book into print and proved powerfully efficient in doing so. Her help in guiding us through the intricacies of the publishing system was invaluable. On the internal side, we want to enormously thank Elise Kramer for her extraordinarily professional editing work as she moved the project forward through its final stages. Without her copyediting, fact checking, accuracy, and her correspondence with authors, we could not have finished this Handbook within the set time frame. This is the second book we have co-edited—a considerably larger and more ambitious undertaking than the first. The entire process of discussing its concept, substance, and structure and of arranging and re-arranging chapters into various sections has, if any-

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acknowledgments

thing, advanced our teamwork several steps further. Toward the end of this process, although we were several thousand miles apart, we could see that we had developed a common vision of what needs to be improved and where. Lengthy discussion was no longer necessary; we would come to meetings with similar drafts. It is good to see how joint work cements team thinking, professional cooperation, and friendship.

Contents List of Figures List of Tables Contributors

x xi xii

Introduction Karin Knorr Cetina and Alex Preda

1

PA RT I F I NA N C IA L I N S T I T U T ION S A N D G OV E R NA N C E 1. Global Finance and Its Institutional Spaces

13

Saskia Sassen

2. Politics and Financial Markets

33

Gerald F. Davis

3. Finance and Institutional Investors

52

Jiwook Jung and Frank Dobbin

4. Business Groups and Financial Markets as Emergent Phenomena

75

Bruce Kogut

5. Central Banking and the Triumph of Technical Rationality

94

Mitchel Y. Abolafia

PA RT I I F I NA N C IA L M A R K E T S I N AC T ION 6. What is a Financial Market? Global Markets as Microinstitutional and Post-Traditional Social Forms

115

Karin Knorr Cetina

7. Auctions and Finance Charles W. Smith

134

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contents

8. Interactions and Decisions in Trading

152

Alex Preda

9. Traders and Market Morality

169

Caitlin Zaloom

10. The Material Sociology of Arbitrage

187

Iain Hardie and Donald MacKenzie

11. Seeing Through the Eyes of Others: Dissonance Within and Across Trading Rooms

203

Daniel Beunza and David Stark

PA RT I I I I N F OR M AT ION , K N OW L E D G E , A N D F I NA N C IA L R I SK S 12. Market Efficiency: A Sociological Perspective

223

Ezra W. Zuckerman

13. Financial Analysts

250

Leon Wansleben

14. Rating Agencies

272

Martha Poon

15. Accounting and Finance

293

Michael Power

PA RT I V C R I SE S I N F I NA N C E 16. The International Monetary Regime and Domestic Political Economy: The Origin of the Global Financial Crisis

317

Bai Gao

17. A Long Strange Trip: The State and Mortgage Securitization, 1968–2010

339

Neil Fligstein and Adam Goldstein

18. Dead Pledges: Mortgaging Time and Space Shaun French and Andrew Leyshon

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contents

19. Financial Crises as Symbols and Rituals

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376

Mark D. Jacobs

20. The Sociology of Financial Fraud

393

Brooke Harrington

PA RT V VA R I E T I E S OF F I NA N C E 21. The Disunity of Finance: Alternative Practices to Western Finance

413

Bill Maurer

22. Islamic Banking and Finance: Alternative or Façade?

431

Aaron Z. Pitluck

23. Geographies of Finance: The State-Enterprise Clusters of China

450

Lucia Leung-sea Siu

24. The Financialization of Art

471

Olav Velthuis and Erica Coslor

PA RT V I T H E H I S TOR IC A L S O C IOL O G Y OF F I NA N C E 25. Historical Sociology of Modern Finance

491

Bruce G. Carruthers

26. Gender and Finance

510

Josephine Maltby and Janette Rutterford

27. The Role of Confidence in Finance

529

Richard Swedberg

28. Finance in Modern Economic Thought

546

Franck Jovanovic

29. Financial Automation, Past, Present, and Future

567

Juan Pablo Pardo-Guerra

Index

587

List of Figures

Figure 1.1 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4

US Top Decile Income Share of National Income, 1917–2005 Institutional Investor Holdings in Large US Firms The Changing Form of CEO Compensation Equity Holding Among Executives Ratio of the CEO Compensation to the Average Compensation for Other Employees Figure 3.5 Average Level of Diversification Figure 3.6 Debt-to-Equity Ratio Figure 3.7 Proportion of Firms Making Downsizing Announcements Figure 3.8 Net Funding Status of Pension Plans Figure 4.1 Effects of Entrepreneurial Ability of a Family and the Growth of the Business Group Figure 12.1 Three Perspectives and Three Principles on Social Valuation and Financial Market Pricing Figure 13.1 Two “Calculative Frames” for Amazon.com Constructed by the Analysts Henri Blodget and Jonathan Cohen Figure 14.1 The Process of Corporate and Municipal Credit Rating Figure 16.1 National Defense and Major War Spending of the US Federal Government, 1950–2008 Figure 16.2 Revenue Effects of US Major Tax Cuts Figure 16.3 Social Spending of the US Federal Government, 1950–2008 Figure 18.1 Geography of Subprime Lending to African-Americans in the US, 2006 Figure 23.1 How Brokers and Industry Associations of China’s Futures Markets Perceive the Market Structure Figure 23.2 How the Hong Kong Stock Exchange Presents its Market Structure to the Local Media Figure 23.3 The Relationship between Exchange Q and its Members

22 55 58 59 61 63 65 67 68 87 234 256 283 326 327 328 370 454 455 460

List of Tables

Table 1.1:

Top five performing broad market indexes last year by major regions, in local currency Table 13.1: Sources of information ranked according to their importance for analysts, surveyed by Barker 1998 Table 14.1: Timeline summarizing the major events in the history of the ratings industry Table 22.1: Top 25 countries ranked by Shariah-compliant assets in 2010 Table 23.1: Commission fees in China’s futures markets (2004–6, schematic sketch)

27 257 287 432 464

Contributors

Mitchel Y. Abolafia is Professor at the Rockefeller College of Public Affairs and Policy, State University of New York. He is the author of Making Markets: Opportunism and Restraint on Wall Street (1997). Recent publications include “The Institutional Embeddedness of Market Failure: Why Speculative Bubbles Still Occur,” Research in the Sociology of Organizations (2010), and “Narrative Construction as Sensemaking: How a Central Bank Thinks,” Organization Studies (2010). Daniel Beunza is Lecturer in Management within the Employment Relations and Organisational Behaviour Group. His research in sociology explores the ways in which social relations and technology shape financial value. His award-winning study of a derivatives trading room within a Wall Street bank traces the roots of extraordinary returns to the use of space and internal organization. He has also studied securities analysts and the systemic risk posed by financial models. His current research is focused on responsible investment and the automation of financial exchanges. Bruce G. Carruthers is the John D. and Catherine T. MacArthur Professor of Sociology at Northwestern University. Carruthers has authored or coauthored five books, City of Capital: Politics and Markets in the English Financial Revolution (1996), Rescuing Business: The Making of Corporate Bankruptcy Law in England and the United States (1998), Economy/Society: Markets, Meanings and Social Structure (2000), Bankrupt: Global Lawmaking and Systemic Financial Crisis (2009), and Money and Credit: A Sociological Approach (2010). He has had visiting fellowships at the Russell Sage Foundation, Australia National University, and the Radcliffe Institute for Advanced Study, and received a John Simon Guggenheim Fellowship. Erica Coslor is lecturer in management at the University of Melbourne, Australia. She completed her PhD in Sociology at the University of Chicago. Her doctoral dissertation, “Wall Streeting Art: The Construction of Artwork as an Alternative Investment and the Strange Rules of the Art Market,” explained the growing interest in art by large, professional investors through the growth of measures, models, and tools to quantify the properties of art as an investment, mutual construction of the area with art market professionals, and the development of appropriate instruments to structure the investment. Her work relates to both science studies and organization theory, using the case of art investment as a case to identify a more general model of how financial investment areas are actively constructed by market actors, and objects with value are turned into recognizable financial assets.

contributors

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Gerald F. Davis is the Wilbur K. Pierpont Collegiate Professor of Management and Professor of Sociology at the University of Michigan. He has published widely in management, sociology, and finance. Recent books include Social Movements and Organization Theory (with Doug McAdam, W. Richard Scott, and Mayer N. Zald; 2005); Organizations and Organizing: Rational, Natural, and Open System Perspectives (with W. Richard Scott; 2007); and Managed by the Markets: How Finance Reshaped America (2009), which won the Academy of Management’s George Terry Best Book Award for 2010. He is the editor of Administrative Science Quarterly and Director of the Interdisciplinary Committee on Organization Studies (ICOS) at the University of Michigan. Frank Dobbin is Professor of Sociology at Harvard. His Forging Industrial Policy: The United States, Britain, and France in the Railway Age (1994) traces the roots of contemporary industrial policy approaches to the institutional logics of political order in different countries. The New Economic Sociology: An Anthology (2004), ties modern economic sociology to classical sociological theory. Inventing Equal Opportunity (2010) explores how corporate human resources professionals managed to define what discrimination meant under the Civil Rights Act. Neil Fligstein is the Class of 1939 Professor in the Department of Sociology at the University of California. He is the author of numerous books including The Architecture of Markets (2001), Euroclash (2008), and A Theory of Fields (with Doug McAdam; forthcoming). He has written extensively on the topics of economic sociology, social stratification, political sociology, and European economic and political integration. He is currently working on studying different aspects of the current financial crisis. He is a member of the American Association of Arts and Sciences, a former Guggenheim Fellow, and a former fellow of the Center of Advanced Study in the Behavioral Sciences in Palo Alto. Shaun French is Lecturer in Economic Geography at the University of Nottingham, UK. He has research interests in the geographies of finance and, in particular, the spatialities of contemporary processes of biofinancialization, of financial subjectification, and the politics of financial exclusion. He is coeditor of Key Methods in Geography (2010), and has published in such journals as Environment and Planning D: Society and Space, British Journal of Politics & International Relations, Antipode, and Transactions of the Institute of British Geographers. Bai Gao is Professor of Sociology at Duke University. He is the author of Economic Ideology and Japanese Industrial Policy: Developmentalism from 1931 to 1965, which received the 1998 Hiromi Arisawa Memory Award for the best books in Japanese studies from the Association of American University Presses, and Japan’s Economic Dilemma: The Institutional Origins of Prosperity and Stagnation. His ongoing research projects include the origins of the 2008 global financial crisis, the Chinese model of economic development, industrial upgrading in China, and industrial cluster and specialized markets in China.

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contributors

Adam Goldstein is a PhD Candidate in the Department of Sociology at the University of California, Berkeley. His research focuses primarily on the economic sociology of financial capitalism in the contemporary United States. Current projects examine how labor market insecurity and growing inequality have shaped households’ incorporation into financial markets since the 1980s; the organizational undermining of the 2008 financial crisis; and the role of local community structures in mediating patterns of housing market speculation. Iain Hardie is a Lecturer in International Relations at the University of Edinburgh. He studied history at Gonville and Caius College, Cambridge, before an 18-year career in investment banking in London and Hong Kong. He completed his PhD at Edinburgh in 2007. His articles have appeared in Review of International Political Economy, New Political Economy, The Sociological Review, Journal of Common Market Studies, and Economy and Society. His book, Financialization and Government Borrowing Capacity in Emerging Markets, is forthcoming with Palgrave. Brooke Harrington is Associate Professor of Economic Sociology at the Copenhagen Business School in Denmark. Her books include Pop Finance: Investment Clubs and the New Investor Populism (2008), as well as the edited volume Deception: From Ancient Empires to Internet Dating (2009). After receiving a doctorate in Sociology from Harvard University, Harrington earned research prizes and grants from organizations such as the National Science Foundation, the Russell Sage Foundation, the Alexander von Humboldt Foundation, the American Sociological Association, and the Academy of Management. Her current project is a qualitative study of the wealth management profession, offshore banking, and cross-national patterns of inheritance and inequality. Mark D. Jacobs is Professor of Sociology at George Mason University, where from 1992–9 he was founding director of the first interdisciplinary PhD Program in Cultural Studies in the US. He is a past chair of the Section on the Sociology of Culture of the American Sociological Association, since September 2011 has been vice-chair of the Research Network on Culture of the European Sociological Association, and is the 2010–11 Robin M. Williams Distinguished Lecturer of the Eastern Sociological Society. He has written Screwing the System and Making It Work: Juvenile Justice in the No-Fault Society (1990); collaborated with Gerald D. Suttles on Front-Page Economics (2010); and coedited The Blackwell Companion to the Sociology of Culture (2005). Franck Jovanovic is Professor of Economics at TELUQ, Université du Québec à Montréal. His research deals with the history of financial economics, and, more recently, with econophysics and its links with financial economics. Among his most recent publications are “The Construction of the Canonical History of Financial Economics,” History of Political Economy (2008) and “The History of Econophysics’ Emergence: A New Approach in Modern Financial Theory” (with Christophe Schinckus), forthcoming in History of Political Economy (2013). Jiwook Jung is a PhD candidate in the Department of Sociology at Harvard University. His research interests include organizational and economic sociology and the sociol-

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ogy of financial markets. His dissertation explores how increased pressure from financial markets has reshaped the behavior of firms, focusing on workforce downsizings by large American corporations between 1981 and 2006. Karin Knorr Cetina is George Wells Beadle Distinguished Service Professor of Sociology and Anthropology at the University of Chicago and project leader of research on scopic media at the University of Konstanz. Her publications include Maverick Markets: The Virtual Societies of Financial Markets (forthcoming); Epistemic Cultures: How the Sciences Make Knowledge (2003, 3rd edn); The Sociology of Financial Markets (edited with Alex Preda; 2005); “Global Microstructures: The Virtual Societies of Financial Markets” (with Urs Bruegger, American Journal of Sociology, 2002). Bruce Kogut is the Sanford C. Bernstein & Co. Professor of Leadership and Ethics and Director of the Sanford C. Bernstein Center for Leadership and Ethics at Columbia Business School. He received his PhD from the MIT Sloan School of Management and holds an honorary doctorate from the Stockholm School of Economics. Previously, he was on the faculties of the Wharton School of the University of Pennsylvania and INSEAD, and he has been a research fellow and visiting professor at the Rand Corporation, École Polytechnique, Social Science Research Center Berlin, Stockholm School of Economics, Humboldt University, Santa Fe Institute, the Singapore Management University, and Tsinghua University, among others. Andrew Leyshon is Head of the School of Geography and Professor of Economic Geography at the University of Nottingham. His research focuses on geographies of money and finance and on the implications of digital technology for the musical economy. Recent publications include The Sage Handbook of Economic Geography (edited with Roger Lee, Linda McDowell, and Peter Sunley; 2011) and Geographies of the New Economy (edited with Peter Daniels, Jon Beaverstock, and Mike Bradshaw; 2007). In 2007 he was elected as an Academician of the Academy of Social Sciences. Donald MacKenzie works in the sociology of science and technology and in the sociology of markets, especially of financial markets. He holds a personal chair in sociology at the University of Edinburgh, where he has taught since 1975. His most recent books are An Engine, Not a Camera: How Financial Models Shape Markets (2006); Do Economists Make Markets? On the Performativity of Economics (2007), coedited with Fabian Muniesa and Lucia Siu; and Material Markets: How Economic Agents are Constructed (2009). Josephine Maltby is Professor of Accounting and Finance at the York Management School, University of York, and previously held a chair at the University of Sheffield. Her major research interests are in accounting and business history, corporate governance, and women as savers and investors. Recent publications include “The Wife’s Administration of the Earnings? Working-class Women and Savings in the Midnineteenth Century,” Continuity and Change (2011); and (with J. Rutterford, J. Green, A. Owens) “Who Comprised the Nation of Shareholders? Gender and Investment in Great Britain, c. 1870–1935,” The Economic History Review (2011).

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Bill Maurer is Professor of Anthropology and Law at the University of California, Irvine. His work on the anthropology of money and finance has considered the offshore financial services sector in the Caribbean, Islamic banking, and, most recently, mobile phone-enabled money transfer and savings services. He is the author of Recharting the Caribbean: Land, Law and Citizenship in the British Virgin Islands (1997); Pious Property: Islamic Mortgages in the United States (2006); and Mutual Life, Limited: Islamic Banking, Alternative Currencies, Lateral Reason (2005). The latter was awarded the Victor Turner Prize. Juan Pablo Pardo-Guerra is Lecturer in Sociology at the London School of Economics and Political Science. Trained in physics and science and technology studies, Juan Pablo’s work deals with the sociology of technological innovation in financial markets. Aaron Z. Pitluck holds a two-year research fellowship with the Political Economy Research Group at Central European University (Budapest) and is an Associate Professor in the Department of Sociology and Anthropology at Illinois State University. Most recently he has researched how illiquidity influences professional investors’ behavior, and how and why professional investors herd in the global south. He has published in Economy and Society and the Society for Economic Anthropology monograph series. Martha Poon is a Scholar in Residence at the Institute for Public Knowledge, New York University. She holds a PhD from the Studies Program at University of California, San Diego. She is currently working on a book manuscript entitled What Lenders See that Tells the History of the U.S. Consumer Credit Rating System. Michael Power is Professor of Accounting and Director of the Centre for the Analysis of Risk and Regulation (CARR) at the London School of Economics. He was educated at St Edmund Hall, Oxford, and at Girton College, Cambridge; is a Fellow of the Institute of Chartered Accountants in England and Wales (ICAEW), and an Associate member of the UK Chartered Institute of Taxation. In 2009 he was awarded an honorary doctorate in Economics by the University of St Gallen, Switzerland, and in 2011 he was made an honorary fellow of the Institute of Risk Management. He is the author of The Audit Society: Rituals of Verification (1999), which has been translated into Italian, Japanese, and French; and Organized Uncertainty: Designing a World of Risk Management (2007). Alex Preda is Professor of Accounting, Accountability, and Financial Management in the Department of Management at King’s College London. He is the author of, among others, Framing Finance: The Boundaries of Markets and Modern Capitalism (2009) and Information, Knowledge and Economic Life: An Introduction to the Sociology of Markets (2009). He is currently writing an ethnography of electronic financial markets. His present research interests are communication and decision making, the valuation of persons, and social competitions.

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Janette Rutterford is Professor of Financial Management at the Open University Business School. Her research interests are the history of investment, women investors, equity valuation, and pension fund management. Her most recent books include Introduction to Stock Exchange Investment (2008, 3rd edn) and she is the coeditor of Women and their Money 1700–1950: Essays on Women and Finance (2009) and of Men, Women and Money: Perspectives on Gender, Wealth and Investment (2011). Saskia Sassen is the Robert S. Lynd Professor of Sociology and the co-chairs Committee on Global Thought, Columbia University (). Her recent books are Territory, Authority, Rights: from Medieval to Global Assemblages (Princeton Universtiy Press 2008), A Sociology of Globalization (W. W. Norton 2007), and the 4th-fully updated edition of Cities in a World Economy (Sage 2011). The Global City came out in a new fully updated in 2001. Her books are translated into twenty-one languages. She is currently working on When Territory Exits Existing Frameworks (under contract with Harward University Press). She contributes regularly to www.Opendemocracy.net Lucia Leung-sea Siu is Assistant Professor in the Department of Sociology and Social Policy, Lingnan University, Hong Kong. She is coeditor (with Donald MacKenzie and Fabian Muniesa) of Do Economists Make Markets? On the Performativity of Economics (2008), and council member of the Hong Kong Sociological Association. She got her PhD from the University of Edinburgh. Charles W. Smith, Professor Emeritus of Sociology, Queens College and the Graduate Schools of CUNY, has been engaged in ethnographic research of auction, primarily financial, markets since the mid-1960s. His books include The Mind of the Market (1981), Auctions (1989), and Success and Survival on Wall Street (1999). His more recent publications include “Coping with Contingencies in Equity Option Markets: The ‘Rationality’ of Pricing” in The Worth of Goods (2011), “Staging Auctions: Enabling Exchange Values to be Contested and Established” in Negotiating Value in the Creative Industries; “Markets as Definitional Practices,” CJS (2007); and “Financial Edgework: Trading in Market Currents,” in Edgework: The Sociology of Risk Taking (2005). His primary focus has been on how markets cope with ambiguity and contingencies. David Stark is Arthur Lehman Professor of Sociology and International Affairs at Columbia University, where he directs the Center on Organizational Innovation. Stark’s most recent book, The Sense of Dissonance: Accounts of Worth in Economic Life (2009) examines the perplexing situations in which organizations search for what is valuable. Papers from his various research projects are available at www.thesenseofdissonance.com. Richard Swedberg has been Professor of Sociology at Cornell University, Department of Sociology, since 2002. His specialties are economic sociology and social theory. His works include Max Weber and the Idea of Economic Sociology (1998), Principles of Economic Sociology (2003), and Tocqueville’s Political Economy (2009). He is currently working on the financial crisis and how to theorize in social science.

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contributors

Olav Velthuis is Associate Professor at the Department of Sociology and Anthropology of the University of Amsterdam. He is the author of Imaginary Economics (2005) and Talking Prices: Symbolic Meanings of Prices on the Market for Contemporary Art (2005), which received the Viviana Zelizer Distinguished Book Award of the American Sociological Association for the best book in economic sociology (2006). Before this he worked as a staff reporter on globalization for the Dutch daily de Volkskrant, as a visiting postdoctoral researcher at Columbia University and as assistant professor at the University of Konstanz. Velthuis is currently studying the emergence and development of art markets in the BRIC countries (Brazil, Russia, India, and China). Leon Wansleben holds a PhD in sociology from the University of Konstanz and since 2010 has been a research fellow at the University of Lucerne, working on a project on economic and financial image practices. His forthcoming monograph Cultures of Expertise in Global Currency Markets provides a first empirical study of market cultures and expert practices in the area of foreign exchange. Caitlin Zaloom is a cultural anthropologist and Associate Professor of Business and of Social & Cultural Analysis at New York University. Her research examines emerging forms of knowledge and practice related to financial risk. Her book Out of the Pits: Traders and Technology from Chicago to London (2006) showed how traders, managers, and technology designers enact formal ideals of economic reason in trading screens and dealing rooms. Zaloom is currently working on a book about the practices of household finance (around education, housing, health care, and retirement) in an age of debt. Ezra W. Zuckerman is a Professor at the MIT Sloan School of Management, where he holds the Nanyang Technology University chair and holds appointments in the TIES (Technological Innovation, Entrepreneurship, and Strategic Management) group and the Economic Sociology PhD Program (ESP). He cofounded the ESP in 2006, and since 2009, he has been the academic director of the MIT Sloan PhD Program. Zuckerman received his PhD in Sociology from the University of Chicago in 1997. From 1997 to 2001, he taught at the Stanford Graduate School of Business. Zuckerman’s research ranges over several related problem domains, including: (a) how positions in social networks relate to different valued outcomes; (b) the causes and consequences of close ties between economic actors; (c) how market dynamics are shaped by structures of classification; (d) how social status affects behavior and valued outcomes; and (e) the conditions under which social valuations approximate or depart from objective conditions.

i n troduction k arin k norr c etina and a lex p reda

Important historical shifts sometimes have implications which are all but overlooked. One such shift is the rise of finance. Almost everyone realizes today that finance is a major force in contemporary economies and societies. Yet few social scientists outside of economics had addressed the phenomenon before the financial crisis of 2007–9, and until very recently, few of those on “Main Street” who have been directly affected by the rise of finance in the last decades have raised questions about this development or protested against its consequences.1 Financial investments and transactions are, of course, not new. The modern nation-state has sought the help of bankers and financiers for its debt and expenditure financing since it came into existence. It has routinely issued multiple financial instruments for the purpose (e.g., bonds, treasury notes) and has cultivated strong ties to the financial elites—ties that also existed in preceding monarchies and other forms of government. Individuals have also become involved with the financial system on a larger scale at least since the seventeenth century (e.g., Rutterford 2009, 2011); the rise of the “popular investor” dates from that time (see Preda 2009). The roots of finance are historically deep. Yet we now live on the crest of a long wave of seemingly unprecedented expansion of the financial system that appears to outrun these historical roots. In other words, we live in a financialized world; financialization, broadly defined, refers to the increasing role of financial motives, markets, actors, and institutions in the operation of economies and their environment (Epstein 2005: 3). In a financialized economy, financial logics and concerns may begin to dominate institutions that had operated on a different basis; think of the rise of shareholder value as a mode of governance of the firm and of financial controllers in the management of corporations. Or think of the growing importance of financial markets which the financial crisis of 2007–9 and the European debt crisis of 2010–11 have driven home to us. Finance can be obtained through two channels: bank lending and financial markets. Manufacturingoriented economies, such as that of Germany, historically developed a financial organization in which bank lending dominated. In the United States, as in Anglo-Saxon

2

karin knorr cetina and alex preda

countries generally, a different pattern emerged with less emphasis on bank lending, while money markets and securities markets each provided important credit channels. In the last decades, the market channel has developed into the centerpiece of the global financial architecture and the financial organization of Western economies. For example, in the US and the UK, less than 30 percent of corporate finance came from commercial banks before the turn of the century (Chernow 1997). Though bank credit is still important in some of today’s more complex economies, it is itself deeply enmeshed in financial markets through banks’ own investment and financing strategies. Only a small fraction of the money lent to credit-seekers actually comes from clients’ deposits of money. The market for repackaged subprime mortgage debt and for credit derivatives, and default obligations more generally, is a case in point. A major factor in the crisis was the expansion of credit available to banks; they expanded their leverage through the use of such instruments to a volume several orders of magnitude larger than their deposits, and this injection of credit massively increased the trading of, and risks incurred by, these instruments (e.g., Taylor 2009: ch. 1). The crisis prompted a hard look at the financial system that had been created since the 1980s, an examination undertaken by various social science disciplines. When were the seeds of this system planted and how did it come to make such tremendous inroads? Did governments facilitate this development? Which economic theories sustain, or perhaps even drive, financial expansion? What role do traditionally important social variables such as trust and confidence play in financial transactions? Do specific types of finance arise in specific types of culture? And what is a financial market, seen from an empirical, sociological, and cultural perspective? For those interested in such questions this handbook offers a wide-ranging resource and a starting point. We bring together authors who specifically address the financial components of the economy and have done so through their own empirical research over many years. While these works do not simply yield one unified empirically based account of finance, they do show the extent to which financial systems are social and cultural, down to the core elements of their operation. This does not mean that finance can somehow be reduced to symbols and social structure. But finance is not exempt from contextual and historical influences, and financial actions and institutions appear to be suffused with orientations and variables that sociologists traditionally study. In fact, finance may be a particularly interesting area to investigate from a broadly empirical social science perspective that goes beyond the fundamentals of the discipline of economics, because it often appears to be at the cusp of the transition from an industrial economy and modern society to a postindustrial and postmodern world. While we cannot really tell what the end result of the transition will be, and whether we are going to like it or not, it seems plain that finance is an area in which drivers and outcomes of this rearrangement can be watched in action. Think of the coevolution of and alignment between finance and specific types of technological media and information that appear to lead to new forms of action (e.g., trading by algorithms), communication, and organization. Or think of the global reach and impact of many financial operations. Finance may well be a driver of globalization. Since the 1970s, several areas of finance have quickly taken advantage of what electronic information

introduction

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technologies make possible and have promoted and paid for the further development of specific systems (e.g., electronic broker systems, trading platforms). These areas of finance are comfortable with a global world that they have learned to navigate in several decades. Finance harbors and spawns “local” and regional varieties in non-Western contexts—take microfinance and Islamic finance as examples. Yet even these “small” varieties (compared to Western finance volumes) appear to have transnational and global clienteles, supply chains, and linkages to global banks without which they might not survive. Globalization is a long-term historical development that encompasses many aspects such as the interdependence of national economies, the operation of global scripts, and the development of a global consciousness. Yet if we want to find a global action system with defined boundaries and an internal level of integration, then finance (operating through a market channel) offers itself for detailed consideration. Financial areas also describe themselves in terms of global concepts; one example is participants’ notion of a global financial architecture. Another example of the transnational orientation of finance is the role financial markets play in influencing the price of national currencies and in evaluating national economic policies and measures. Several chapters in this handbook study the global character of finance as a specific development pointing beyond the modern period. Sociology tends to look at finance broadly as an action system within the framework of the institutions and organizations in which financial activities take place. This is different from a concern with what finance is made for and good for—its function, purpose, and design. As investors and speculators, as fund managers and traders, and to a degree as professional economists, we surely want to understand financial markets, for instance, but we want to understand them in relation to how they affect our investments, how to profit from them, how to maintain value. All advisory books and collections are of this nature—they tap and relate what they think are successful investors’ and fund managers’ strategies and know-how in getting returns from markets. As investors and credit-seekers, we are concerned with what finance can do for us, and we raise the respective questions on a more or less sophisticated level—that of day traders, for instance, of professional analysts, or of scientific portfolio management theory and the development of an option formula. What we are not concerned with, with such goals, is the internal operations of the financial system. Unlike perhaps a physicist, we want to see the processing results of the machine, but not the processors inside. Sociologists are more like physicists in this particular respect: they tend to ask questions about the internal operation of the financial system, and they often also ask questions about its effects— for example, about longer-term consequences of the system for the welfare of various segments of the population. Both types of questions tend to go beyond the typical questions of investors and analysts. Yet answers to both types of questions are urgently needed. Given the importance of finance as a pillar of the economy, we will need more, rather than less, knowledge in the future about the internal workings of the financial system, participants’ attitudes and orientation, and the system’s various points of vulnerability and positive and negative consequences for the welfare of societies. The study of finance from a behavioral social science perspective is an emergent interdisciplinary

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field in its own right that has started to provide answers to such questions. This handbook brings together the emerging perspectives and micro- and macro-level concerns of this field, and it maps out directions in which the social science analyses of finance will need to go in the future. Finance has also emerged as a field of analysis in its own right in economics—as exemplified in specialized conferences, associations, textbooks, fields of study, and the denomination of chairs and professorships. Perhaps the most fundamental reason for this is that finance has historically evolved as a distinctive system of activities. If production, consumption, and distribution or exchange—the market interface between production and consumption—are three different spheres of economic activity, then finance is a fourth sphere; it cannot simply be subsumed under the terms of production as described by industrial sociology or those of primary, producer markets. Nor can we describe finance simply as a category of consumption. While finance involves principles of distribution (e.g., the distribution of risk), and arguably a dimension of the consumption of information, it hardly appears understandable in the terms of leading theories of consumption that are concerned with the consumers’ lifestyle, identity, and self-expression. One reason for the dissimilarity between finance and other economic spheres is that finance fulfills a specialized function: that of supplying and controlling credit. In a capitalist economy, credit needs to be obtained before a production cycle can start; credit, as Keynes argued, is prior to production (e.g., Shapiro 1985: 77). Accordingly, finance and the primary economy may have distinctive histories, a phenomenon for which some historians provide evidence (see Chapter 6). Finance and other economic spheres are also differently regulated, and they exhibit different regimes of action. For example, over-the-counter markets for financial instruments not traded in exchanges have long been deregulated—they were successively “liberated” from the restrictions and oversight that apply to the industrial side of the economy, and from some that apply to exchange-traded markets, in the 1970s and early 1980s. This does not mean that these areas of finance have been effectively cut off from political connections or that they have shunned political influence—in fact, as some chapters in this volume suggest, they appear to have greatly benefitted from such influence. But until the financial crisis of 2008–9 hit and prompted a measure of reregulation, it did mean that these markets were left to their own devices of internal self-regulation. In regard to their regimes of action, financial markets require us to learn to understand the action structure of investment and speculation. Both types of financial action appear to involve promise-based engagements and relationships between a credit supplier (e.g., an investor, the promisee) and a credit-seeker (e.g., a firm or state, the promiser) as well as the market. Transactions of goods for money in the primary economy do not routinely involve promissory engagements that extend well beyond the actual transaction; in primary markets, participants are quits when they have finished the transaction (Slater 2002: 237). If we conflate primary producer markets with financial markets we cannot capture the different transactional orientations and logics of these spheres that have enormous consequences. The financial imagination, for instance, works quite differently from the economic imagination. While the former is based on a positive notion of risk-taking and turns around the

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future potential value of an object whose present value may be negative, economic thinking may have its roots in the running of a household and various historical societies’ experience with it. Economic thinking since the mid-twentieth century would seem to be perched between a household form of reasoning and the idea of individual interest optimization enshrined in the notion of economic man—notions that may not give us much purchase in understanding the financial imagination.2 The emergence of a new field of sociology of finance thus mirrors developments in economics and business, areas in which finance has branched off and become a major, distinctive, degree-validated area of study—in correspondence with its history and development as a specialized subsystem of society. Internal differentiation quickly follows when fields branch off, and it may also precede the emergence of new fields. The sociology of finance is the main focus of this handbook, as the title suggests. But sociology encompasses many different approaches and methodologies; for example, some authors use large quantitative data sets to substantiate a finding, while others employ observation and ethnography to serve as a basis for theoretical conceptualizations and to uncover the details of particular financial practices and operations; some focus on macro-developments while others focus on the microlevel accomplishments of financial institutions. Sociological concerns have always been broad; they include questions that anthropologists, psychologists, political scientists, historians, and scholars in business schools may also have on their agenda—neighboring fields have overlapping concerns, and scholars may want to keep an eye on the findings that different approaches yield. The handbook reflects our belief in the need to bring together different viewpoints—we include some historical, anthropological, political, and financial economics perspectives. The longstanding concerns of sociology are with questions of groups, culture, and conventions. These are well reflected in this volume, as are recent concerns with social and cultural transitions to a more technological, media-saturated lifeworld and an object- and knowledge-oriented lifestyle—think of financial markets as a platform for symbols and an object of emotional attachment. Each of the six parts of the handbook presents the reader with a set of chapters analyzing a particularly relevant aspect of contemporary finance, including global institutions, technology and cognition, alternatives to Western finance and its history, and the microstructures of global financial markets. The first part, “Financial Institutions and Governance,” brings together five chapters examining the global institutions of contemporary finance, the links between finance and politics, and those between firms and financial institutions. Saskia Sassen explores the larger assemblage of institutional and geographic spaces that constitute the global financial system and examines its internal diversity. Gerald F. Davis shows how the structural organization of finance within a country reflects and shapes the organization of business and politics, and Jiwook Jung and Frank Dobbin demonstrate the role institutional investors played in promoting a new model of management based on agency theory under the banner of shareholder value, a change that resulted in several disadvantages for the American worker. Social networks and groups, which have been prominent in sociological research on markets, are examined in their relationship to finance in Bruce Kogut’s chapter; Kogut argues that

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the interplay between law-like properties of firm-size distributions and the micromotives of economic agents lead to the emergence of business groups. Mitchel Y. Abolafia, in his turn, devotes his attention to how central banks position themselves in relationship to financial markets. He locates an important, though not exclusive, source of central banks’ authority in their interpretive power. This focus on the politics of interpretation anticipates the second part of the handbook, “Financial Markets in Action,” which examines microstructural and interactional aspects of financial markets. The introductory chapter to Part II, written by Karin Knorr Cetina, asks how we can conceptualize contemporary global financial markets; her answer is that these markets contrast with firms and networks not just in that they are distributed, interaction-level systems, but in that they are coordinated by a central media mechanism that is “scopic” and leads to a level of global, attentional integration—coordination is based on a projected, augmented, and coercively monitored electronic rendering and image of the market. In his contribution, Charles W. Smith analyzes the nature and variability of auctions and the shift from the preeminently local format of face-to-face auctions to auctions used in electronic commerce in order to establish the value of intangibles such as words. The chapter on interactions and decisions in trading, written by Alex Preda, shows how paying attention to interactions in relationship to decision-making processes can help explain phenomena of which behavioral economists have long been aware, such as the links between emotions and cognition. Caitlin Zaloom turns next to the role and positions of traders in finance, discussing among other things the transformation of their activities when computerized trading became dominant, as well as their public perception. The topic of trading and technology is examined from a different angle in Chapter 10 (Iain Hardie and Donald MacKenzie), which investigates the role played by financial models in relationship to the growing prominence of hedge funds. The final chapter of Part II, coauthored by Daniel Beunza and David Stark, starts from an organizational ecology viewpoint. It explores the crucial role of diversity in terms of evaluative principles in the context of financial organization—and shows how the dissonance of evaluative principles across an organizational interface may contribute to organizational learning and economic evolution. Part III, “Information, Knowledge, and Financial Risks,” opens with the chapter authored by Ezra W. Zuckerman, who examines a key topic from the financial economics literature, namely market efficiency in relationship to cognition. Leon Wansleben, in his contribution, sheds a spotlight on the role played by financial analysts in the production of the cognitive formats within which financial markets operate. He tracks the history and development of this profession and argues that analysts do not merely produce passive forms of cognition, but play a significant part in enabling modes of coordination at collective levels. There is but a short distance from analysts to rating agencies, which are covered by Martha Poon in her contribution. Poon tracks the emergence and growing influence of rating agencies, examining the standardization techniques they produced and why markets adopted them. Michael Power’s contribution shifts the spotlight from rating agencies to accounting, which is yet another significant cognitive presence

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in finance. Power looks at how accounting practices have changed in relationship to markets, and how these changes have impacted the understanding of financial risks. Perhaps there is no other situation in which this understanding of risks comes better to the fore than in the recent, ongoing financial crisis that started in 2008. Part IV, “Crises in Finance,” is entirely dedicated to this topic. The opening chapter, written by Bai Gao, provides a detailed prehistory of the financial crises in all its global dimensions and ramifications. The following contribution, authored by Neil Fligstein and Adam Goldstein, shows that financial crises are never isolated from politics and that the latter play a major role in creating the conditions conducive to crisis. This examination of the politics of crises is followed by the chapter written by Shaun French and Andrew Leyshon, who discuss a major aspect of the recent crisis: housing finance. Using the analytical tools of human geography, French and Leyshon discuss the role of the credit industry in triggering this crisis, as well as the spread of the crisis across countries and continents. Since financial crises can never be reduced to a purely economic impact, entirely separated from a broader social one, critical aspects of crises acquire symbolic dimensions which resonate in the public sphere via political discourses, media representations, and public protests, among other things. It is such symbolic aspects which constitute the focus of the chapter authored by Mark D. Jacobs. Jacobs reviews the ways in which financial crises have resonated in the public sphere, the symbolisms associated with crises, and the ways in which the crisis has impacted the political discourse. Oftentimes, the symbolic character of financial crises is exacerbated by forms of manipulative behavior or deceit, which are uncovered precisely at such critical times. Examples abound here, and the final chapter of Part IV, written by Brooke Harrington, deals with the role and place of financial frauds in times of crisis and beyond. Part V, “Varieties of Finance,” brings together four chapters that examine not only non-Western forms of finance, but also alternative practices that have emerged within the mainstream of Western finance. The introductory chapter written by Bill Maurer provides an overview of alternative forms of finance ranging from Islamic to microfinance and local currencies, among others, discussing the economic projects within which they emerge. Following this introductory overview, Aaron Z. Pitluck focuses in his contribution on the principles, forms, and applications of Islamic finance; based on available statistical data, Pitluck evaluates its impact and its position vis-à-vis mainstream finance, as well as its global spread. The third chapter in this section is authored by Lucia Leung-sea Siu and discusses the institutions and forms of Chinese finance. Siu provides readers with an overview of the main institutions involved in contemporary Chinese finance; she examines the forms and activities of the main Chinese markets and exchanges, the regulatory framework, and the main actors involved in Chinese financial markets. The final chapter of the section, written by Olav Velthuis and Erica Coslor, sheds a spotlight on forms of investment alternatives to mainstream financial securities. Their case study is provided by the financialization of the art market: Velthuis and Coslor examine the processes through which, since the 1970s, the art market has become more and more a niche market for financial investment, accepted as legitimate by mainstream finance and by economists.

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The sixth and final section of the Handbook of the Sociology of Finance, titled “The Historical Sociology of Finance,” opens with Bruce G. Carruthers’ overview of the historical processes through which financial markets have achieved prominence in capitalist societies. Carruthers traces the evolution of the links between markets and states, ascribing prominence to the political processes which have made finance into a major economic force. The second chapter, written by Josephine Maltby and Janette Rutterford, turns to another aspect of the historical evolution of finance: the role played by gender and gender relationships. Rutterford and Maltby provide readers with evidence against the age-old prejudice that finance has passed women by. They show that, from early on, women were a recognized presence in finance, achieving a certain degree of prominence at particular historical moments. The third chapter in Part VI is authored by Richard Swedberg and focuses on the role and historical development of confidence as a driving force in finance. Swedberg makes a powerful argument in favor of distinguishing between trust and confidence, and shows how the latter was conceptualized in economic thought while becoming an explanatory principle in the functioning of markets. Swedberg’s historical and theoretical overview of confidence is followed by Franck Jovanovic’s examination of the evolution of financial economics from a side issue into a centerpiece of economic theory. Jovanovic argues that this evolution is recent and that it has been made possible in the first place by two kinds of developments: first, in stochastic theory, which provided financial economists with the means of formalizing their ideas; second, institutional evolutions that provided financial economists with prominent positions in business schools from which they could disseminate their points of view successfully. The section on the historical sociology of finance closes with Juan Pablo Pardo-Guerra’s overview of the technological evolution of financial markets, and especially of market automation. Pardo-Guerra stresses that contemporary financial markets cannot be conceived outside technology, and that automation has become a major driving force. He traces the social roots of this process and highlights the groups and the professional shifts that made technology into the keystone of contemporary markets. With that, and without aiming at being exhaustive, the Handbook of the Sociology of Finance examines major sets of issues of contemporary markets in a fashion that is concise yet as comprehensive as possible, aiming to help readers achieve a better understanding of how and why finance became what it is today, and what can be expected for the future. We hope to have succeeded in this enterprise.

Notes 1. The “Occupy Wall Street” demonstrations in the US, for instance, began only in the second half of 2011. 2. See Swedberg (2011). for the notion of a household in three historical periods. See Knorr Cetina (forthcoming: ch. 1) for the notion of the financial imagination.

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References Chernow, R. (1997). The Death of the Banker: The Decline and Fall of the Great Financial Dynasties and the Triumph of the Small Investor. New York: Vintage. Epstein, G. (ed.) (2005). Financialization and the World Economy. Cheltenham: Elgar. Knorr Cetina, K. (forthcoming). Maverick Markets: The Virtual Societies of Financial Markets. Preda, A. (2009). Framing Finance: The Boundaries of Markets and Modern Capitalism. Chicago: University of Chicago Press. Shapiro, M. M. (1985). Foundations of the Market-Price System. Lanham, MD: University Press of America. Slater, D. (2002). “From Calculation to Alienation: Disentangling Economic Abstractions.” Economy and Society, 31: 234–49. Swedberg, R. (2011). “The Household Economy: A Complement or Alternative to the Market Economy?” Cornell University Center for the Study of Economy and Society. (accessed November 12, 2011). Taylor, J. (2009). Getting Off Track: How Government Action and Intervention Caused, Prolonged, and Worsened the Financial Crisis. Stanford, CA: Hoover Institution Press.

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chapter 1

gl oba l fi na nce a n d its i nstitu tiona l space s s askia s assen

The aim of this chapter is to get a grip on the constitutive elements of global finance, and specifically high finance. A rapidly growing scholarship on financial institutions and markets has made a critical contribution to our understanding of high finance. Representative of diverse approaches are, for example, MacKenzie et al. (2007), Knorr Cetina and Preda (2004), Eichengreen (2003), Zaloom (2006), Fisher and Downey (2006), Krippner (2011), Smith (2012), and the special issue of the journal Globalizations (2011). This chapter builds on elements of this vast scholarship but with a somewhat different organizing question and somewhat different types of data analyses, including of historical data. The aim is to bring to the fore the institutional spaces of finance through the notion of an operational field, rather than a focus on firms and markets. The argument is that global finance has debordered the narrowly defined notion of financial firms and markets, and financial institutions generally. It is not so much about institutions as about a larger assemblage of institutional, technical, and geographical components (Sassen 2008: ch 5 and pp 348–65; see also Knorr Cetina and Bruegge an the limits of firms). These components include, among others, a broad range of financial and nonfinancial institutions, different types of jurisdictions, technical infrastructures, and public and private domains. This analytical perspective helps explain four of the key issues examined in this chapter. First, it helps explain why the Bretton Woods (BW) internationalism was not enough to generate the global financial system that emerged in the 1980s. Many of the components that became important in the 1980s were in place in the postwar period, as they were at the end of the 1800s. But the organizing logic of the whole assemblage of elements in each of those earlier periods was not conducive to the formation of a global, as distinct from an international, capital market. Second, it helps explain the distinctive growth patterns and conditions for growth of the global financial system, which are quite different from those of other economic sectors; the latter inhabit a more clearly defined institutional space than global finance. Third, it helps explain the networked format of

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finance which enables it to incorporate diverse elements and develop innovative formats, such as alliances of exchanges; this contrasts with the old-style format of the traditional bank and the corporation, notably closure and vertical integration. Fourth, this analytic perspective can accommodate the fact that finance has properties that differentiate it from the rest of the market economy; one notable instance is its need to financialize other economic sectors—these function as the grist for its mill. Generally, much in these four traits holds for domestic high finance as well. But when finance goes global on the scale at which it has since the 1980s, some of these issues become acute, and therewith visible. The first section examines the different organizing logic of BW internationalism from that of the post-1980s global era, even as many of the same elements are present in both; among these are an international framing geography, the development of norms to be adopted by all signatory states, and more. Distinguishing between components and encompassing organizing logic helps explain this (Sassen 2008: ch. 1). The second section examines the organizing logic of the post-1980s era. The third section discusses the major growth patterns and conditions for growth of the post-1980s financial system, which brings to the fore the differences between finance and other economic sectors. The fourth section examines the slippery relation between finance and exchanges and, more generally, financial centers, both of which are institutionalized spaces rather than institutions per se. I examine this issue through the problem of “incomplete knowledge” (Sassen 2011: ch. 5) facing all firms and investors in market economies, and the role of financial centers in making knowledge; in the case of finance, the problem of “incomplete knowledge” can become acute given the velocities and orders of magnitude involved. Further, I (2011: chs 4 and 5) interpret the existing evidence as showing that the specialized differences of financial centers are a critical variable for addressing the problem of incomplete knowledge; this contrasts with much writing about financial centers that tends to overlook the specialized differences among these centers and emphasizes standardization—of technological facilities, operational standards, contractual obligations, and more. I see all these standardized conditions as the equivalent of an infrastructure for global financial centers. The strategic importance of financial specialization derives from the possibility of building deep and often largely informal knowledge about particular financial markets (e.g., Chicago’s preeminence in many commodities markets). This in turn repositions the question of competition among firms, exchanges, and centers. I find that there is far less competition among centers and exchanges than is commonly posited. So much emphasis has gone to the standard features across exchanges and financial centers that this has, in turn, generated an overemphasis of competition. It is impossible to do full justice in this short chapter to the subjects and to the vast literatures in diverse disciplines that are critical to my discussion here. Each of these subjects is complex and controversial and I have examined them at length elsewhere with extensive bibliographies (2001: ch. 4; 2008a: chs 4, 5, 7; 2009; 2010; 2011: chs 4 and 5).

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Varieties of financial internationalism An infrastructure of laws and customs for interstate collaboration and cross-border transactions has been in place for well over a century. National states, especially major powers, have participated in a variety of internationalisms across history, especially during the immediate post-World War II period. This indicates that internationalism alone was not enough to move us into the type of world scale and global financial system evident today. It is too general a feature: the modern capitalist state was born within an international framework—with the empires of earlier centuries as one key component. The major powers of the late nineteenth and early twentieth centuries had broad jurisdictions to prescribe regulations for their citizens given that the nexus between the modern market-centered state and its subjects could be very loose (for a variety of angles, see Murphy 1994; Picciotto and Mayne 1999; Sassen 2008: ch. 3; Suter 1992). Reciprocal arrangements such as extradition and judicial assistance were already developed by the late nineteenth century. While the executive power to enforce such regulation was, and in most regards remains, essentially territorial, the mobility of people and firms and the interlinking of ownership and world markets have meant that, in principle, state authority has long had considerable scope beyond its national territory (e.g., Brilmayer 1989; Walker 1993; Stephan 2002). In several ways, then, the requisite capabilities for entering the global age were long available. This was perhaps particularly so after World War II when major states were developing international regimes and the necessary institutional infrastructure. For many observers and experts this is when the global age begins. But there are organizational features that have led some of us to emphasize that the larger organizing logic in that period was one centered in international regimes aimed at protecting national economies from external economic forces. They were not aimed at forming a global economy. Although international, this period was geared toward building the national economy and protecting the national interest. No genuinely global system was set in place. In this context, the early BW system is particularly significant insofar as it aimed at something approaching genuine global governance for the good of each and all member states.1 But the United States was, both then and later, a reluctant participant in this larger effort and consistently sought to pursue its own advantage. The US pushed BW toward the development of state capabilities for enabling firms to be global; in practice, this meant US firms, since these were dominant at a time when other major powers were recovering from massive war destruction. And it was these recovering states that were also far more disposed toward an international system that would ensure balance. It is useful to distinguish two phases before the breakdown of the early 1970s. In its first 12 years, and in its framers’ concept, the BW system was a supranational authority for protecting national governments.2 Eventually, it evolved into a market-centered

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system dominated by private banks, particularly US banks. Neither of these phases was akin to the current global economic system. In my reading, much had to come together to reach the major tipping point for a new organizing logic that reoriented state capabilities toward global projects (see Sassen 2008: ch. 4). The strong unilateral pursuit of global dominance for its firms by the United States was not enough and was a different type of project from that of shaping today’s global economy. Even the American push for an international system dominated by markets and firms was not enough to tip the international system into the new global phase that began in the 1980s. Yet many of the capabilities for international operation developed before and with BW were to become critical for the implementation of a global economy. Methodologically this entails distinguishing the particular components from the larger whole. Among these are a series of capabilities involving both state and nonstate actors. This was necessary to have major cross-border financial flows after World War II. But it was not enough to secure the existence of a global financial market. Similarly, cross-border trade flows are not enough to create a global trading system. The particular assemblage of territory, authority, and rights wired into the formation of today’s global financial market and global trading system differs sharply from that of earlier international systems for handling cross-border flows. Thus, for instance, territory does not disappear from our global electronic financial system; rather it is repositioned as a network of a hundred plus global cities with major financial centers. And so are authority and rights: neoliberal policy transfers not only power, but also authority to global financial markets and away from national states, and it develops a range of new types of rights for global firms in foreign countries. At the same time, not everything about these three conditions changes—national borders have not changed much and national states continue to be indispensable actors. It is rather that the BW and the current global era are two very distinct assemblages of institutional, technical, and spatial components, each with its specific organizing logic even though they both depend on the International Monetary Fund (IMF) and national state policy. This type of analysis can accommodate the importance of both the BW capabilities for the current system and the constitutive differences of these systems—each with its particular organizing logic. One indicator of this constitutive difference is the sharp policy shifts that took off in the 1980s, from protectionisms of all sorts to deregulations of all sorts. It points to the specificity of the larger assemblage of elements that constitutes today’s global financial system. It is not simply the power of finance and multinational corporations that reconfigure the system. Significant for finance are the new forms of private authority, actually enabled by the growing power of the executive branch of government, which in turn further feed executive branch power (Sassen 2008: ch. 4). Present in this dynamic is the possibility of an articulation between the executive branch and the financial system that cannot be simplified as either “the decline of the state” or the dominance of finance over the state. Nor can it be seen as a mere continuation of BW multilateralism.

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Two framing features radically distinguish the postwar BW financial system, especially in its first decade, from the current global system, even if the latter incorporates some BW rules. One is the role of financial markets. Until the 1950s financial policy was cautionary, regulatory controls were in place, and the stock market was relatively inactive. The central policy issue was unemployment, not free trade or global finance as it became in the 1980s (Tabb 2004). In fact, unemployment was seen as resulting from free trade.3 The early phase of the BW project involved the making of a global system to protect national economies against major crises. While it is not easy to disentangle the causal interactions between policy and stock markets, governments generally kept these policies in place even as growth resumed and stock markets revived in the 1950s. This became unacceptable in the 1980s. The second major framing condition was the use of managed exchange rates and controls on international capital flows to protect the financial system from international competitive and exchange rate pressures. This insulation was the norm in the world economy of that time (Eichengreen 2003; Helleiner 1999). All the major powers supported systems for domestic economic management—including the United States. The most familiar of these policy systems are Britain’s Keynesian welfare state, West Germany’s “social market,” France’s “indicative planning,” and Japan’s Ministry of International Trade and Industry (MITI) model of systematic promotion of export industries. There was a trade-off in the early BW phase between embedded liberalism in the international trading and production order and increased domestic economic management aimed at protecting national economies from external disruptions and shocks. Underlying this policy stance was a concern with the redistributive effects of capitalist economies. Keynes proposed making debtor and surplus countries work at returning the international system to balance—which the United States, then the leading surplus country, rejected.4 Keynes wanted easier borrowing for debtor nations (by then Britain was a debtor nation) and prevention of capital flight.5 The actual regime adopted was not quite what Keynes had proposed (Kapstein 1994: 93; Ruggie 1998: 265; Tabb 2004: 112). Bretton Woods delivered multiple capabilities for globalizing finance. But these framing aims amounted to a different organizing logic from what was to become necessary for the current global financial system.

The global capital market: power and norm-making The many negotiations between national states and global economic actors that led to our current global financial system generated a de facto normativity. Among familiar components are exchange rate parity, privileging low inflation over employment growth, and the variety of items found in IMF conditionality.6 The claims and criteria

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for policymaking that emerge as legitimate overrode older norms that privileged expenditures to ensure the well-being of people at large; those older norms are now seen as making states “less competitive” in a normative context where states are expected to become more so. In my reading (2008: ch. 5), this normative transformation entails a privatizing of capacities for making norms, capacities we have associated with the state in our recent history. This brings with it strengthened possibilities of norm-making in the interests of the few rather than the majority. In itself, this is not new. New is the formalization of these privatized norm-making capacities and the sharper restricting of who benefits. This privatizing also brings with it a weakening and even elimination of public accountability. In practice this might not appear to be much of a change given multiple corruptions of the political process. But the formalizing of this weakened public accountability is consequential. This was the setting for the ascendance of the post-1980s global financial system. The global capital market represents a concentration of power capable of systemically, not just through influence, shaping elements of national government economic policy and, by extension, other government policies. The powerful have long been able to influence government policy (Arrighi 1994). But today it is also the operational logic itself of the global financial system that becomes a norm for “proper” economic policy (Sassen 2008: ch. 5). These markets can now exercise the accountability functions formally associated with citizenship in liberal democracies: they can vote governments’ economic policies out or in; they can force governments to take certain measures and not others. Given the properties of the systems through which these markets operate—speed, simultaneity, and interconnectivity—the resulting orders of magnitude give them real weight in the economies of countries and their policymaking. There has long been a market for capital and it has long consisted of multiple, variously specialized, financial markets (e.g., Eichengreen 2003; Helleiner 1999). It has also long had global components (Arrighi 1994; Eichengreen 2003; Sinclair 2008). Indeed, a strong line of interpretation in the literature of the 1990s (e.g., Hirst and Thompson 1996) is that the post-1980s market for capital is nothing new and represents a return to an earlier global era—the turn of the century and, then again, the interwar period. However, all of this holds only at a high level of generality. When we factor in the specifics of today’s capital market some significant differences emerge with those past phases. I emphasize two major ones here. One concerns today’s far higher level of formalization and institutionalization of the global market for capital, partly an outcome of the interaction with national regulatory systems that themselves gradually became far more elaborate over the last hundred years (see Sassen 2001: chs 4 and 5). The second concerns the transformative impact of the new information and communication technologies, particularly computer-based technologies (henceforth referred to as digitization). In combination with the mix of dynamics and policies we usually refer to as globalization they have constituted the capital market as a distinct institutional order, to be differentiated from other major markets and circulation systems, such as global trade.

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One outcome of these processes is the formation of a strategic cross-border operational field constituted through the partial disembedding of specific state operations from the broader institutional frame of the state; this entailed a shift from national agendas to a series of new global agendas. The transactions are strategic, cut across borders, and entail specific interactions among government agencies and business sectors, to address the new conditions produced and required by corporate economic globalization. They do not engage the state as such, as in international treaties, or intergovernmental networks. Rather, these transactions consist of the operations and policies of specific subcomponents of diverse institutional orders, including particulalr state agencies (for instance, technical regulatory agencies, specialized sections of central banks and ministries of finance, special commissions within the executive branch of government, etc.), components of the supranational system linked to the economy (IMF, World Trade Organization (WTO)), and private non-state actors. In this process these transactions push toward convergence across countries in order to create the requisite conditions for a workable global financial system. This global financial system, in turn, is embedded in a vast array of specific, often highly specialized, bits of state and supranational institutions; it does not only consist of its firms, exchanges, and electronic networks (Sassen 2008: 348–65, ch. 5). There are two distinct features about this field of transactions that lead me to posit that we can conceive of it as a disembedded space in the process of becoming structured. The transactions take place in familiar settings: the state, the interstate system, the “private sector.” But the practices of the agents involved are constructing a distinct assemblage of bits of territory, authority, and rights that functions as a new type of operational field. In this regard, it is a field that exceeds the institutional world of the interstate system and of “the global economy.” Insofar as interactions between these specific state actors and specific private corporate actors provide substantive public rationales for developing national and international policy, it is an operational field that denationalizes state agendas. That is to say, the rationales for global action of those specific state and corporate actors run through national formal law and policy, but are in fact rationales that denationalize state policy (Sassen 2008: ch. 4). This can bring with it a proliferation of rules that begin to assemble into partial, specialized systems of law only partly embedded in national systems, if at all. Here we enter a whole new domain of private authorities—fragmented, specialized, and increasingly formalized but not running through national law per se. Two sets of interrelated empirical features of these markets capture the rapid transformation since the mid-1980s.7 One is accelerated growth, partly due to electronic linking of markets—both nationally and globally—and the sharp rise in innovations enabled by both financial economics and digitization. The second is the sharp growth of a particular type of financial instrument—the derivative—a growth evident both in the proliferation of different types of derivatives and in its becoming the leading instrument in financial markets.8 This diversification and dominance of derivatives has made finance more complex and enabled far higher growth rates than those of other globalized sectors.

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Finance and its orders of magnitude: overtaking whole economies There are two phases in this short but accelerated history of post-1980 finance, one going into the early 1990s and the second one taking off in the late 1990s. During this post1980s growth, the global capital market became an increasingly necessary component in an expanding range of domains. Thus diverse kinds of government debts began to get financed through the global market—including the kinds of debt that were thought to be basically local, such as municipal debt. This has led to a sharp financial deepening in many economies. Between 1980 and 2000, the total stock of financial assets increased three times faster than the aggregate gross domestic product (GDP) of the 23 highly developed countries that constituted the Organisation for Economic Co-operation and Development (OECD) for much of this period; and the volume of trading in currencies, bonds, and equities increased about five times faster and now surpasses aggregate GDP by far. The worldwide (notional) value of traded derivatives, which came to account for most financial market transactions, was $30 trillion in 1994, $80 trillion by 2000, and $270 trillion by mid-2005, for a 240 percent increase as of 2001, pointing not only to higher levels in values traded but also to an increase in the growth rate (BCBS 2005 21). To put this in perspective it is helpful to compare it to the value of other major components of the global economy at a time of high growth, for example, cross-border trade ($14.4 trillion in 2006) and global foreign direct investment stock ($6 trillion in 2000 and $8.2 trillion in 2003) (WTO 2005: 3; UNCTAD 1998, 2005: 9). Annual foreign exchange transactions were ten times as large as world trade in 1983 but 70 times larger in 2004, even though world trade also grew sharply over this period.9 In 2001, the average daily turnover in foreign exchange markets was $1.3 trillion and, in 2004, $1.8 trillion (BCBS 2005).10 In many ways the international financial market from the late 1800s to the 20th century interwar period was as massive as today’s if we measure its volume as a share of national economies and in terms of the relative size of international flows. This fact is critical to scholars who argue that globalization is not new (e.g., Hirst and Thompson 1996). The international capital market in the earlier period was large and dynamic, highly internationalized, and backed by a healthy dose of Pax Britannica to keep order. The extent of its internationalization can be seen in the fact that in 1920, for example, Moody’s rated the bonds issued by about 50 governments to raise money in the American capital markets (Sinclair 1994; 2008). The depression sharply reduced this internationalization, and it was not until the late 1980s that Moody’s was once again rating the bonds of about 50 governments.11 As recently as 1985, only 15 foreign governments were borrowing in the US capital markets. But in my reading it is not simply a question of volumes: the type of internationalization also matters. Institutional investors are not new (see Sassen 2008: ch. 3); it

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is the diversity of the types of funds and the rapid escalation in the value of their assets that is one of the key factors making this global epoch different. In the United States, institutional investors as a group came to manage two-fifths of US households’ financial assets by the early 1990s, up from one-fifth in 1980. By 2001 these assets had reached $19.2 trillion, notably in pension funds and insurance companies. Assets of US institutional investors rose from the equivalent of 59 percent of GDP in 1980 to 136.3 percent in 1993. All these trends continued in the second phase that took off in the 1990s. The assets of pension funds more than quadrupled in the United States from $1.5 trillion in 1985 to $11 trillion in 2004. The OECD weighted average asset-to-GDP ratio for pension funds increased from 68.0 percent of GDP in 2009 to 71.6 percent of GDP in 2010. The United States saw an increase of 5 percentage points in the value of its asset-to-GDP ratio in 2010, equivalent to a gain of $1 trillion in assets, from $9.6 trillion to $10.6 trillion (OECD 2011a). It should be noted that the weight of pension funds relative to the size of the economy shows sharp variation among the countries covered by OECD data. Thus in 2010, the Netherlands (135 percent), the UK (86.6 percent), and the US (72.6 percent) were among the highest, whilst Germany (5.2 percent) and France (0.2 percent) were among the lowest (OECD 2011a: Figure 5). It is the rise of hedge funds that stands out in this post-1990s phase (Maslakovic 2010; OECD 2011b). Hedge funds, among the most speculative of financial institutions, sidestep certain disclosure and leverage regulations by having a small, private clientele and, frequently, by operating offshore. While they are not new, their size and their capacity to affect the functioning of markets grew enormously in the 1990s and they emerged as a major force by the late 1990s. According to some estimates they numbered 1,200 with assets of over $150 billion by mid-1998 (BCBS 1999), which exceeded the $122 billion in assets of the total of almost 1,500 equity funds as of October 1997 (UNCTAD 1998). By 2005 they numbered over 9,000 and the global hedge fund industry stood at a reported $1.5 trillion (BCBS 2005b: 79). Both types of funds need to be distinguished from asset management funds, of which the top ten were estimated to have $10 trillion under management by 2006. 12 By 1996 it is clear that the four main components in the world’s financial assets were equities, private debt securities, government debt securities, and bank deposits. From 1996 to 2006, just before the crisis, the first two grew the fastest, at average annual compound rates of over 10 percent, compared to around 7 percent for the other two. In 2006, equities grew by 20 percent—$9 trillion (in constant exchange rates), accounting for “nearly half the total increase in financial assets” in 2006 (McKinsey 2008: 11). Global financial stock has continued to rise since 2008, and reached $212 trillion in 2010 (McKinsey 2011: 2). To contextualize the meanings of these numbers it helps to compare them to global GDP. The ratio of global financial assets to global GDP was nearly 350 percent in 2006, and after one of the worst financial crises, was back up to 336 percent in 2010 (World

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Bank 2011). The number of countries where financial assets exceed the value of their GNP more than doubled from 33 in 1990 to 72 in 2006. In most highly developed countries, the value of financial assets was up to three times the size of their GDP with a growing number at over four times (the United States, Netherlands, Japan, Singapore, and others). In the United States it was 450 percent of GDP (McKinsey 2008: 11). But we find this trend also in countries at other levels of development: thus China’s financial assets are worth three times its GDP. A year before the financial crises began in 2007, the total value of the world’s financial assets grew by 17 percent (in nominal terms, 13 percent at constant exchange rates) from 2005 to 2006, reaching $167 trillion, an all-time high, up from $12 trillion in 1980, $94 trillion in 2000, and $142 trillion in 2005. This growth is far higher than that of the other major components of the global economy: trade and foreign direct investment. While we cannot make a causal link, diverse indications do connect this type of economic system to the rapid growth of inequality that took off in the 1980s (Sassen 2001: pt 3, 2010) and reached extreme dimensions after the crisis of 2008 (Mishel 2004, 2007; Sherman and Stone 2010). Figure 1.1 shows the sharp increase in the income ratio of the highest earning decile to the lower earning deciles in the two periods that include the major financial crises of respectively the 1930s and 2008 onward. The Keynesian decades show a decline in the share of the top decile, from 42 percent to 33 percent, which points to the expansion of a middle class. Beginning in the 1980s, the top decile again began to receive an increasingly high share of total income.

45.0%

40.0%

35.0%

2002

1997

1992

1987

1982

1977

1972

1967

1962

1957

1952

1947

1942

1937

1932

1927

25.0%

1922

30.0%

1917

Share (in %), excluding capital gains

50.0%

figure 1.1 US Top Decile Income Share of National Income, 1917–2005 *Income is defined as market income but excludes capital gains (Source: Mishel 2004)

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Why does global finance need financial centers? One key element in the larger assemblage of geographies and institutions that constitute the global financial system is financial centers. Given electronic networks and trading, we might have expected the number of “international” centers to fall. Instead, the opposite is true—the number of centers has grown. This can easily be seen as a continuation of the BW era since, with few exceptions, these centers existed by then, and long before. But this isn’t the case. In that earlier era, each country’s financial center duplicated all core and specialized functions, given relatively closed national economies. Today’s centers are globally articulated with each other, tend to specialize in particular sectors, and have eliminated many of the redundant functions of the earlier era. Let me elaborate. The proliferation of such “global” financial centers as strategic spaces is counterintuitive in what is an increasingly electronic and globally integrated financial system: one might expect a few global centers to handle matters in a globally integrated system. Besides growing numbers, today’s financial centers have also expanded the diversity of their functions. Thus, over the last decade private closed investment networks run by banks and traders have grown sharply and so has the forming of alliances among exchanges and takeovers of exchanges. In short, the organizational architecture of financial centers increasingly deborders the exchanges that once constituted the financial center. Finally, and also counterintuitively, financial centers have become increasingly specialized. We might have expected a different pattern given the technological capacities of computer-centered networks along with the possibility of rich firms voting with their feet and locating in a few super-financial centers. Rather than concentrating all necessary functions in a few mega-financial centers, the opposite trend is evident. Here I examine the elements that contribute toward an explanation of these institutional and spatial features of global finance in the current epoch. In my research I find three constraints that keep today’s global and mostly electronic financial system from being the placeless electronically distributed system one might have expected. I develop this at length elsewhere (Sassen 2008: 348–65, ch. 5; 2011: ch.5). 1) The problem of incomplete knowledge. Firms have always confronted incomplete knowledge in market economies. When such firms go global, this problem becomes acute. The specific contribution of the financial center vis-à-vis the incomplete knowledge problem, especially for global actors, is that its diverse networks, information loops, and professionals coming from diverse parts of the world, together produce a particular type of knowledge capital. I refer to it as urban knowledge capital—a capital that is more than the sum of the knowledge of the professionals and the firms in a city. Analytically, I posit this is a key element in the economic production function of the global city (Sassen 1991/2001: ch. 6; 2011: ch. 5). The proposition I developed to organize

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the combination of factors involved is that the more speculative, digitized, subject to speed, and globalized a firm’s operations are, the more acute is its incomplete knowledge problem, and hence the more dependent on the financial/business center as a strategic site. 2) The growing specialization of financial centers. The global financial system thrives both on standardized products and technical infrastructures, and on specialized differentiation in much of high finance. Each of the leading financial centers has developed its specialized advantages over the last two decades. No two of them are the same. Globalization homogenizes standards, a fact that has led many to interpret this as homogenization of markets and of urban economies. But the homogenizing of standards can coexist with growing specialization. In contrast, before the 1980s, each “closed” national economy duplicated all functions necessary for international transactions, and specialization was a somewhat secondary aspect. 3) Finance is about financializing the nonfinancial. In the two preceding sections in this chapter I have examined finance as an invasive economic sector. Today’s global financial firms are largely geared toward entering the thick specificities of nonfinancial sectors and of national economies not yet fully articulated with the global economy. Financial centers, and even more so global cities, are a bridge, an intermediate space between the globalized part of finance and the thick national and local cultures of investment of a country or a region. We can think of financial centers as sites for producing knowledge components that address the problem of incomplete knowledge of firms and investors in market economies. The proliferation of secondary financial centers now integrated into the global system also serves this function. This making of knowledge components takes different forms. We can conceive of the advanced corporate services as producers of “organizational commodities” (Sassen 2001: ch. 4). These become increasingly complex and necessary when a firm operates in a globalized space, rather than the more familiar home setting of a closed national economy. This holds for global firms and markets, no matter what the sector—mining, agribusiness, finance, insurance, and so on. It is simply more acute in high finance given the speed and speculative character of trading. Thus the more digitized, speculative, and globalized the operations of a financial firm, the more acute is its incomplete knowledge problem, and hence the more dependent on knowledge-making firms and centers. This then also explains why global capitalism produced a systemic demand for a growing number of global cities across the world as globalization expanded in the 1990s and onward. Each of these is a site for the production of urban knowledge capital, which is in a good part specific to each city. Indeed, even in the 1980s when these patterns were merely emergent, I found this global phase needed and stimulated the specialized differences of cities. Thus, already in the 1980s, I found significance in what was then a rather elementary division of functions among New York, London, and Tokyo, at the time the three strategic global cities articulating an emergent new phase of global capitalism: Tokyo as the major exporter of “undeveloped” money capital, London the most developed financial entrepot given its old imperial

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geography, and New York as the silicon valley of finance. I thus argued that the intensifying problem of incomplete knowledge as globalization expands is partly addressed through a systemic demand for more strategic sites (global cities) and multiplying divisions of functions among such sites. A second aspect in the making of knowledge concerns the meaning of information. There are two types of information in this global financial world of high-speed transactions. One is the datum: At what level did Wall Street close? Did Argentina complete the public sector sale of its water utility? Has Japan declared such-and-such bank insolvent? But there is a far more difficult type of information, akin to a mix of interpretation, evaluation, and judgment. It entails negotiating diverse data sets and interpretations in the hope of producing a higher-order datum. Access to the first kind of information is now global and immediate, thanks to the digital revolution. You can be a broker in the Colorado mountains and have access to this type of information. But the second type of information requires a complicated mixture of elements—the social infrastructure for global connectivity—and it is this that gives major financial centers a leading edge. One can, in principle, reproduce the technical infrastructure anywhere. Shenzhen, for example, has technical connectivity matching Hong Kong’s. But does it have Hong Kong’s social connectivity? When the more complex forms of information needed to execute major international deals cannot be gotten from existing databases, no matter what a firm can pay, then that firm needs the social information loop with the associated interpretations and inferences that come with bouncing off information among talented, informed people. The importance of this input has given a whole new weight to creditrating agencies, for example. Part of the rating has to do with interpreting and inferring the quality of a firm’s or government’s resources. Credit-rating firms are in the business of producing authoritative interpretations and presenting them as information available to all, even though they get it wrong regularly (Sinclair 2008). But firms, especially global firms in finance, need more than what credit-ratings firms sell. They need to build this advanced type of interpretation into their daily work process, and this takes not only talent but also information-rich milieux (Sassen 2008: 346–65, ch. 7). Financial centers, and especially the greater diversity and complexity of global cities, are such milieux. Each of today’s leading financial centers has distinctive strengths, as is well captured in comparing such familiar cases as New York, Paris, Frankfurt, Hong Kong, and so on. Further, this differentiation is also evident inside countries, as is reflected in the familiar pairs of New York and Chicago, and Hong Kong and Shanghai. London and New York, with their enormous concentrations of resources and talent, continue to be the powerhouses in the global network for the most strategic and complex operations for the system as a whole, but they are increasingly dependent on the larger network of centers and no longer have the absolute primacy they had 15 years ago. This combination of more and more globally integrated centers along with the growing strength of a limited number of those centers is also evident, with its own specifics, inside countries. What stands out is that this pattern toward the consolidation of one or two leading financial centers in a county is a function of rapid growth in the sector, not necessarily of decay in the losing cities. In the United States, for example, New York

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concentrates all the leading investment banks with only one other major international financial center, Chicago, in this enormous country. Boston is a strong financial center but has lost market share to New York, as has Philadelphia. Several of the other financial centers in the US have also lost market share even as they may be growing. Sydney and Toronto each took over functions and market share from what were once the major commercial centers in their respective countries, Melbourne and Montreal. So have São Paulo and Mumbai, which gained share and functions from, respectively, Rio de Janeiro in Brazil and New Delhi and Calcutta in India. These are all enormous countries, and one might have thought that they could sustain multiple major financial centers. In France, Paris today concentrates larger shares of most financial sectors than it did in the 1970s, and once-important stock markets such as Lyon have become “provincial,” even though Lyon is today the hub of a thriving economic region. Milan privatized its exchange in September 1997 and electronically merged Italy’s ten regional markets. Frankfurt now concentrates a larger share of the financial market in Germany than it did in the early 1980s, as does Zurich in Switzerland. Further, these processes of growing concentration moved fast. For example, by 1997, Frankfurt’s market capitalization was five times greater than all other regional markets in Germany combined, whereas in 1992, it had been only twice as large. These patterns are evident in countries worldwide. It continues today, often under novel formats. Thus the European Union’s singlecurrency Eurozone spells the end of an era in which each country had its full-fledged financial center; a steep hierarchy is very likely, with Frankfurt and Paris at the top and a crisscross of alliances centered in either of these major centers or among centers not included in those alliances. The dominance of the leading centers rests partly on the fact that one of the ways in which the global financial system grows is by incorporating more and more national economies. This is a process that happens through the development of a state-of-the-art financial center in each country—which often evolves into a second- or third-tier global city. Table 1.1 illustrates this proliferation of global financial networks that now include more and more centers, mostly along highly specialized vectors—each center integrated through particular commodities or securities. Here I have selected just some of the many cases to illustrate this juxtaposition of ongoing dominance by a limited number of centers and a proliferation of financial centers integrated into the global system. The financial centers of a growing number of less powerful countries worldwide are increasingly fulfilling gateway functions for the global financial system. This has facilitated the proliferation of sources of, and destinations for, investment. Gateway functions are their main mechanism for integration into the global financial market rather than, say, the production of innovations to package the capital flowing in and out. The production of innovations tends to remain concentrated in the leading 20 or so centers, as these have not only the specialized talents but also the clout to persuade investors to buy innovative instruments. Further, the complex operations in most second- and third-tier financial centers often are executed by foreign global investment, accounting, and legal services firms through affiliates, branches, or direct imports of those services. These gateways for the global market are also gateways for the dynamics of financial crises:

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Table 1.1 Top five performing broad market indexes last year by major regions, in local currency Rank

Americas

1. 2. 3. 4. 5.

Buenos Aires Stock Exchange Lima Stock Exchange BM&FBOVESPA Colombia Stock Exchange Santiago Stock Exchange

Rank

Asia/Pacific

1. 2. 3. 4. 5.

Colombo Stock Exchange Shenzhen Stock Exchange Bombay Stock Exchange National Stock Exchange India Indonesia Stock Exchange

Rank

Europe/Africa/Middle East

1. 2. 3. 4. 5.

Istanbul Stock Exchange Tel Aviv Stock Exchange Oslo Bors Luxembourg Stock Exchange Warsaw Stock Exchange

% change 2009/2008 103.6% 101.0% 82.7% 53.5% 46.9% % change 2009/2008 125.2% 117.1% 90.2% 88.6% 87.0% % change 2009/2008 96.6% 78.8% 60.1% 54.6% 46.9%

(Source: World Federation of Exchanges 2010)

capital can flow out as easily and quickly as it flows in. And what was once thought of as national capital can now as easily join the exodus. Although electronic networks are growing in number and in scope, they are unlikely to eliminate the need for financial centers. Rather, they are intensifying the networks connecting such centers in strategic or functional alliances among exchanges in different cities. What is important to note is that these alliances and takeovers have a format that distinguishes them from cross-border mergers and acquisitions in other economic sectors, where elimination of plants and offices is often part of the aim. The alliances and takeovers of exchanges aim at keeping the distinctive exchanges—a key purpose for the takeover is precisely that each exchange has its own bridges into a national economy (Sassen 2008: chs 5 and 7; 2011: chs 4 and 5). Ironically, the current wave of alliances and takeovers of financial exchanges contributes to strengthen the combination of two geographies described earlier: growing numbers of globally integrated centers and at the same time ongoing dominance of major centers.

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Conclusion—beyond institutions: a larger ecology The organizing proposition of this chapter is that the global financial system is an assemblage of diverse components that deborders the narrowly defined institutions of finance—firms and exchanges. I examined three core components of the larger assemblage that is global finance today. The first is the particularity of the internationalism of our current global financial system. It diverges sharply from the BW-era internationalism. The fact that our current system uses capabilities developed through the BW system has led some to see BW as the origin of the current system. In contrast, I find that this disjuncture is possible because the different organizing logic of the current system can re-mark capabilities of the earlier period. More generally, using the case of the BW international system illuminates the fact that internationalism by itself is too general a condition to explain our current global system. Further, it shows that the participation of the state is also too general a notion: the state was an active participant in both, especially through the executive branch, but the character of this participation was very different. The second core component is the critical role played by the privatizing of normmaking capacities that were once the exclusive domain of national states. The switch into our global system required extensive making of new norms that had little relation to the norms of the BW system. The latter had sought to strengthen national state capacities to confront financial crises and to develop a supranational system that could protect national economies from excessive international fluctuations. These features contrast sharply with the current global financial system and with the privatizing of norm-making in the interest of finance itself rather than national economies. The third element is the role and the geography of financial centers, part of both the BW era and the current one—and of course, partly also of much earlier eras. But even if present in both eras, their role can vary considerably. In the BW era we saw a recurrence of similar functions in financial centers integrated into the international financial system. Financial centers were quite routinized. In the current financial system, these centers are highly differentiated strategic production sites for innovations, and benefit from considerable deregulation and privatized norm-making capacities. They are strategic in that they contribute to knowledge-making in a context where incomplete knowledge becomes acute given the speed of trading, the orders of magnitude involved, and the multiplication of specialized financial markets.

Notes 1. The Bretton Woods conference in 1944 was the last stage of a process initiated by Britain and US Treasury officials working on the rules for a postwar monetary and trade regime, as well as the conditions for countries’ participation.

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2. We see considerable shifts in the balance between internationalists and nationalists in the postwar years. Thus, in 1948 Congress rejected the International Trade Organization (ITO), which the executive had worked hard to change and negotiate, because it would have undermined state sovereignty. The ITO was not all bad: it gave Less Developed Countries (LDCs) some preferential treatment in the development of finance and commodity agreements, which were not included in the later General Agreement on Tariffs and Trade (GATT); thus after Congress rejected the ITO, the LDCs felt little incentive to join GATT. 3. There was neither strong opposition to free trade nor much serious consideration of it. Viner (1958) notes at the time that no one was addressing the question of free trade or, indeed, even talking about it. 4. The United States insisted that surplus countries not be penalized. Eventually the United States became far less competitive and a massive debtor; nonetheless its hegemonic position allowed it to escape the disciplining of the supranational system and market dynamics that other debtor countries were subjected to (Sassen 1996: ch. 2; 2008a: ch. 4). Paralleling Britain at its time of world dominance, in the postwar period the United States sought an open trading system, while most other countries sought protections under national developmentalist regimes. There is a vast scholarship on the postwar asymmetry between the United States and most other countries that traces in enormous detail the consequences for different actors of having an open trading system under US dominance versus the advantages for development of nationally protected economies; it is quite different from the scholarship that emerges in the 1980s and 1990s. It is impossible to do justice here to that postwar scholarship. 5. Tabb (2004: ch. 5), among others, finds that there is a strong case to be made that the high costs borne by the more vulnerable components of the world community could have been avoided if Keynes’s position (that surplus countries had as much responsibility as debtor ones to re-establish equilibrium) had prevailed. 6. Since the Southeast Asian financial crisis there has been a revision of some of the specifics of these standards. For instance, exchange rate parity is now evaluated in less strict terms. 7. There are other factors that are significant, particularly institutional changes, such as the bundle of policies usually grouped under the term deregulation and, on a more theoretical level, the changing scales for capital accumulation. For a full analysis of these issues, see Eichengreen (2003), Eichengreen and Fishlow (1996), Abolafia (2001), Swedberg (2004), and Krippner (2011) on deregulation and re-regulation in the financial markets today; on new scales for capital accumulation, see “Special Issue: Globalization and Crisis” (2010) for some recent developments; for a state of the art examination of the full array of specialized corporate services, see Bryson and Daniels (2009). 8. See Sassen (2008a: 350) for a brief description. 9. The foreign exchange market was the first one to globalize, in the mid-1970s. Today it is the biggest and in many ways the only truly global market. Daily turnover has gone from about $15 billion in the 1970s, to $60 billion in the early 1980s, and $1.8 trillion in 2003. In contrast, the total foreign currency reserves of the rich industrial countries amounted to about $1 trillion in 1999 and $3 trillion in 2004. 10. Other comparisons at high points before the 2008 crisis were the global market capitalization of firms listed on the WFE’s 54 member bourses, which was $51 trillion in January 2007 compared with World GDP of $44 trillion .

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11. Switzerland’s international banking was, of course, the exception. But this was a very specific type of banking and does not represent a global capital market, particularly given basically closed national financial systems at the time (I have examined this difference in Sassen 1991: ch. 4). 12. In that same period, assets of insurance companies increased by 110 percent (from $1.6 trillion to $3.3 trillion), assets of commercial banks grew by 100 percent (from $3.5 trillion to $7 trillion), and deposits of commercial banks increased by 79 percent (from $2.5 trillion to $4.5 trillion) (Investment Company Institute 2003: 1 2n. 4). The level of concentration is enormous among these funds, partly as a consequence of mergers and acquisitions driven by the need for firms to reach what are the de facto competitive thresholds in the global market today.

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McKinsey (2008). “Mapping Global Capital Markets Fourth Annual Report.” McKinsey Global Institute, January. (accessed May 16, 2011). ——– (2011). “Mapping Global Capital Markets 2011.” McKinsey Global Institute, August. (accessed May 16, 2011). Mishel, L. (2004). “Unfettered Markets, Income Inequality, and Religious Values.” Economic Policy Institute. (accessed July 26, 2008). ——– (2007). “Who’s Grabbing All the New Pie?” Economic Policy Institute. (accessed July 26, 2008). —— Murphy, Craig N. (1994). International Organization and Industrial Change: Global Governance since 1850. New York: Oxford University Press. OECD (Organisation for Economic Co-operation and Development) (2011a). “Pension Funds Climb Back to Pre-crisis Level but Full Recovery Still Uncertain.” Pension Markets in Focus, 8. (accessed July 30, 2011). ——– (2011b). “Institutional Investors’ Assets.” (accessed July 30, 2011). Picciotto, S. and Mayne, R. (1999). Regulating International Business: Beyond Liberalization. London: Macmillan. Ruggie, J. G. (1998). “Introduction: What Makes the World Hang Together? Neo-utilitarianism and the Social Constructivist Challenge.” In Constructing the World Polity: Essays on International Institutions. London: Routledge. Sassen, S. (1998). Losing Control? Sovereignty in an Age of Globalization. New York: Columbia University Press. ——– (2001). The Global City (2nd edn, 1st ed 1991). Princeton, NJ: Princeton University Press. ——– (2008). Territory, Authority, Rights: From Medieval to Global Assemblages. Princeton, NJ: Princeton University Press. ——– (2009) “When Local Housing Becomes an Electronic Instrument: The Global Circulation of Mortgages—A Research Note.” International Journal of Urban and Regional Research. Vol. 33, issue 2, pp.411–26. ——– (2010a). “Global Inter-City Networks and Commodity Chains: Any Intersections?” Global Networks 10/1: 24–37. ——– (2010b). “A Savage Sorting of Winners and Losers. Contemporary Versions of Primitive Accumulation.” Globalizations, March–June 2010, vol 7, nos 1–2, pp.23–50. ——– (2011). Cities in a World Economy (4th edn). Thousand Oaks, CA: Sage/Pine Forge. Sherman, A. and Stone, C. (2010). “Income Gaps Between Very Rich and Everyone Else More than Tripled in Last Three Decades, New Data Show.” Center on Budget and Policy Priorities, 25 June. (accessed September 22, 2011). Sinclair, T. J. (1994). “Passing Judgment: Credit Rating Processes as Regulatory Mechanisms of Governance in the Emerging World Order.” Review of International Political Economy, 1: 133–59. ——– (2008). The New Masters of Capital: American Bond Rating Agencies and the Politics of Creditworthiness. Cornell Studies in Political Economy. Ithaca, NY: Cornell University Press.

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Smith, S. J. (2012). Care-full markets: miracle or mirage? Tanner Lectures on Human Values 31 (in press). Cambridge: Cambridge University Press. Stephan, P. B. (2002). “Institutions and Elites: Property, Contract, the State and Rights in Information in the Global Economy.” Cardozo Journal of International and Comparative Law, 10: 305–17. Suter, C. (1992). Debt Cycles in the World Economy: Foreign Loans, Financial Crises, and Debt Settlements, 1820–1986. Boulder, CO: Westview Press. Swedberg, R. (2004). “Investors and the Conflicts of Interests in the US Brokerage Industry,” in K. Knorr Cetina and A. Preda (eds.), The Sociology of Financial Markets. Oxford: Oxford University Press, 187–206. Tabb, W. K. (2004). Economic Governance in the Age of Globalization. New York: Columbia University Press. UNCTAD (United Nations Conference on Trade and Development) (1998). World Investment Report 1998: Trends and Determinants. New York: United Nations. ——– (2010). World Investment Report 2010: Investing in a Low Carbon Economy, New York: United Nations. Viner, J. (1958). The Long View and the Short: Studies in Economic Theory and Policy. Glencoe, IL: Free Press. Walker, R. B. J. (1993). Inside/Outside: International Relations as Political Theory. Cambridge: Cambridge University Press. World Bank (2011). “World Development Indicators.” (accessed July 1, 2011). World Federation of Exchanges (2010). First Half 2010 Market Highlights. Paris: World Federation of Exchanges. WTO (World Trade Organization). (2005). International Trade Statistics 2005. Geneva: WTO. Zaloom, C. (2006). Out of the Pits: Traders and Technology from Chicago to London. Chicago: University of Chicago Press.

chapter 2

politics a n d fi na ncia l m a r k ets g erald f. d avis

Over the past generation, financial markets conquered the world. The number of countries with a local stock market doubled after 1985, and the market capitalization in emerging markets (formerly known as the “Third World”) topped $5 trillion by 2006. The fall of the Berlin Wall was followed by the creation of thousands of new public corporations in Eastern Europe. Hundreds of millions of new investors began buying and selling company shares from Chile to China to the United States, and financial news became pervasive. The range of things traded on financial markets also expanded from stocks and bonds to mortgage-backed securities, collateralized debt obligations, and life insurance contracts for the terminally ill. Households found themselves participating in global financial markets as buyers (through pension plans and mutual funds) and sellers (through securitized mortgages, credit card debt, auto loans, college loans, and insurance). Homeowners in Poland took out mortgages denominated in euros to take advantage of lower interest rates, and car buyers in Hungary took on loans in Swiss francs to buy Italian cars, giving them an immediate financial interest in central bank policies. The surprising interconnections created by global finance became evident during the financial crisis that began in 2008, when pensioners in Australia and Norway learned that their financial security depended on the mortgage payments of delinquent property speculators in Florida, and taxpayers in the UK learned that the banks they had bailed out might be responsible for repaying defrauded investors in the United States. Finance was at the center of the global economic crisis. Yet the impacts of the crisis were distributed in peculiar ways. Why was the United States devastated and not Canada? Why Iceland and not Denmark? Why Greece and not Turkey? Why the UK and not France? Why Ireland? The political reactions to the crisis also varied widely. The United States initially elected a substantially more liberal government, followed by an immediate right-wing backlash against “big government”; the UK went more

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conservative and implemented vast budget cuts in education and social welfare, followed by its own backlash; and the Greeks took to the streets to protest government austerity measures. Finance and politics were connected in deep yet unpredictable ways across different economies. The central argument of this chapter is that the structural organization of finance within a country reflects and shapes the organization of business and politics. By “structural organization of finance” I mean the ways that savings are channeled from households to businesses and other borrowers. This includes questions such as what are the mechanisms (e.g., markets, banks), who are the intermediaries, how is the banking industry organized, and what are the characteristic ways for corporations to raise financing. The structural organization of finance inherently implicates politics. One of the main stakes of politics is control of business, that is, who gets to control the decisions businesses make and how the fruits of business activity are divided. This is the domain of corporate governance—“the structures, processes, and institutions within and around organizations that allocate power and resource control among participants” (Davis 2005: 143). Although traditionally an obscure term of art used in law and business schools, corporate governance has recently become a central concern of scholars across many disciplines, including sociology, political science, economics, law, and business (Aguilera and Jackson 2010). This chapter seeks to integrate some of the theoretical threads that have emerged from disciplinary studies of finance and politics. I first describe how finance varies around the world and some of the efforts to create typologies of national systems. Finance is organized in starkly divergent ways, even among the largest and most successful economies (e.g., the United States, China, Japan, and Germany), with banks, markets, firms, and the state taking on characteristically different roles (Zysman 1983). I then review research from several disciplines on how law and domestic politics shape finance, and how finance creates interests within the polity. Contributions in this area have come from diverse academic domains, from sociology and political science to law and finance, and researchers have put forward theories proposing rather different dynamics to explain the interaction of finance and politics (e.g., Carruthers 1996; Gourevitch and Shinn 2005; Hall and Soskice 2001; La Porta et al. 1998; Roe 1994). I then shift to a discussion of how the practice of finance has changed with globalization over the past generation, and how the increasing size, scope, and reach of financial markets has altered some of the traditional “varieties of capitalism.” The balance among different institutional elements—product markets, labor markets, education systems, social welfare provision—has shifted due to the expansive spread of financial markets across geographic and social space. Hypertrophied finance created policy challenges that were resolved (or not) in diverse ways around the world. Finally, I conclude with a brief discussion of the financial crisis that began in 2008 and its implications for how researchers should think about finance and politics.

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Variation in finance around the world In spite of the homogenizing pressures of globalization, finance is organized in quite diverse ways around the world. Businesses can raise funds through wealthy families, through markets, through banks, through interfirm networks, through retained earnings, and in many other ways. Some countries, including most industrialized nations, have substantial stock markets and well-developed banking sectors to channel savings to business. Yet even among the wealthiest economies there are stark differences in how finance is organized. Consider the three largest economies in the OECD. The United States has traditionally had vast capital markets, and the bulk of its corporations are publicly traded. In 2009, the market capitalization of public corporations in the United States totaled over $15 trillion—slightly higher than GDP that year, albeit one-quarter lower than it had been two years earlier. Corporate ownership is typically dispersed in the United States, with the largest single shareholder often owning less than 10 percent of a company’s shares. Germany, on the other hand, had fewer public corporations than Pakistan in 2010—roughly 600—and large banks have traditionally held substantial stakes in even the largest public corporations. And Japan has many public corporations, like the United States, but their ownership was traditionally intertwined through crossshareholding arrangements with other corporations. The organization of finance correlates with many other aspects of a nation’s economy and polity. Social democracies often have relatively large and concentrated banks, less prominent capital markets, and their corporations tend to have concentrated ownership structures in which a single family or group might own a dominant stake. They also have lower levels of inequality, and their leading industries often include manufacturing firms that require a specially trained workforce. English-speaking countries tend to have more dispersed corporate ownership and a greater reliance on markets for financing rather than banks. Vanguard industries might include biotech, software, and other innovative industries that rely on venture capital, and the high payoffs to entrepreneurs and financiers contribute to relatively higher inequality. Scholars have proposed a variety of typologies to capture this correspondence. Among the largest economies, a simple dichotomy distinguishes between bank-based and market-based financing, exemplified by Germany and the United States (Zysman 1983). Political scientists drawing on a more extended set of dimensions distinguish between coordinated market economies and liberal market economies, with Germany and the United States again providing the paradigm cases (Hall and Soskice 2001). Yet another polarity that yields similar categories is the distinction between legal families, that is, countries whose legal systems were based on common law (primarily Englishspeaking countries and those that had been colonized by Great Britain) and countries whose legal systems were based on civil law (including most of Continental Europe and countries that had been colonized by France). The former have characteristically larger financial markets and stronger legal protections for small shareholders, while the latter

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frequently have small or nonexistent financial markets and weaker shareholder protections. Such typologies often rely on a relatively truncated set of countries, most often rich Western countries, Japan, and Korea. Often left out of the analysis are Africa, Latin America, the Middle East, and much of Asia. But they do point to a set of dimensions that covary with finance. As these typologies suggest, the connection between finance and politics implicates broader national economic systems. The organization of finance is a consequence of political decisions, a stake of political struggles, and a source of political interests and conflicts. It is a consequence because political struggles often result in constraints on finance (e.g., limits on the size, reach, and activities of banks) or in new possibilities (e.g., eliminating constraints on foreign investment). It is a stake because the organization of finance creates some of the basic ground rules over how the proceeds from business are distributed (e.g., in profits to shareholders vs. investments in worker training). And it is a source of political interests because actors’ position in the system of business and finance shape who benefits and who has a voice in economic choices (e.g., capital gains taxes arouse different interests in a country with widely distributed stock ownership than one without). As we will see, political outcomes reflect not just finance but broader economic systems in which finance is embedded.

Finance and national economic systems Financial markets have long played a critical but mercurial role in mediating between states and economies—“mercurial” because many aspects of financial markets elude direct control. In the late seventeenth century, England—with a limited monarch dependent on parliament for funds—developed financial markets, while France—with an absolutist monarch who could levy taxes at will—did not. Military technology had become costly at this point, and thus “War had become as much a test of financial strength as military power” (Carruthers 1996: 90). Because financial markets could raise the huge sums necessary for war quickly, Britain’s military power was enhanced by its financial markets, while France was weakened by their absence. State power, in short, depended on systems of finance, and financial markets were enhanced by limits in state power. Within a few decades Britain had become a global hegemon, projecting military power around the world and extending its empire and laws to far-flung colonies. Moreover, it had developed a set of institutions to support financial markets that comported well with its system of common law (Carruthers 1996). The organization of finance also had direct implications for the state’s ability to guide the economy. In Imperialism: The Highest Stage of Capitalism, Lenin ([1916] 1939) surveyed a set of wealthy economies and concluded that industrialization and industry consolidation had led to a situation in which a few banks, through their control of critical oligopolies, occupied the commanding heights of the economy. Concentrated finance created concentrated economic power, particularly within Germany and the

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United States. Thus, taking control of a nation’s largest banks was tantamount to taking control of the economy—at least in the most advanced industrial economies. The format of finance, in short, shaped the capacities of states to intervene in the economy. Subsequent political theorists built on this basic insight to unpack the links between states, finance, and business in different economies. Zysman (1983) argued that the organization of the financial system determined what levers government officials had over business, and thus how states might guide responses to industrial crises. He distinguished three main types of financial systems corresponding to the three largest economies at the time. Each format implied a different repertoire of policy strategies available to the state. In the United States the financial system was organized around financial markets with competitively established prices. In this situation, state and industry had an arms’ length relation. Companies led the process of industrial adjustment, while the state had very little leverage to guide industrial policy through finance. Japan had a credit-based financial system with government-administered prices that allowed government intervention in industry, and thus the state led industrial adjustment. Germany featured a credit-based system in which autonomous financial institutions had a preponderant influence on industry. This created a style of industrial adjustment that entailed negotiation among major social partners, including government, banks, companies, and often labor. This argument also suggested a potential model of national economic development. Countries that industrialized late—in this case, Germany and Japan—tended to have credit-based systems rather than market-based systems. Late development reduces some of the uncertainty around industrial planning: when the path to industrial development is already known and the best technologies and practices have emerged, it is more feasible for policymakers to seed the development of firms in critical industries that meet global standards. That is, a developmental state can guide industry through targeted finance through banks, acting as a surrogate for undeveloped financial markets. Thus, Evans (1995) describes how Korea, following the lead of Japan, rapidly industrialized by channeling finance to companies in keystone industries such as steel, shipbuilding, autos, and electronics, reinforcing dense links between the state and industry (and earning the nickname “Korea Inc.”). By the 1990s, Korea had become one of the dozen largest economies in the world and participated in a variety of vanguard industries, while the former “developmental state” had substantially stepped back from its directive role in the economy. The configuration of finance shapes the policy repertoire available to states to influence the economy. But late development alone cannot explain why finance looks the way it does around the world. During the decades after Zysman wrote, dozens of countries have opened stock exchanges. In 1990 China reopened its first stock market since the 1949 revolution, and by 2006 it was among the world’s largest—in a country still communist in name. Where did these configurations come from? And how do they change, if at all? One influential perspective came out of the “law and economics” school. In an important series of articles published in the late 1990s, four financial economists claimed that a

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country’s system of law had a permanent effect on its financial system, largely through its influence on the legal protections available to “minority” (noncontrolling) shareholders (La Porta et al. 1997, 1998, 2000). Legal systems can be classified along many dimensions, but a broad distinction applicable to most advanced economies is between civil law and common law systems. In civil law, codes of law are created by statutes and interpreted by judges, with relatively modest reference to precedent. In common law systems, prior court decisions create more or less binding precedents, and thus law as applied in practice can draw as much on precedent (case law) as on statute. Common law countries tend to have better-articulated protections for minority shareholders, and such protections tend to be a precondition for widespread stock ownership: few investors are willing to risk an investment in a firm in which a large shareholder can dominate corporate decision-making in ways that harm their interests. Financial markets and patterns of ownership differ in characteristic ways between common law and civil law countries. A basic dimension is size: common law countries generally have significantly larger financial markets relative to the size of the real economy (as measured by market capitalization/GDP). A second dimension is ownership concentration within particular firms: ownership tends to be much more dispersed in corporations domiciled in common law countries compared to those in civil law countries. Thus, market-based finance and corporate governance are much more prevalent in common law countries than in civil law countries (Clayton, Jorgenson, and Kavajecz 2006). An implication of this argument is that historical events long ago—whether a European country had been invaded by Napoleon in the early nineteenth century, or whether an African nation had been colonized by the British rather than the French— set nations on paths of financial organization that are still in place today. Former French colonies were stuck with small or nonexistent financial markets and concentrated corporate ownership, regardless of the helpful advice of the IMF on the benefits of creating domestic stock exchanges. Indeed, with the exceptions of Vietnam and Lebanon, stock exchanges are almost entirely absent from former French colonies, whereas they are widespread among former British colonies (Weber, Davis, and Lounsbury 2009). Moreover, the presence and vibrancy of financial markets is associated with subsequent economic growth, indicating that countries unable to sustain a financial market (such as former French colonies) are doomed to a permanently weaker economic trajectory (Levine and Zervos 1998). Yet historical comparisons show that finance waxes and wanes over time and thus cannot be fully determined by legal family. In the early part of the twentieth century, France and Japan both had vibrant equity markets. After World War I, however, France experienced a “great reversal” as its economy became more detached from trade with its neighbors and its financial markets retrenched (Rajan and Zingales 2004). In contrast, Germany and the United States could both be characterized as having bank-controlled “finance capitalism” on the verge of World War I. Many industries had become relatively concentrated in the United States (Chandler 1977), and three New York banks had each placed their officers on the boards of dozens of major corporations, often including the

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largest competitors in the same industry (Brandeis 1914). This was the situation that had piqued Lenin’s interest: the concentrated economic power of early finance capitalism was a small step from state control. Yet a generation later, the United States was the prototype of “managerial capitalism” in which financial institutions had been neutered and a new class of autonomous professional managers was in control of industry thanks to the broad dispersion of corporate ownership (Berle and Means 1932). This transition could not be attributed to a change in legal systems, as the United States was still firmly in the grip of Anglo-Saxon common law. We therefore need to find another explanation. Domestic politics provides one explanation for the expansion and contraction of finance and the relative power of different kinds of financial institutions. In the United States, populists have repeatedly mobilized to prevent the concentration of finance since the founding of the republic (Roe 1994). Banks were purposely kept relatively small and weak in the United States compared to other industrialized countries. Moreover, when banks grew large and powerful, as in the early twentieth century, policymakers intervened to limit their control of industry. By the time Other Peoples’ Money appeared in print in 1914, Congress had outlawed board interlocks among competitors and the biggest banks had recalled their executives from most corporate boards (Davis 2008). Within a decade, finance capitalism was merely a memory in the United States, and the famous “separation of ownership and control” was underway. This regime was reinforced by the 1933 passage of the Glass-Steagall Act, which formally separated commercial banking (making loans) from investment banking (underwriting and dealing in securities). For most of the twentieth century, the United States had a bizarrely fragmented financial system due to a series of political restrictions on financial institutions. Commercial banks were prohibited from operating branches in more than one state, so that New York, California, Illinois, and every other state had their own separate banking sectors with their own set of regulations. Commercial banks and investment banks were strictly separate, so that making a loan and underwriting a bond had to be done through different institutions that were in implicit competition. Moreover, commercial banks were banned from owning shares in companies, which severely limited their influence (Neuman, Davis, and Mizruchi 2008). The contrast between Spain and Italy after World War II also demonstrates how domestic politics can shape the format of finance and banking. In Italy during the early 1930s, commercial and investment banking were legally separated, as in the United States, thereby pushing Italian firms toward selffinancing and their characteristic form of ownership pyramids. By contrast, the Spanish state facilitated ownership and lending ties between big banks and industrial corporations, thus encouraging a kind of Mediterranean finance capitalism (Aguilera 2003). The link between domestic politics and finance is evident among the broader set of OECD countries, where neoliberal countries have systematically larger and more dispersed finance than social democracies. Mark Roe (2003) argues that there is a causal relation between corporate ownership structures and the degree of social democracy. Powerful organized labor corresponds to strong owners; weak labor corresponds to dispersed owners and large financial markets. Thus, ownership is dispersed in the UK

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and the United States, where labor is relatively weak, while it is relatively concentrated in Germany and the Nordic countries, where labor is strong. His interpretation of this regularity is that concentrated ownership acts as a countervailing force for the political struggles within firms among managers, owners, and labor. Large shareholders have the incentives and the ability to govern the firm directly, and their position of power in the governance system strengthens their hand with respect to labor. Moreover, their incentives to sell (i.e., to disperse ownership) are dampened by the fact that outside investors would undervalue a firm with powerful (and legally protected) stakeholders. The organization of finance and the organization of labor are clearly linked. But capital and labor are implicated in a larger matrix of interdependent institutions at a national level, and thus understanding the politics of finance requires a more comprehensive view of the economy and the polity. Political scientists have taken a comparative approach to this question by seeking to organize national economic systems into moreor-less coherent “varieties of capitalism.” The best-known typology distinguishes two main forms among advanced economies, each exemplified by a prototype: liberal market economies (LMEs), represented by the United States, and coordinated market economies (CMEs), represented by Germany (Hall and Soskice 2001). Hall and Soskice’s approach is distinguished by several factors. The first is that firms and their strategies are the leading elements in the economy, and different varieties of capitalism facilitate different kinds of firms and strategies. That is, configurations at the national level imply what are the most fruitful firm-level strategies. In LMEs, firms interact primarily via arms’ length market-based relations, while in CMEs networks of firms have more collaborative and nonmarket-based relations. A second distinguishing feature of this approach is that firms engage with five institutional spheres, each of which shapes their feasible strategies and therefore the kinds of industries that thrive. The spheres include: (1) industrial relations (bargaining over wages and working conditions); (2) vocational training and education (recruiting a workforce with suitable skills); (3) corporate governance (how firms relate to suppliers of finance); (4) interfirm relations; and (5) their own employees. These five spheres line up into more or less coherent configurations of complementary elements that encourage firms to specialize in particular kinds of strategies. CMEs have characteristically stronger employment protections, while LMEs have more developed financial markets. Thus, in CMEs, firms and workers should be more willing to invest in specialized assets, while in LMEs they should prefer investing in switchable assets (Hall and Soskice 2001: 17). This is reflected in the characteristic leading industries in an economy: in the United States, information technology, medical engineering, and biotechnology (typically funded via the stock market) are among the leading industries, while in Germany civil engineering, nuclear engineering, and machinery (which require a highly skilled and specialized workforce) are among the leading industries. Although the idea of a dichotomy (or even a continuum) of formats of capitalism is conceptually pleasing, it fits uneasily with the data, even among OECD countries. Hall and Soskice (2001) classify six countries as LMEs (the United States, UK, Australia, New Zealand, Canada, and Ireland), ten as CMEs (Germany, Japan, Switzerland, the

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Netherlands, Belgium, Sweden, Denmark, Norway, Finland, and Austria), and six as ambiguous (France, Italy, Spain, Portugal, Turkey, and Greece). Such typologies often seem to reflect the two or three exemplars chosen as the “poles” or ideal types—for example, the United States and Germany (Hall and Soskice 2001), or these two and Japan (Zysman 1983). Yet even among the OECD countries, two or three types seem inadequate to capture the diversity of institutional configurations (cf. Aguilera and Jackson 2010). One approach to this problem is to work inductively from the data rather than beginning with the ideal types. Bruno Amable (2003) accomplishes just this, with a series of cluster analyses that distinguish no fewer than five varieties of capitalism among 21 OECD countries. His analysis begins with five “fundamental institutional areas” that implicate firms: product markets; labor markets; financial intermediation; social protection and welfare provision; and education. Again, these institutional areas display strong complementarities—what Amable describes as “specific architectures of complementary institutions” (20). For instance, strong employment protections and social welfare guarantees encourage workers to invest in training that might be specific to a particular employer; vigorous product market competition, on the other hand, encourages flexible (less-protected) employment practices, which discourage worker investment in specific skills and promotes competition within the education sector. Using detailed cross-national data on each of the five domains for the late 1990s, Amable finds slightly different clusterings across each of the five domains (e.g., six clusters for product market competition; four clusters for employment protection). These clusters are in turn aggregated into five main models of capitalism: market-based economies (the AngloSaxon model); social democratic economies (the Scandinavian model); Asian capitalism (including Korea and Japan); Continental European capitalism; and south European (or Mediterranean) capitalism. Each model underlies a distinct “social system of innovation and production” that provides an environment that is conducive to some kinds of economic activities and less attractive for others. Market-based economies specialize in activities where fast adaptation and good industry–university links matter: biotechnologies, computer science, and electronics. Social-democratic countries have a comparative advantage in health-related activities as well as industries linked to their natural resources (paper and printing). Countries on the Mediterranean model specialize in light industries and low-tech activities. Asian-capitalism countries have a comparative advantage in computers, electronics, and machines. The only model which does not seem to exhibit a strong pattern of specialization is the Continental European model. (Amable 2003: 22)

Politics enters this account at the level of institutional design: “Rather than optimal solutions to a given problem, institutions represent a compromise resulting from the social conflict originating in the heterogeneity of interests among agents. What we consider to be different economic ‘models’ are therefore based on specific social compromises over institutions. The question of institutional change is basically a question of political economy” (Amable 2003: 10). This provides a morphology. How, then, might they change— that is, what could provide a theory of evolution for models of capitalism?

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The prospects for change depend on a country’s political institutions. The feasible set of governance formats is constrained by how political decisions are made: who are the players, what are their interests, and what are the specific mechanisms of preference aggregation (Gourevitch 2003). Gourevitch and Shinn (2005) provide a systematic model for linking politics to corporate governance systems. In contemporary economies, firms create wealth, and corporate governance shapes how the spoils are divided among different players (owners, managers, workers). Thus, claims on profits within the firm depend on politics outside the firm; participants in the firm will therefore seek allies in the polity to promote the institutions of corporate governance they prefer, such as greater or lesser protection of minority shareholder rights, which in turn pushes toward lesser or greater ownership concentration. The three main players each have characteristic interests that influence their prospects for forming political coalitions. Workers seek good wages, job stability in the face of layoffs, even at the expense of profitability, and protection of their pension claims on the firm . . . Managers seek income, job security, and managerial autonomy. They want high payments of various kinds, from salary to options, and the greatest autonomy in directing the resources of the firm—which also gives them the greatest leeway to shirk . . . Owners prefer to minimize all the forms of agency costs paid to managers and workers, fearing that each of these groups is able to divert resources from profits, requiring the firm to pay above market prices to them. (Gourevitch and Shinn 2005: 59)

Gourevitch and Shinn propose three possible coalitional struggles (owners and managers vs. workers; workers and managers vs. owners; owners and workers vs. managers), each of which has two possible outcomes. When owners and managers win over workers, it is an investor coalition and promotes ownership diffusion; when workers win, it is a labor coalition and promotes blockholding. When managers and workers win over owners, it is a corporate compromise and accords with blockholding; when owners win, it is an oligarchy and also promotes blockholding. Finally, when owners and workers prevail over managers, it is a transparency coalition, while when managers win it is a managerism coalition; in either case, shareholding is likely to be diffuse. What determines which coalition wins? Gourevitch (2003) notes that above and beyond distinctions such as common law vs. civil law, national political systems within democracies can systematically shape the prospects for changes in corporate governance and systems of production. Consensus systems, as among many of the parliamentary systems of Europe, commonly require the creation of political coalitions to get things done, and thus policy swings are relatively minimal. But in majoritarian systems such as the UK and the United States, small shifts in votes can lead to large swings in policy as a new dominant party sweeps out the policies of the old, creating an uncertain climate for investment in firm-specific assets. Once again, we find a systematic difference between Anglo-Saxon countries (which commonly have majoritarian systems) and the coordinated market economies, which in turn corresponds to levels of ownership concentration or dispersion.

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The clean distinction between managers, owners, and workers, each with clear political interests, can become quite muddled through changes in the structure of the economy and the organization of finance. Systems of production create different political interests and give different prospects for financial control, thereby creating a feedback loop to domestic politics. This suggests that changes in the organization of production— for example, the shift from an industrial to a postindustrial economy—can lead to shifts in perceived political interests and new forms of political coalitions, which can in turn change the organization of finance. In the United States, for instance, the wave of finance-driven hostile takeovers of manufacturing conglomerates in the 1980s and the outsourcing movement of the 1990s led to the disaggregation of production and the end of traditional forms of job security (Davis 2009). This was accompanied by a shift from company-sponsored retirement pensions to individual, portable pension plans (typically “401(k)” plans, named for the section of the tax code that enabled them). Because of the rise of individual pension plans and the increased accessibility of mutual funds for college savings, most American households had invested in the stock market by the turn of the twenty-first century. Although the amounts involved were often small—the median shareholding household had under $30,000 invested in the market, hardly enough to retire on—the psychological impact of stock ownership can be substantial. Due in part to targeted recruiting efforts by the administration of George W. Bush, shareholders came to identify with the Republican party at astonishing rates during the first decade of the twenty-first century, increasing from 30 percent to 40 percent between 2000 and 2004 (compared with a flat 18 percent among non-shareholders). This in turn helped assure the (re)election of Bush in 2004, who spent the first years of his second term pressing for the privatization of the national pension system in the United States in order to create a “nation of shareholders” who would (presumably) vote Republican (Davis and Cotton 2007). By contrast, in nations with more generous state-sponsored pension systems such as traditional social democracies, private pensions are of relatively little consequence and provide little push toward market-oriented voting (Jackson and Vitols 2001). Similarly, state-funded higher education lessens the need for private savings through vehicles such as mutual funds, again muting the connection between household decision-making and financial markets. In short, the organization of finance is shaped in part by whether individuals identify politically as workers, managers, or owners, which in turn depends on the structure of the economy, which is shaped by the organization of finance. Endogenous forces can lead to changed relations between politics and finance.

Change and crisis in finance By the turn of the millennium, it was clear that financial markets were becoming ever more central to global political economy. The collapse of the Soviet Union and the disintegration of Yugoslavia set in motion an array of disparate new approaches to capitalism

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in Eurasia, often prominently featuring financial markets. Mass privatization of former state-owned enterprises created thousands of new public corporations. By 2000, Azerbaijan had two publicly traded corporations, Bulgaria had 500, and Romania had over 5,500 (behind only the United States and India). While the economic trajectories of former communist countries varied widely, most included stock markets as a means to transfer state ownership, with varying levels of success (cf. Kogut and Spicer 2002). Outside Eastern Europe, dozens of other countries opened their first stock exchange during the 1980s and 1990s, doubling the number of countries in the world with a domestic stock market. New exchanges opened in Iceland (1985), Barbados (1987), Guatemala (1989), Mongolia (1992), Latvia (1993), Lebanon (1996), Tanzania (1998), Papua New Guinea (2000), and scores of other countries now dubbed “emerging markets.” The neoliberal dream of Western economists appeared to be coming true, as new outlets for portfolio investment spread across nearly every continent. Finance became increasingly unconstrained by state control as the effortless flow of funds through electronic means enabled a new placelessness. This challenged the coherence of the varieties of capitalism we have reviewed, which tend to assume that states preside over porous but meaningfully bounded economies. Corporations had long been somewhat strategic in their financing, but now nationality itself had become more a matter of choice than circumstance. The opportunity to list shares in New York or London or Hong Kong attracted businesses from around the world. Hundreds of nonUS companies created secondary share listings in the United States, and by the end of the 1990s there were more foreign companies traded on American markets than there were German companies traded on the Deutsche Börse. As finance increasingly detached from place, it became possible for companies to opt out of their domestic financial system entirely. Dozens of companies domiciled in Israel bypassed the Tel Aviv stock market and went straight to NASDAQ; many were funded by American venture capitalists, advised by American law firms, and incorporated in the United States. On the stock market, only their mailing address distinguished these firms from typical Silicon Valley startups (Davis and Marquis 2005). This development fitted uneasily with the premise of varieties of capitalism: If whole institutional sectors can be bypassed, then what becomes of the complementarities assumed by this approach? In retrospect, it is clear that the late 1990s represented the high-water mark of the neoliberal consensus on the role of finance in economic growth. Enthusiasts seemed to believe that installing a financial market was the economic equivalent of providing vaccinations, clean water, and universal literacy—an unambiguously positive step on the path to economic growth and development in the contemporary global economy. True believers were rapturous about the benefits of financial markets. Treasury Secretary Larry Summers stated in 1997 that “Financial markets don’t just oil the wheels of economic growth—they are the wheels” (Murray 1997). A handful of economic studies provided evidence consistent with the claim that vibrant financial markets encouraged economic growth (e.g., Levine and Zervos 1998), and policymakers and the punditry popularized this idea. Thomas Friedman (1999) described the “golden straitjacket” that

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embraced emerging economies who availed themselves of the benefits of financial markets. The path to economic growth was clear but narrow and required acceding to the demands of faceless global investors. This was, of course, a rather different model of development than the familiar developmental state (Evans 1995). What had changed? A Whiggish account would run like this: reductions in the transaction costs of market-based finance relative to other forms of financing created an irresistible attraction for both issuers and investors. Entrepreneurs were attracted by the opportunity to get rich quick via a public stock offering; global investors were attracted by the high potential growth rates in emerging markets. Old models of state-directed investment—the ones that guided developmental states such as Japan and Korea—would be replaced by an entrepreneurial model in which Western investors would fund the entrepreneurial visions of local businesses around the world. States would no longer be in the business of “picking winners”: markets would do that. Instead, the proper role of the state in finance was to create a legal infrastructure for financial markets and the protection of shareholder rights (drawing on the well-documented architecture of the American system), reduce restrictions on the flow of finance, and watch the economy grow (Davis 2010). The new model was not without trade-offs. Technological changes expanding market-based finance created clear winners and losers, both within the polity and in society at large. Within the United States, the manager/worker coalition was replaced by a manager/owner coalition, resulting in a corresponding loss in power by labor. The precipitating event was the takeover wave of the 1980s, in which one-third of the largest US industrial corporations were taken over and often split up in the name of “creating shareholder value” (Davis, Diekmann, and Tinsley 1994). Corporate managers were increasingly compensated according to their ability to increase share price, thus aligning their interests with those of their shareholders. By the 1990s there was consensus among those who owned and those who managed that corporations existed to create shareholder value, not to provide steady employment, and a wave of downsizing shrank the largest US firms down to their core, creating a spike in income inequality (Davis and Cobb 2010). Even within banking, the hyper-expansion of financial markets created both winners and losers. The increasing availability to businesses of market-based debt meant that commercial banks in the United States lost much of the primary market for their lending; on the other side of the balance sheet, savers found market-based vehicles such as mutual funds offered a more remunerative alternative to traditional savings accounts, leaving banks increasingly irrelevant (Davis and Mizruchi 1999). A long-delayed wave of consolidation in the industry during the 1990s and 2000s created a small handful of national giants (JP Morgan Chase, Bank of America, Citigroup) but left most major cities without a locally based bank. Investment banks, on the other hand, grew increasingly large and powerful, as they were the primary conduits to market-based finance. Both in terms of compensation and political influence, investment bankers became a potent force in American society, as witnessed by the market-friendly staffing of the Clinton Administration in the 1990s.

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Due to the reorganization of finance, new categories of players emerged and gained political influence. Mortgage finance, for instance, had traditionally been a simple affair in the United States: depositors put their savings in local banks, and the banks made mortgage loans to local borrowers. Widespread securitization of mortgage loans fundamentally reshaped the value chain for housing finance, creating new industries of freestanding mortgage brokers (who replaced bank loan officers), loan originators such as Countrywide and New Century (who made the initial loans and then sold them to investment banks for packaging into mortgage-backed securities), and loan servicers (who took in payments from home buyers and distributed them to investors). And lightly regulated hedge funds and private equity firms grew into a “shadow banking system” outside the traditional categories of finance. Even among advanced economies with long-standing traditions of corporate governance, the growing scope and influence of financial markets challenged the internal coherence of the varieties of capitalism in which market-based finance had featured less prominently. In Germany, the prototypical coordinated market economy, public corporations in the 1990s began proclaiming their newfound commitment to “shareholder value,” in part to enhance their allure to foreign investors (Fiss and Zajac 2004). Meanwhile, Japanese companies began to abandon the traditional model of lifetime employment security, encouraged in part by the influence of foreign investors (Ahmadjian and Robinson 2001). It appeared that emerging markets were not alone in experiencing the effects of the golden straitjacket. Some argued that mobile finance threatened the power of the nation-state. When the bargaining power of states is weakened by increasingly mobile capital, it has a direct impact on the bargaining power of labor (Arrighi and Silver 1999). Martin Wolf (2004: 243–4) stated, “The interests of a transnational company are not the same as those of the country from which it originates or of the workers it has historically employed. It has become, to coin a phrase, a ‘rootless cosmopolitan.’ ” The traditional national coalitions between workers and firms (or managers) are undermined when corporations and investors have little fixed attachment to place. Thus, states may find themselves increasingly attentive to the demands of investors, particularly when they are backed by a seemingly coherent theory of economic growth. This dynamic played out in countries around the world during the 1990s, from the Phillippines to Bill Clinton’s America, where investment banking veterans such as Robert Rubin provided a Greek chorus for the markets. But the economic crisis that began in 2008 created an inflection point for global finance. If the decade that ended in 2000 represented the high-water mark for financebased neoliberalism, then the decade that ended in 2010 demonstrated the dangers of tying the well-being of society too closely to financial markets. What began with a few thousand American homeowners falling behind in their mortgage payments ended up creating a global crisis that brought the world to the precipice of a second Great Depression. In September 2008, the United States saw the biggest bank failure and business bankruptcy in its history (Washington Mutual and Lehman Brothers), the seizure of the two institutions behind half of its mortgage market (Fannie Mae and Freddie Mac), the near-implosion of the world’s largest insurance company (AIG), and the disappearance

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of two of its four biggest independent investment banks (Lehman and Merrill Lynch)— all within three weeks. Only massive and unprecedented intervention by the Federal government prevented the world’s financial system from seizing up. As housing prices declined, homeowners stopped paying their mortgages, and many global investors discovered that the mortgage-backed bonds peddled to them by Wall Street were nearly worthless. Meanwhile, exporters who relied on debt-loving Americans to buy their wares found demand drying up overnight as consumers rediscovered the virtues of thrift. A contagion of financial crises spread to unlikely places—Iceland, Greece, Ireland, Spain—calling into question the integrity of European financial union. Moreover, at the beginning of 2010, the S&P 500 market index stood one-quarter lower than it had a decade before, and the United States had half as many public corporations as it did in 1997. Even in its home and native land, finance-centered capitalism appeared increasingly untenable. Meanwhile, China—which defies all of the varieties of capitalism we have reviewed—surpassed Japan to become the world’s second-largest economy. Ten years hence, we may be seeking to explain a rather different league table of global economic success.

Conclusion The study of finance and politics has become a vibrant and highly interdisciplinary domain over the past generation. Important contributions have come from many scholarly quarters. We have reviewed financial economists writing about the law (La Porta et al. 1998); legal scholars writing about political dynamics (Roe 2003); political scientists writing about corporate management and strategy (Hall and Soskice 2001); and management scholars writing about finance (Davis 2009). Every few years a previously overlooked construct becomes a central topic for scholarship (e.g., bank vs. marketbased finance; civil law vs. common law; majoritarian vs. consensus political systems). New data collection efforts seek to compile cross-national time-series information on topics from the average level of ownership concentration in public companies to the death rates of European colonists. Yet more and better data do not seem to resolve the debates within the field. Indeed, new data often serve to undermine existing interpretations shortly after they are established. Legal family seems to correlate highly with financial market development and corporate ownership, yet both show substantial change over time even within prototypes (the United States, France, and Germany). Comparative information suggests that simple dichotomies (e.g., market-based vs. bank-based financial systems) can obscure more than they reveal, and expanding the sample beyond one or two dozen countries leads to the realization that, for instance, Latin America does not fit readily into the category of “Mediterranean capitalism,” and Africa has a diversity of economic formats from north to south. Moreover, models seem to rise and fall over time in ways that seem inconsistent with theory. China’s rapid economic expansion is a puzzle from almost any perspective we have examined.

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Even the collection of lavish time-series data has failed to plausibly establish causality. Many core aspects of countries are relatively fixed. Nations rarely change their legal family, their language, the point in history when they industrialized, or their dominant religion, and changes in political systems are only slightly less infrequent. (There are, of course, “exogenous” shocks such as the collapse of the Soviet Union that occasionally create rapid shifts in political systems, but these were not designed with an experimental handbook.) In addition, many of the elements hypothesized to shape finance and politics frequently occur together—common law, a majoritarian political system, Protestantism, and the English language are broadly shared among neoliberal economies, for instance, so distinguishing the effective ingredient is difficult. One conclusion from our review is that typologies of capitalism should be held lightly. The most empirically grounded typology, from Amable (2003), distinguishes five models of capitalism among 21 OECD countries, but notes that the Netherlands and Switzerland may form yet a sixth distinct type. The addition of other areas of the world— Latin America, Africa, the Middle East, China, Southeast Asia—suggests that the final typology may have at least a dozen models. And even within the identified types, a determined skeptic would find reason to quibble. Consider the differences between close neighbors and model-mates Denmark and Sweden, or Korea and Japan, or Chile and Argentina. Even the United States and Canada are quite different on several relevant dimensions. In contrast to the United States, Canada has four major political parties, state-funded higher education, universal healthcare, low income inequality, and a financial sector that has seen only two bank failures since the 1920s—and none during the Great Depression or the recent financial crisis (which helps explain its 2008 ranking by the World Economic Forum as the best banking system in the world). Of course, to claim that every country is utterly unique would be hostile to the enterprise of social science—but the evidence suggests that typologies of capitalism should be considered provisional at best. A second conclusion, borne out by the financial crisis, is that states are still central actors in the global economy. Capital may be internationally mobile, but in a crisis it is ultimately left to the state to sort things out, bail out the players deemed to be indispensable, and create reforms sufficient to coax participants back in to the market. Ultimately, the state is inextricable from the economy, and finance and politics are inseparable (Block 1994). A third conclusion is that the microlevel dynamics of finance and politics have received very little attention relative to cross-national comparisons. Tectonic shifts in the organization of production have been matched by equally massive changes in the organization of finance and property. Securitization has done for homes, cars, and college educations what the dispersion of shareholding did for the large corporation, “splitting the atom of property” (in Berle and Means’ phrase) and changing the meaning of ownership and control. The mortgage crisis in the United States revealed just how Byzantine finance could be. Mortgages were pooled and sliced into bonds (mortgage-backed securities), which were in turn pooled and turned into second-generation bonds (collateralized debt obligations), which were sold to investors around the world. Efforts to foreclose on

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delinquent homeowners were hampered by the fact that it was in many cases impossible to prove who owned what. And efforts at intervention at the policy level were hampered by the fact that the interests of homeowners, borrowers, financial institutions, and bondholders formed no clear coherent coalition: for instance, while delinquent homeowners and the bank that nominally owned the mortgage might have an interest in reducing the principal owed, this might come at the expense of the bondholder or neighboring homeowners. Property ownership is a fundamental source of political interest, yet we have surprisingly little research on how participation in finance—as buyer or seller—affects microlevel politics (e.g., party identification or political activism). Finally, the evolution of the technologies of finance suggests that finance can be a flywheel of historical change. The idea of technology as an engine of economic change is commonplace, but the vast expansion of finance over the past generation—enabled by advanced information and communication technologies (ICTs)—indicates that finance has its own relatively autonomous developmental path. The sociological study of finance is still at a relatively early stage, but it is hard to imagine a more suitable topic for ongoing inquiry.

References Aguilera, R. V. (2003). “Are Italy and Spain Mediterranean Sisters? A Comparison of Corporate Governance Systems,” in M. Federowicz and R. V. Aguilera (eds.), Corporate Governance in a Changing Economic and Political Environment: Trajectories of Institutional Change. New York: Palgrave MacMillan, 23–70. ——– and Jackson, G. (2010). “Comparative and International Corporate Governance.” Annals of the Academy of Management, 4: 485–556. Ahmadjian, C. L. and Robinson, P. (2001). “Safety in Numbers: Downsizing and the Deinstitutionalization of Permanent Employment in Japan.” Administrative Science Quarterly, 46: 622–54. Amable, B. (2003). The Diversity of Modern Capitalism. New York: Oxford University Press. Arrighi, G. and Silver, B. J. (1999). “Hegemonic Transitions: Past and Present.” Political Power and Social Theory, 13: 239–75. Berle, A. A. and Means, G. C. (1932). The Modern Corporation and Private Property. New York: Commerce Clearing House. Block, F. (1994). “The Roles of the State in the Economy,” in N. J. Smelser and R. Swedberg (eds.), Handbook of Economic Sociology. Princeton, NJ: Princeton University Press. Brandeis, L. D. (1914). Other People’s Money: And How the Bankers Use It. New York: Frederick A. Stokes Company. Carruthers, B. G. (1996). City of Capital: Politics and Markets in the English Financial Revolution. Princeton, NJ: Princeton University Press. Chandler, A. D. (1977). The Visible Hand: The Managerial Revolution in American Business. Cambridge, MA: Belknap Press. Clayton, M. J., Jorgenson, B. N., and Kavajecz, K. A. (2006). “On the Presence and MarketStructure of Exchanges Around the World.” Journal of Financial Markets, 9: 27–48. Davis, G. F. (2005). “New Directions in Corporate Governance.” Annual Review of Sociology, 31: 143–62.

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——– (2008). “A New Finance Capitalism? Mutual Funds and Ownership Re-Concentration in the United States.” European Management Review, 5: 11–21. ——– (2009). Managed by the Markets: How Finance Reshaped America. New York: Oxford University Press. ——– (2010). “Is Shareholder Capitalism a Defunct Model for Financing Development?” Review of Market Integration, 2: 317–31. ——– and Cobb, J. A. (2010). “Corporations and Economic Inequality Around the World: The Paradox of Hierarchy.” Research in Organizational Behavior, 30: 35–53. ——– and Cotton, N. C. (2007). “Political Consequences of Financial Market Expansion: Does Buying a Mutual Fund Turn You Republican?” Presented at the American Sociological Association Annual Meetings, New York. ——– and Marquis, C. G. (2005). “The Globalization of Stock Markets and Convergence in Corporate Governance,” in V. Nee and R. Swedberg (eds.), The Economic Sociology of Capitalism. Princeton, NJ: Princeton University Press, 352–90. ——– and Mizruchi, M. S. (1999). “The Money Center Cannot Hold: Commercial Banks in the U.S. System of Corporate Governance.” Administrative Science Quarterly, 44/2: 215–39. ——–. Diekmann, K. A., and Tinsley, C. H. (1994). “The Decline and Fall of the Conglomerate Firm in the 1980s: The Deinstitutionalization of an Organizational Form.” American Sociological Review, 59: 547–70. Evans, P. (1995). Embedded Autonomy: States and Industrial Transformation. Princeton, NJ: Princeton University Press. Fiss, P. C. and Zajac, E. J. (2004). “The Diffusion of Ideas over Contested Terrain: The (Non) adoption of a Shareholder Value Orientation among German Firms.” Administrative Science Quarterly, 49: 501–34. Friedman, T. L. (1999). The Lexus and the Olive Tree: Understanding Globalization. New York: Farrar, Strauss, Giroux. Gourevitch, P. A. (2003). “The Politics of Corporate Governance Regulation.” Yale Law Journal, 112: 1829–80. ——– and Shinn, J. (2005). Political Power and Corporate Control: The New Global Politics of Corporate Governance. Princeton, NJ: Princeton University Press. Hall, P. A. and Soskice, D. W. (2001). Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford: Oxford University Press. Jackson, G. and Vitols, S. (2001). “Between Financial Commitment, Market Liquidity and Corporate Governance: Occupational Pensions in Britain, Germany, Japan and the USA,” in B. Ebbinghaus and P. Manow (eds.), Comparing Welfare Capitalism: Social Policy and Political Economy in Europe, Japan and the USA. London: Routledge. Kogut, B. and Spicer, A. (2002). “Capital Market Development and Mass Privatization are Logical Contradictions: Lessons from Russia and the Czech Republic.” Industrial and Corporate Change, 11: 1–37. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., and Vishny, R. W. (1997). “Legal Determinants of External Finance.” Journal of Finance, 52: 1131–50. ——– (1998). “Law and Finance.” Journal of Political Economy, 106: 1113–55. ——– (2000). “Investor Protection and Corporate Governance.” Journal of Financial Economics, 58: 3–27. Lenin, V. I. ([1916] 1939). Imperialism: The Highest Stage of Capitalism. New York: International Publishers. Levine, R. and Zervos, S. (1998). “Stock Markets, Banks, and Economic Growth.” American Economic Review, 88: 537–54.

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Murray, A. (1997). “Super Model: Asia’s Financial Foibles Make American Way Look Like a Winner—IMF Comes Round to View that Short-Term Focus has its Virtues After All.” The Wall Street Journal, 8 December: A1. Neuman, E. J., Davis, G. F., and Mizruchi, M. S. (2008). “Industry Consolidation and Network Evolution in U.S. Global Banking, 1986–2004.” Advances in Strategic Management, 25: 213–48. Rajan, R. G. and Zingales, L. (2004). Saving Capitalism from the Capitalists: Unleashing the Power of Financial Markets to Create Wealth and Spread Opportunity. Princeton, NJ: Princeton University Press. Roe, M. J. (1994). Strong Managers, Weak Owners: The Political Roots of American Corporate Finance. Princeton, NJ: Princeton University Press. ——– (2003). Political Determinants of Corporate Governance: Political Context, Corporate Impact. New York: Oxford University Press. Weber, K., Davis, G. F., and Lounsbury, M. (2009). “Policy as Myth and Ceremony? The Global Spread of Stock Exchanges, 1980–2005.” Academy of Management Journal, 52: 1319–47. Wolf, M. (2004). Why Globalization Works. New Haven: Yale University Press. Zysman, J. (1983). Governments, Markets, and Growth: Financial Systems and the Politics of Industrial Change. Ithaca, NY: Cornell University Press.

chapter 3

fi na nce a n d i nstitu tiona l i n v e stor s j iwook j ung and f rank d obbin

Introduction Institutional investors have come to play a central role in financial markets since the early 1970s. They controlled about three out of ten shares of Fortune 500 companies in 1970. Today they control seven out of ten. The aging of the baby boom generation, coupled with new fiduciary requirements for defined benefit pension plans, contributed to this change. As the retirement savings of the baby boom generation piled up, the regulatory changes led employers to favor individual retirement accounts managed by Fidelity, Vanguard, and the like. In the process American workers and pensioners came to own the lion’s share of stock in most large companies, with institutional investors representing their interests. Some who anticipated the democratization of corporate ownership through pension investments, in the United States and elsewhere, described a gradual road to socialism (Stephens 1979). From the 1980s, stakeholder theory gained ground by suggesting that the firm was beholden not only to shareholders, but to other stakeholder groups, from customers to employees to the community (Donaldson and Preston 1995; Freeman 1984). As ownership became more widespread, firms might have been expected to embrace stakeholder theory, for workers and pensioners were becoming majority shareholders. Instead, institutional investors and then corporate leaders embraced agency theory and the shareholder value approach. They rewrote the title of Milton Friedman’s 1970 article, “The Social Responsibility of Business is to Increase Its Profits,” replacing the last two words with “Share Value.” Agency theory offered a litany of innovations designed to ensure that executives pursued the interests of shareholders, rather than feathering their own nests. The theory reduced the common interests of diverse shareholders to a single metric, share value. Institutional investors promoted the theory with a vengeance, encouraging firms through shareholder proposals and private bidding to put its prescriptions into place.

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We review evidence showing that firms responded to the entreaties of institutional investors, putting most of the innovations they lobbied for into place. We also review evidence concerning the effects of these innovations. Most have not proven to improve share value, but quite a few have had adverse consequences for worker-owners who hold stock. Executive compensation through stock options has transferred wealth from worker-owners who hold stock to executives. Dediversification has been accomplished through corporate restructurings, typically accompanied by massive layoffs. Debt financing has made firms vulnerable when the economy slumps, and more likely to declare bankruptcy, close their doors, and bail out on their pension obligations. The mandate to increase share price through cost-cutting has led firms to downsize, eliminating jobs, and to curtail contributions to defined-benefit pension plans, leaving those plans underfunded and leaving workers or taxpayers to pay the price. Institutional investors thus promoted a new model of management that has been good for the financial elite of executives, investment bankers, hedge fund managers, private equity chiefs, and institutional investors, but not so good for the workers and pensioners who are now the majority shareholders. The distribution of national income is one indicator of the consequences of these changes. By 2007, the richest 1 percent of Americans took home 23.5 percent of national income, up from 9 percent in 1970 (Piketty and Saez 2003, 2009). Take out the star athletes and Hollywood celebrities, who are not part of the financial elite, and the numbers change little. We chart the role of institutional investors in promoting changes in corporate management under the banner of shareholder value, and review evidence that these changes did little to promote share value and that they resulted in several disadvantages for the American worker-owner. Some of the changes have been described as inevitable given growing global competition, but elites in other developed countries responded quite differently to the challenge of globalization. German firms, for instance, emphasized products that required high skill levels and could not readily be produced effectively elsewhere, avoiding massive layoffs, sustaining relatively high median wages, and forestalling the concentration of income (Thelen 2003).

A word about evidence In addition to reviewing evidence from a number of studies, we present evidence from a representative sample of 783 major American firms to track the move toward agency theory prescriptions between 1980 and 2005. We also review evidence about the effects of different innovations adopted under the flag of shareholder value. We chose a representative group of industries from Fortune lists of industry leaders, selecting equal numbers of firms from aerospace, apparel, building materials, chemicals, communications, computers, electrical machinery, entertainment, food, health care, machinery, metals, oil, paper, pharmaceuticals, publishing, retail, textiles, transportation, transportation equipment, utilities, and wholesale. We sampled firms from Fortune lists in odd years between 1965 and 2005 so as to achieve a sample that represents both rising and declining

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firms. The core data come from Standard and Poor’s Compustat data files. A number of variables, as noted, come from other sources.

The rise of institutional investors The rise of both institutional investors and agency theory can be traced to the economic stagnation that began in the late 1960s and continued through the 1970s. Stagnation helped to convince Congress to expand the regulation of pensions in 1974, for company pension funds suffered under high inflation and low growth. The Pension Reform Act contributed to the popularity of individual retirement accounts among corporations by making defined-benefit pension plans more expensive to run, and this shifted pension contributions into the hands of mutual fund managers. Meanwhile, America was looking for a scapegoat for the economic malaise of the 1970s, and a way out of the economic quagmire. Agency theory came along toward the end of the decade to offer up the selfish corporate executive as the scapegoat, and to offer a tidy set of prescriptions for reorienting the firm to making money. Newly influential institutional investors, who now controlled much of the money that flowed into capital markets, became enamored of agency theory and pushed firms to follow its dictates about executive compensation, industrial focus, debt financing, and costcutting to improve profits and share value. Agency theory had conjoined the interests of institutional investors and corporate executives, for under the new compensation schemes based on stock options, executives saw windfalls each year in which share prices grew, but shared none of the downside risk with investors. The bonuses of the institutional fund managers were likewise tied to growth in share value, and, like executives, fund managers did not share in the downside risk. By promoting stock options, in particular, institutional investors ensured that the interests of corporate executives would coincide with their own interests, if not always with those of shareholders, who held most of the downside risk.

The Pension Reform Act of 1974 and the growth of mutual funds The expanding power of institutional investors in equity markets was in large measure an unintended consequence of Washington’s efforts to insure the private pension system that had arisen alongside the public system during the twentieth century (Dobbin 1992). Benefits from private pensions combined with government-sponsored Social Security provided comfortable retirement incomes for employees in high-paying, unionized sectors. The passage of the Employee Retirement Income Security Act of 1974 marked the high point of this uniquely American system. Designed to guarantee that plans were fully funded and could pay projected expenses, the act unintentionally led to the growth of defined contribution pension plans, such as the 401(k) (Hacker 2006). The new

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80.0%

Percent of shares held by institutions

70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0%

Investment Advisors Insurance

Investment Companies Public Pensions

02

04 20

20

00 20

98

96

19

94

19

19

92 19

90 19

88

86

19

84

19

19

82 19

19

80

0.0%

Banks Others

figure 3.1 Institutional Investor Holdings in Large US Firms Source: Authors’ sample of 783 large US corporations.

regulations increased the cost of defined benefit plans, and in the context of low growth, defined contribution plans now seemed a better bet for firms hoping to transfer the risk of poor investment returns to the individual. The shift to defined contribution plans was rapid. In 1981, about 60 percent of workers with private pensions depended exclusively on a defined benefit plan, but in 2003, this was down to only 10 percent. Meanwhile the percentage of workers who depended exclusively on a defined contribution plan increased from 20 to 60 percent (Buessing and Soto 2006). In Figure 3.1 we show the growth in holdings by institutional investors between 1980 and 2005, based on the 783 leading American firms in our sample. In 1980, institutional investors controlled three of ten shares in the average company. Banks held the biggest proportion of shares, followed by investment advisors (such as Goldman Sachs) and insurance companies. By 2005, bank holdings had declined as a proportion of all shareholding, and investment advisors and investment companies (such as Fidelity) held the largest aggregate positions in the stock market. Overall, institutional investors controlled 70 percent of shares in the average company by 2005, with investment advisors and investment companies, which manage retirement and personal accounts, controlling half of shares in the typical firm.

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The rise of agency theory The stagflation of the 1970s stimulated business to search for a diagnosis and remedy. Agency theorists offered both. Jensen and Meckling’s (1976) seminal article suggested that the interests of principals (shareholders) and their agents (executives) were out of sync. Executives acted to serve their own interests, building large diversified firms to minimize the risk of failure and to raise their own salaries, rather than focused firms that would maximize profits, and turning away from efforts by boards and investors to monitor them (Fama 1980; Fama and Jensen 1983, 1985; Jensen and Meckling 1976). To bring corporate behavior into line with shareholder interests, agency theorists proposed changes to compensation: tying executive fortunes to investor interests through stock options, in place of salary, and executive stockholding. They proposed changes to corporate strategy: dediversification to make use of the management team’s industry expertise, and debt financing of expansion to discipline executives inclined to use profits for acquisitions of questionable value. They proposed more generally that firms cut costs to increase profit margins, and executives pursued a number of strategies for doing just that, including reducing payroll expenditures. They proposed governance and monitoring reforms as well that we do not take up here, including more independent boards and more transparency to facilitate external monitoring by securities analysts (Jensen and Meckling 1976). Michael Jensen popularized these ideas, publishing in the business press as well as in academic journals (Jensen 1984, 1989). Below, we show that leading firms embraced most of these prescriptions. But first we review the role of fund managers in popularizing the innovations.

Institutional investor support for agency theory prescriptions Institutional investors took the lead in promoting agency theory precepts, though hostile takeover firms and securities analysts also played roles, as we discuss below. Executives were generally wary of the changes, preferring the stability of the management system they had developed to a system designed to make their firms more entrepreneurial, and to increase risk. Hence, someone had to hold their feet to the fire. Among institutional investors, public pension funds led the charge, sponsoring an array of shareholder proposals to improve board governance, expand external monitoring, and compensate executives for raising share price (Carleton et al. 1998; Davis and Stout 1992; Gourevitch and Shinn 2005; Jacoby 2007; Proffitt 2001; Useem 1996). CalPERS (California Public Employees’ Retirement System) became active in the early 1980s (Blair 1995; Schwab and Thomas 1998), sponsoring shareholder resolutions and, in 1995, spearheading the Council of Institutional Investors (CII), which assembled public, private, and union fund managers. CII’s “shareholder bill of rights” called for greater shareholder input to reduce agency costs (Jacoby 2007). Mutual fund managers often worked behind the scenes to promote innovations, in part because they hesitated to challenge firms to whom they marketed pension instruments

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(Davis and Kim 2007; Gourevitch and Shinn 2005). Moreover, as institutional shareholding grew after the 1970s, managers at the largest funds were more and more likely to hold large stakes in a given firm, and thus more inclined to try to influence management rather than simply pull their investments out. Although some institutional investors today still take the “Wall Street Walk” when dissatisfied with management, that is, sell stock (Parrino et al. 2003), that strategy is difficult for investors who hold large blocks to carry out, for they risk a substantial price discount in order to liquidate (Coffee 1991).

Consequences of shareholder-value prescriptions The shareholder value movement, fueled by the growth of institutional shareholding, found its voice in a budding financial theory in economics—agency theory. According to the theory, in the 1950s and 1960s America’s leading companies were run by, and for, managers. Jensen and Meckling (1976) proposed that the managers of firms should rightly be working for shareholders. Agency theory moved quickly beyond the ivory tower in the context of the economic crisis of the 1970s. The popular business press provided advice about how to implement agency theory prescriptions in pursuit of the interests of shareholders (Baker and Smith 1998; Hammer and Champy 1993; Prahalad and Hamel 1990; Walther 1997). We discuss several of the key prescriptions offered by agency theorists, as well as innovations promoted by business leaders under the broad heading of shareholder value. We explore the uptake of the new pay-for-performance compensation scheme, the dediversification strategy, the debt-financing strategy, and cost-cutting through downsizing and limiting pension contributions. In the process we review evidence about the effects of these innovations, both on firm performance and on workers.

Equity-based compensation for executives Agency theorists argued that managers tend to be more risk-averse than shareholders would like them to be (Eisenhardt 1989). CEOs fortify their empires against collapse when they should be making money for shareholders. This represents an important cost of agency, or of having a hired hand run the firm you own. One way of reducing agency costs is to have managers hold equity (Jensen and Meckling 1976; Jensen and Murphy 1990). If they hold 100 percent of equity, agency costs drop to zero. Agency theorists called for CEOs to hold substantial equity and to be paid for performance through stock options and bonuses. Previously, they argued, firms made the mistake of paying their executives like bureaucrats, tying compensation to showing up for work rather than to performing (Jensen and Murphy 1990). The old executive salary system encouraged expansion rather than profits, because the highest salaries typically went to the managers of the largest corporations. Stock

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options would remedy this by entitling executives to buy a set number of shares at a future date, typically three years hence, but at the market price of the stock on the date of issue or thereabouts. Executives would thus benefit from increases in stock price between the date of pricing and the date of vesting. Institutional investors became vocal advocates for the new equity-based executive compensation system (Gourevitch and Shinn 2005; Proffitt 2001; Useem 1996). Investors bid up the price of firms that announced long-term incentive plans that would increase executive equity (Westphal and Zajac 1998). CEO stock options and equity increased the value of initial public offerings (Dalton et al. 2003). Options led to particularly close alignment of executive and fund manager interests, as noted, because executives and fund managers alike were rewarded when stock price rose, but were not punished when it fell. Stock options spread far and wide, contributing to a sharp increase in executive compensation. Figure 3.2 charts median CEO compensation over time in our sample of large American firms, by form. Median CEO compensation rose seven-fold from 1984 to 2004, to over $3,500,000. Much of the rise came in the form of stock option grants and bonuses.

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figure 3.2 The Changing Form of CEO Compensation Source: Authors’ sample of 783 large US corporations. Salary and bonus are not reported separately until 1992. The spike in 1992 results from a smaller sample (of larger firms) for that one year. Data on CEO compensation from 1984 to 1991 were provided by David Yermack. CEO compensation data after 1992 are from Standard and Poor’s ExecuComp database, available through Compustat.

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figure 3.3 Equity Holding Among Executives Source: Authors’ sample of 783 large US corporations. Unexercised options excluded. Data on executive equity holding are from the ExecuComp database.

Firms did not heed the advice to require executives to hold equity, however. Over time, despite the fact that executives had significantly more wealth to invest thanks to stock options, they did not invest it in the firms they ran. Figure 3.3 shows equity ownership by executives in our sample of 783 firms between 1992 and 2005, excluding unexercised options. Data on earlier years are not available. Equity ownership by CEOs, and by all executives, scarcely changes over the period while, as we see in Figure 3.2, median income tripled. What were the effects of stock options? First, they do not appear to have increased corporate profits or share value, although they do appear to have increased executive risk-taking, leading more often to outsized losses than to outsized gains. Second, they do appear to have encouraged executive earnings “management” to increase share price, that is, accounting fraud of the sort responsible for the Enron debacle. Third, the most dramatic effect of stock options was to transfer wealth from shareholders to the financial elite. Corporate income that might have gone to workers within the firm, in the form of increased wages, or to worker-owners in and out of the firm in the form of dividends, went instead to top executives.

Profits and risk-taking Agency theory suggests that stock options and equity holding should lead to improved profits and share price. In line with the theory, one study suggests that the spread of

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stock options caused total compensation to be much more closely aligned with firm performance (Hall and Liebman 1998). Evidence that option grants and equity holding lead firms to superior performance, however, is weak and there is some evidence that options increase recklessness. Many studies have looked for a relationship between stock options or equity holding and corporate performance, without finding one. In a meta-analysis of 220 studies of equity holding, Dalton and colleagues (2003) reach the conclusion that CEO, officer, and director equity holdings have no clear effect on performance. Quite a few studies have shown that pay-for-performance compensation systems have been subverted by executives, who benefit whether or not they improve performance (Bebchuk and Fried 2003; Bebchuk et al. 2002). Moreover, Sanders and Hambrick (2007) show that stock options encouraged reckless risk-taking by executives, because options reward executives for increases in stock price in the near term but do not punish them for declines. Their analysis shows that option-loaded CEOs are more likely to deliver big losses than big gains. One reason for the excessive risk-taking, they suggest, is that boards did not follow the agency theory dictum of requiring executives to hold more equity.

Earnings management Stock options create an incentive for executives to ensure that earnings meet analyst projections. As investors became dependent on securities analysts to evaluate firms, they paid increasing attention to projections. When earnings fall short of projections, stock price usually dips, which is bad news for executives holding options. Earnings management, by which firms manipulate reported earnings to please analysts, was one response. One signal of earnings management is earnings restatement, by which firms report corrected figures after they have submitted erroneous figures. Restatements rose among Fortune 500 companies over time, and some studies link the rise to stock option grants (Burns and Kedia 2006; Efendi et al. 2007). Using data on thousands of quarterly reports between 1974 and 1996, Degeorge et al. (1999) show that firms are significantly more likely to report earnings that exactly match analyst predictions than they are to report earnings that overshoot or undershoot by even a penny, suggesting that firms regularly manage earnings to hit analyst targets. Some of the accounting techniques they use amount to little more than fraud, and were prominent in the Enron, WorldCom, and Tyco scandals. By misleading investors about profits, executives at those firms fattened their own wallets before the share price collapsed, wiping out the investments of workerowners. Thus, for instance, over half of the funds in Enron’s employee 401(k) plans were invested in Enron shares when the company’s stock price dropped from $90 dollars to 26 cents in November of 2001. More generally, earnings management often catches up with firms, and so while executives may benefit from boosting share value before cashing in on stock options, the average shareholder eventually pays the price.

Transfer of profits to executives Finally, stock options have transferred the wages of the firm away from its employees and investors. Agency theorists promote stock options with the idea that option grants

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come at no cost to the firm, because they simply reward executives with a portion of the earnings they have achieved for the firm. But evidence that stock option grants do not promote corporate profits or share value belies that idea. If stock options do not lead to increases in firm value, then options do not pay for themselves. Investors pay for them through diluted ownership, and workers pay for them through diluted wages. The cost of options and bonuses can be seen in Figure 3.2, which shows the dramatic increase in CEO income. As stock options have not led to increases in share value, one might conclude that most of the run-up in compensation came directly at the expense of shareholders. What were the effects on workers of the growing share of income accruing to the chief executive? Between 1945 and 1970, working Americans enjoyed steady growth in earnings and the gap between rich and poor remained stable. By the early 1980s, median earnings were stagnating and income inequality was growing (Morris and Western 1999). By the early 1990s, a significant number of workers were earning less than their 1960s counterparts (Bernstein and Mishel 1997). The financial crisis of 2008 exacerbated these trends, and the earnings gap is now at its widest since the census began keeping track and is the widest of any Western industrialized nation (DeNavas-Walt et al. 2010). As we noted at the outset, the top 1 percent of Americans earned 23.5 percent of national income in 2007, up from 9 percent in 1970 (Piketty and Saez 2003, 2009). Change in the distribution of corporate income among our 783 large US firms can be seen in Figure 3.4, charting chief executive compensation over the average income of all

Base Component (Salary & Bonus)

figure 3.4 Ratio of the CEO Compensation to the Average Compensation for Other Employees Source: Authors’ sample of 783 large US corporations.

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other employees. Ideally we would remove top management team (TMT) compensation from the denominator, but full data on TMT compensation are not available. We estimate the average compensation for all employees but the CEO, dividing labor expense by the total number of employees (minus CEO compensation). The ratio of CEO compensation to average compensation increases dramatically, particularly after the mid1990s. Most of the change is caused by stock options grants; the ratio of base pay (salary and bonus) barely increased.

Industrial focus From the 1950s through the 1970s, leading American firms remade themselves as conglomerates. By 1980, almost half of the Fortune 500 operated in three or more two-digit Standard Industrial Classification (SIC) sectors, while only 25 percent operated in a single industry (Davis et al. 1994: 553). Agency theory challenged the efficiency of conglomerates. Portfolio theory had provided a rationale for conglomeration, suggesting that the modern firm should run an internal capital market, investing in promising sectors and spreading risk across different sorts of industries. Agency theory suggested, in the midst of the stagflation of the 1970s, that diversification was not in the interest of shareholders, and managers alone stood to gain by acquiring businesses of questionable value that would reduce the risk of corporate collapse (Jensen and Meckling 1976). They insisted that the investor, not the firm, should assemble portfolios to spread risk, and a diversified investor should expect some firms to be culled from the herd (Amihud and Lev 1981; Bettis 1983; Teece 1982). Shareholders should shy away from ponderous conglomerates that held poorly performing enterprises in industries little understood by their executives (Shleifer and Vishny 1989, 1997). Firms should be lean and focused. This idea was widely promoted by management consultants in the wake of agency theory. The first blockbuster management bible, In Search of Excellence (Peters and Waterman 1982), admonished executives to “stick to the knitting,” by focusing on the core business of the firm. In 1990 the reengineering gurus C. K. Pralahad and Gary Hamel published “The Core Competencies of the Firm” in Harvard Business Review, arguing that a management team should play on its strengths. As Michael Useem (1996: 153) argues, “While diversification had been a hallmark of good management during the 1960s, shedding unrelated business had become the measure during the 1980s and 1990s.” Many institutional investors came to favor focused firms not only because they were converts to agency theory, but also because they preferred to build their own diversified portfolios out of firms with clear industry profiles (Dobbin and Zorn 2005). Hostile takeover firms encouraged dediversification in the 1980s, targeting diversified conglomerates that they could break into pieces to be resold at a profit (Davis et al. 1994; Fligstein and Markowitz 1993; Liebeskind et al. 1996; Matsusaka 1993). Institutional investors were deeply involved in hostile takeovers in the 1980s, often supporting takeovers that were opposed by incumbent management (Holmstrom and Kaplan 2001). Where

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figure 3.5 Average Level of Diversification Source: Authors’ sample of 783 large US corporations.

institutional investors held sway, firms were fast to dediversify. From the 1980s, Fortune 500 companies with concentrated ownership were most likely to spin off unrelated businesses (Useem 1996: 153). The threat of hostile takeovers induced many conglomerates to dediversify on their own. Securities analysts joined the dediversification chorus. They also carried the banner of agency theory, but had their own reasons as well. Analysts specialized by industry, and conglomerates that did not fall into a neat category usually failed to win coverage. Executives coveted coverage because coverage was overwhelmingly positive, encouraging investors to buy their stock. This motivated companies to dediversify in order to win coverage and boost institutional investor interest (Zuckerman 1999, 2000). Fund manager preferences clearly influenced firms (Campa and Kedia 2002). In Figure 3.5, we chart the level of diversification among our sample of large American firms, using the entropy index, which measures diversification based on the contribution of each industry to the firm’s sales. Diversification declined considerably between 1980 and the mid-1990s. This pattern suggests that even after the hostile takeover wave subsided, diversification continued to decline, as executives voluntarily spun off units unrelated to their core businesses.

Dediversification and performance Did dediversification improve performance? The evidence is mixed. Some studies find a “conglomeration discount” in stock price in the 1960s and after the mid-1970s, but not in between (Matsusaka 1993; Servaes 1996), and others find no discount at all (Campa and

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Kedia 2002; Villalonga 2004). The pattern is consistent with the proposition that the post-1975 conglomerate stock price discount was a consequence of investors fulfilling the prophesy of agency theory (LeBaron and Speidell 1987; Wernerfelt and Montgomery 1988). While it is not clear that focused firms have higher profits, it does seem clear that corporate spinoffs produced widespread layoffs.

Dediversification and job losses One clear effect of the restructuring fad of the 1980s and 1990s was that many workers lost their jobs. Consolidations within an industry, of the sort that became popular, are particularly likely to result in downsizings, as management attempts to make the combined company profitable quickly. In the telecommunications industry, the list of postmerger downsizings includes 10,000 job losses after the Bell Atlantic–Nynex merger of 1997, 13,000 job cuts after the Quest–US West merger in 2000, and another 13,000 jobs lost after SBC’s acquisition of AT&T in 2005 (Cauley 1997; Romero 2000; Young 2005). In defense, Martin Marietta announced 11,000 jobs cut after acquiring GE Aerospace in 1993, and two years later, when Martin Marietta merged with Lockheed, it cut a further 12,000 jobs (Gilpin 1995; Sims 1993). Restructuring to produce corporate focus meant significant job losses across a range of industries. Hostile takeovers of the 1980s generally had negative consequences for employment (Harrison and Bluestone 1988). Firms, and groups of individual investors, borrowed heavily to acquire targets, and then, to pay off debts, they sold assets and cut wage costs. Some argued that anticipated labor cost savings explained the high takeover premiums seen in the 1980s (Shleifer and Summers 1988). Few empirical studies have assessed that claim, but Bhagat et al. (1990), examining 62 hostile takeover contests between 1984 and 1986, reported that layoffs could account for 11 percent to 26 percent of the premium. They identified 28 cases of downsizing subsequent to a takeover bid, but did not consider job cuts in the bidding firm. The hostile takeover wave receded after the crash of the junk bond market in the late 1980s, but the level of merger and acquisition (M&A) activity reached another peak in the 1990s, as industrial giants combined in hope of enhancing industrial focus and market power.

Debt-financing A third way of reducing agency costs, according to Jensen and Meckling (1976), is to take on debt. Debt reduces the share of equity financing and thus moderates the conflict of interest between shareholders and managers. Agency costs stem from executives’ preference for stability, which can lead them to make investments that will reduce the risk of firm failure but also dilute profits. Investors with diversified portfolios should prefer high-reward strategies that carry some risk of firm failure, whereas executives should prefer strategies that minimize failure risk. According to the theory, CEOs will not borrow money at 6 percent for an endeavor that will return 4 percent, because they

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figure 3.6 Debt-to-Equity Ratio Source: Authors’ sample of 783 large US corporations. Debt-to-equity ratio is calculated as total long-term debt divided by common equity. Data on both items are from Compustat.

must account for capital costs, but they might invest profits, because they do not have to account for capital costs. Under the theory, institutional investors came to favor firms that used debt financing, taking it as a signal of management’s conviction that new investments will pay off. Because debt financing multiplies returns to equity, agency theory suggests that shareholders should prefer it to the issuance of new stock, and that they should prefer to see profits returned to shareholders through dividends or share buybacks that boost share value (Westphal and Zajac 1998; Zajac and Westphal 2004). The stock market thus reacts positively to most leverage-increasing transactions, such as debt-for-equity swaps (Finnerty 1985; Lys and Sivaramakrishnan 1988). Following the advice of agency theorists, large American corporations increased leverage significantly after 1980. In Figure 3.6, we report debt–equity ratios by quartiles for the firms in our sample from 1963 to 2005. Before the mid-1980s, the median firm had about 40 cents of debt for every dollar of equity. This rose to about 60 cents after the mid-1980s. For firms at the 75th percentile, debt rose from about 80 cents on the dollar to over 110 cents for much of the last half of the period.

Debt and corporate vulnerability While debt financing may reduce agency costs associated with free cash flow (Jensen 1986), it can increase corporate vulnerability (Modigliani and Merton 1958). Recent

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studies show that firms with heavy debt burdens are especially vulnerable during economic downturns (Campello 2003; 2006). Heavy use of debt can also be problematic during economic upturns when interest rates rise; if returns from a new investment do not exceed the interest on the bonds used to finance it, a firm may find itself with debt it cannot pay off. In the circumstance, executives have frequently made bets on high-risk investments to pay bondholders when their initial investments do not pay off (Crutchley and Hansen 1989: 37). Many accounts of the recent financial crisis point to excess leverage by mortgage lenders, which put them at risk when mortgage-backed securities and mortgages themselves failed, and encouraged them to try even riskier moves to save themselves (Johnson 2008; Posner 2009; Sorkin 2009). Hence, debt can make a firm vulnerable both in periods of economic dynamism, when interest rates rise, and in periods of recession, when sales lag. Employees and investors alike pay the cost of this vulnerability when a firm declares bankruptcy or closes its doors.

Defunding pension funds Corporations that took on excessive debt, whether as part of a takeover process or as part of a business strategy, increasingly withdrew investments from pension funds. Ippolito and James (1992) show that there is a strong and statistically significant increase in pension terminations following leveraged buyout announcements, and other studies (Hamdallah and Ruland 1986; Mittelstaedt 1989; Stone 1987) find that firms with large debt burdens, which may have trouble raising cash in hard times, are more likely to raid well-funded pension plans. Bankruptcy judges often allowed firms to reduce assets in pension schemes that appeared to be overfunded. Following subsequent market declines, these funds sometimes did not have adequate assets, and had to be bailed out by the Pension Benefit Guarantee Corporation. Employees and taxpayers ultimately bore the cost of this strategy.

Raising value by downsizing Practitioners pursued agency theory’s charge, of putting shareholder value first, with several strategies designed to reduce costs to raise profits and share price. A number of CEOs won fame through aggressive cost-cutting (Khurana 2002). “Chainsaw” Al Dunlap made his name at Sunbeam, and preached the virtues of restructuring and shareholder value in his bestselling autobiography, Mean Business: How I Save Bad Companies and Make Good Companies Great. Soon after arriving at Sunbeam in 1996, he announced a plan to cut the workforce of 12,000 by half, an unheard of feat (Collins 1996). The stock market welcomed the announcement, but the firm’s stock price dropped from $52 to $26 in 1997 as sales faltered. Nevertheless, in March of 1998, the board extended another three-year contract that doubled Dunlap’s salary and granted him a staggering 3.75 million stock options. He responded with yet another plan to cut about 6,400 jobs, or 40 percent of total employment of the company after its acquisition of Coleman (Canedy 1998a).

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Waves of downsizing swept through corporate America from the early 1980s, eroding what Paul Osterman (1999: 21) terms the “postwar institutional structure” of the labor market. Firms had laid off employees in hard economic times before, but now even healthy firms were laying off employees in the hope of boosting stock price (Cappelli 1999; Osterman 1999). Keeping investors happy was the motive. When Jonathan Schwartz, the new CEO of Sun Microsystems, announced on May 31, 2006, that the company planned to cut 4,000 to 5,000 jobs, he argued that the expected cost savings from the job cuts would help Sun meet analyst forecasts of a loss of two cents a share in the fourth quarter. Eastman Kodak announced a plan to trim 10,000 jobs despite strong profits, as it was under pressure from institutional investors to increase margins (Holusha 1993a). Xerox announced a plan to cut 10,000 jobs as well, or 10 percent of its workforce, despite consistent profitability; its CEO explained, “To compete effectively, we must have a lean and flexible organization which can deliver the most cost-effective document-processing products and services” (Holusha 1993b). Both the CEO and the institutional investor could agree on the goal of boosting share value (Flynn 2006). As firms strove to improve their stock performance under the oversight of demanding investors, they became more likely to downsize (Budros 1997; Lazonick and O’Sullivan 2000). Downsizings thus increased over time, even when the economy was booming. In Figure 3.7, we plot the proportion of firms in our sample that announced at least one downsizing each year. Even though companies still cut jobs frequently during economic downturns (during the recessions in the early 1980s, the early 1990s, and the early

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2000s), they continued to downsize throughout the 1990s despite an improving economy.

Raising value by cutting pension contributions The defined-benefit pension plan became a significant source of cost-cutting in the 1990s. Firms had generally moved away from those plans to reduce their costs. Even healthy firms, such as IBM and Sears, froze their defined benefit plans, moving employees over to defined contribution plans (Munnell et al. 2006). Between 2004 and 2006 more than 400,000 current employees and more than a million new workers were affected by the freezes (Munnell et al. 2006). This transition itself transferred risk from firms to employees, as the new plans carried no guarantees against stagnation or loss (Hacker 2006). In the 1990s, the run-up of the stock market made many defined-benefit plans appear to be overfunded, which enabled corporations to curtail or cease contributions. The pension plan became a source of cost-cutting. After the post-9/11 stock market decline, and drop in interest rates, this trend came to an end (Munnell and Soto 2007), but market volatility has left many plans significantly underfunded and many employers have neglected to fill the coffers. In Figure 3.8, we chart the average net funding status of defined benefit plans in our sample of 783 large US firms, calculated as the difference between current pension assets and projected benefit obligations. Throughout the

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1980s and 1990s, the net funding status of the average fund remained above zero, but then after 2001, it declined significantly and has deteriorated further during the latest recession. A stock market boom could restore these funds to health, but failing that the cost of this underfunding will likely be transferred to taxpayers, as the Pension Benefit Guarantee Corporation bails out funds that cannot meet their obligation.

Conclusion Under the tutelage of newly empowered institutional investors, executives pursued shareholder value with the tools of agency theory. They changed much about the way they did business. Firms used to pay the CEO 20 times what the average employee made. Now they pay the CEO a hundred times as much, draining value from investors. They used to pursue conglomeration to spread risk. Lately they have bought and sold units to focus on a single industry, and have laid off hordes in the process. They used to borrow 40 cents on the equity dollar, and now they borrow 60 cents, which increases the risk of bankruptcy and corporate raiding of the pension fund. Firms used to announce layoffs when their sales slowed. Now they lay off workers when sales are booming in the hope of boosting stock price. They used to put money in the pension fund for a rainy day. Now they let someone else worry about rainy days, with the result that each stock market drop puts funds further in the red. These changes were promoted by proponents of the shareholder value revolution, in the name of reorienting the firm to the true interest of shareholders in the steady rise of firm value. The new business practices were outlined by agency theorists in economics in the 1970s and 1980s, but institutional investors made them popular, often despite the resistance of corporate leaders who were mostly content with the status quo, in which their positions were stable and their firms were protected from the ups and downs of the market. Institutional investors did not find it easy to convince executives to dediversify, use debt financing, accept stock option compensation, or focus on cutting costs rather than expanding by conglomeration. But the end result of these changes has been a bonanza for the financial elite of fund managers, securities analysts, investment bankers, and corporate executives themselves. The impact of these innovations on the average worker or pensioner who holds stock through a pension fund has generally been negative. While it is certainly the case that the one interest all shareholders, from the investment banker down to the assembly line worker, have in common is to see share value rise, the growing primacy of share value has not served the other interests of the average worker or pensioner, who is not only the most common shareholder but is increasingly, with her fellows, the majority shareholder in America’s largest corporations. We have reviewed evidence that many innovations pursued under the banner of shareholder value produced results that conflicted sharply with the interests, and likely the values, of the average shareholder.

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If the shareholder value movement had unambiguously enriched the average investor in the process, then we might conclude that institutional investors who promoted agency theory precepts had served their masters, the shareholders, well. The agency theory prescriptions designed to make the firm more entrepreneurial and focused have changed how firms behave, but evidence does not suggest that firms that adopted them saw improvements in earnings or share value. The evidence points to the conclusion that institutional investors who championed agency theory have failed to promote shareholder value even in the narrow sense of increasing share price.

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Carleton, W. T., Nelson, J. M., and Weisbach, M. S. (1998). “The Influence of Institutions on Corporate Governance through Private Negotiations: Evidence from TIAA-CREF.” Journal of Finance, 53/4: 1335–62. Cauley, L. (1997). “Bell Atlantic, Nynex Job Cuts to Hit 10,000.” The Wall Street Journal, May 6: A3. Coffee, J. C., Jr. (1991). “Liquidity versus Control: The Institutional Investor as Corporate Monitor.” Columbia Law Review, 91/6: 1277–368. Collins, G. (1996). “Sunbeam to Halve Work Force of 12,000 and Sell Some Units.” The New York Times, November 13: D1. Crutchley, C. E. and Hansen, R. S. (1989). “A Test of the Agency Theory of Managerial Ownership, Corporate Leverage, and Corporate Dividends.” Financial Management, 18/4: 36–46. Dalton, D. R., Daily, C. M., Certo, S. T., and Roengpitya, R. (2003). “Meta-Analyses of Financial Performance and Equity: Fusion or Confusion?” Academy of Management Journal, 46/1: 13–26. Davis, G. F. and Kim, E. H. (2007). “Business Ties and Proxy Voting by Mutual Funds.” Journal of Financial Economics, 85/2: 552–70. ——– and Stout, S. K. (1992). “Organization Theory and the Market for Corporate Control: A Dynamic Analysis of the Characteristics of Large Takeover Targets, 1980–1990.” Administrative Science Quarterly, 37/4: 605–33. ——– , Diekmann, K. A., and Tinsley, C. H. (1994). “The Decline and Fall of the Conglamerate Firm in the 1980s: The Deinstitutionalization of an Organizational Form.” American Sociological Review, 59/4: 547–70. Degeorge, F., Patel, J., and Zeckhauser, R. (1999). “Earnings Management to Exceed Thresholds.” Journal of Business, 72/1: 1–33. DeNavas-Walt, C., Proctor, B. D., and Smith, J. C. (2010). “Income, Poverty, and Health Insurance Coverage in the United States: 2009.” Current Population Reports, 60–238. Dobbin, F. (1992). “The Origins of Private Social Insurance: Public Policy and Fringe Benefits in America, 1920–1950.” American Journal of Sociology, 97/5: 1416–50. ——– and Zorn, D. M. (2005). “Corporate Malfeasance and the Myth of Shareholder Value.” Political Power and Social Theory, 17: 179–98. Donaldson, T. and Preston, L. E. (1995). “The Stakeholder Theory of the Corporation: Concepts, Evidence, and Implications.” Academy of Management Review, 20/1: 65–91. Efendi, J., Srivastava, A., and Swanson, E. P. (2007). “Why Do Corporate Managers Misstate Financial Statements? The Role of Option Compensation and Other Factors.” Journal of Financial Economics, 85/3: 667–708. Eisenhardt, K. M. (1989). “Agency Theory: An Assessment and Review.” Academy of Management Review, 14/1: 57–74. Fama, E. F. (1980). “Agency Problems and the Theory of the Firm.” Journal of Political Economy, 88/2: 288–307. ——– and Jensen, M. C. (1983). “Separation of Ownership and Control.” Journal of Law and Economics, 26/2: 301–25. ——– (1985). “Organizational Forms and Investment Decisions.” Journal of Financial Economics, 14/1: 101–19. Finnerty, J. D. (1985). “Stock-for-Debt Swaps and Shareholder Returns.” Financial Management, 14/3: 5–17. Fligstein, N. and Markowitz, L. (1993). “Financial Reorganization of American Corporations in the 1980s,” in W. J. Wilson (ed.), Sociology and the Public Agenda. Beverly Hills, CA: Sage Publications, 185–206.

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Flynn, L. J. (2006). “Sun Says It Will Cut at Least 4,000 Jobs.” The New York Times, May 31: C1. Freeman, R. E. (1984). Strategic Management: A Stakeholder Approach. Boston, MA: Pitman. Gilpin, K. N. (1995). “Lockheed to Eliminate 12,000 Jobs.” The New York Times, June 27: D1. Gourevitch, P. A. and Shinn, J. (2005). Political Power and Corporate Control: The New Global Politics of Corporate Governance. Princeton, NJ: Princeton University Press. Hacker, J. S. (2006). The Great Risk Shift: The Assault on American Jobs, Families, Health Care, and Retirement and How You Can Fight Back. Oxford: Oxford University Press. Hall, B. J. and Liebman, J. B. (1998). “Are CEOS Really Paid Like Bureaucrats?” Quarterly Journal of Economics, 113/3: 653–91. Hamdallah, A. E.-S. and Ruland, W. (1986). “The Decision to Terminate Overfunded Pension Plans.” Journal of Accounting and Public Policy, 5/2: 77–91. Hammer, M. and Champy, J. (1993). Reengineering the Corporation: A Manifesto for Business Revolution. New York: Harper Business. Harrison, B. and Bluestone, B. (1988). The Great U-Turn: Corporate Restructuring and the Polarizing of America. New York: Basic Books. Holmstrom, B. and Kaplan, S. N. (2001). “Corporate Governance and Merger Activity in the United States: Making Sense of the 1980s and 1990s.” Journal of Economic Perspectives, 15: 121–44. Holusha, J. (1993a). “10,000 Jobs to Be Cut by Kodak.” The New York Times, December 9: D1. ——– (1993b). “A Profitable Xerox Plans to Cut Staff by 10,000.” The New York Times, August 19: D1. Ippolito, R. A. and James, W. H. (1992). “LBOs, Reversions and Implicit Contracts.” Journal of Finance, 47/1: 139–67. Jacoby, S. M. (2007). “Principles and Agents: CalPERS and Corporate Governance in Japan.” Corporate Governance, 15/1: 5–15. Jensen, M. C. (1984). “Takeovers: Folklore and Science.” Harvard Business Review, 62/6: 109–21. ——– (1986). “Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers.” American Economic Review, 76/2: 323–9. ——– (1989). “Eclipse of the Public Corporation.” Harvard Business Review, 67/5: 61–74. ——– and Meckling, W. H. (1976). “Theory of the Firm: Managerial Behavior, Agency Costs, and Ownership Structure.” Journal of Financial Economics, 3/4: 305–60. Jensen, M. C. and Murphy, K. J. (1990). “Performance Pay and Top-Management Incentives.” Journal of Political Economy, 98/2: 225–264. Johnson, S. (2008). “Faltering Economic Growth and the Need for Economic Stimulus”. Hearing of the Joint Economic Committee of Congress, October 30. Khurana, R. (2002). Searching for a Corporate Savior: The Irrational Quest for Charismatic CEOs. Princeton, NJ: Princeton University Press. Lazonick, W. and O’Sullivan, M. (2000). “Maximizing Shareholder Value: A New Ideology for Corporate Governance.” Economy and Society, 29/1: 13–35. LeBaron, D. and Speidell, L. S. (1987). “Why Are the Parts Worth More than the Sum? ‘Chop Shop,’ a Corporate Valuation Model,” in L. E. Browne and E. S. Rosengren (eds.), The Merger Boom. Boston, MA: Federal Reserve Bank of Boston, 78–101. Liebeskind, J. P., Opler, T. C., and Hatfield, D. E. (1996). “Corporate Restructuring and the Consolidation of US Industry.” Journal of Industrial Economics, 44/1: 53–68. Lys, T. and Sivaramakrishnan, K. (1988). “Earnings Expectations and Capital Restructuring: The Case of Equity-for-Debt Swaps.” Journal of Accounting Research, 26/2: 273–99.

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Matsusaka, J. G. (1993). “Takeover Motives during the Conglomerate Merger Wave.” RAND Journal of Economics, 24/3: 357–79. Mittelstaedt, H. F. (1989). “An Empirical Analysis of the Factors Underlying the Decision to Remove Excess Assets from Overfunded Pension Plans.” Journal of Accounting and Economics, 11/4: 399–418. Modigliani, F. and Merton, H. M. (1958). “The Cost of Capital, Corporation Finance and the Theory of Investment.” American Economic Review, 48/3: 261–97. Morris, M. A. and Western, B. (1999). “Inequality in Earnings at the Close of the Twentieth Century.” Annual Review of Sociology, 25/1: 623–57. Munnell, A. H. and Soto, M. (2007). “Why Are Companies Freezing Their Pensions?” Working paper. (accessed August 3, 2011). ——– Golub-Sass, F., Soto, M., and Vitagliano, F. (2006). “Why Are Healthy Employers Freezing Their Pensions?” Center for Retirement Research at Boston College, Issue in Brief no. 44. Osterman, P. (1999). Securing Prosperity. Princeton, NJ: Princeton University Press. Parrino, R., Sias, R. W., and Starks, L. T. (2003). “Voting with Their Feet: Institutional Ownership Changes around Forced CEO Turnover.” Journal of Financial Economics, 68/1: 3–46. Peters, T. J. and Waterman, R. H. (1982). In Search of Excellence: Lessons from America’s BestRun Companies. New York: Harper & Row. Piketty, T. and E. Saez. (2003). “Income Inequality in the United States: 1913–1998.” Quarterly Journal of Economics, 118/1: 1–39. ——– (2009). “Income Inequality in the United States: Updated Tables.” (accessed August 3, 2011). Posner, R. A. (2009). A Failure of Capitalism: The Crisis of ‘08 and the Descent into Depression. Cambridge, MA: Harvard University Press. Prahalad, C. K. and Hamel, G. (1990). “The Core Competence of the Corporation.” Harvard Business Review, 68/3: 79–91. Proffitt, W. T. (2001). “The Evolution of Institutional Investor Identity: Social Movement Mobilization in the Shareholder Activism Field.” PhD thesis, Northwestern University, Evanston, IL. Romero, S. (2000). “Qwest Stock Dips on News of 13,000 Layoffs.” The New York Times, September 8: C6. Sanders, W. G. and Hambrick, D. C. (2007). “Swinging for the Fences: The Effects of CEO Stock Options on Company Risk Taking and Performance.” Academy of Management Journal, 50/5: 1055–78. Schwab, S. J. and Thomas, R. S. (1998). “Realigning Corporate Governance: Shareholder Activism by Labor Unions.” Michigan Law Review, 96/4: 1018–94. Servaes, H. (1996). “The Value of Diversification During the Conglomerate Merger Wave.” Journal of Finance, 51/4: 1201–25. Shleifer, A. and Summers, L. H. (1988). “Breach of Trust in Hostile Takeovers,” in A. J. Auerbach (ed.), Corporate Takeovers: Causes and Consequences. Chicago: University of Chicago Press, 33–67. ——– and Vishny, R. W. (1989). “Management Entrenchment: The Case of Manager-Specific Investments.” Journal of Financial Economics, 25/1: 123–39. ——– (1997). “A Survey of Corporate Governance.” Journal of Finance, 52/2: 737–83.

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Sims, C. (1993). “Martin Marietta to Eliminate 11,000 Jobs.” The New York Times, October 1: D1. Sorkin, A. R. (2009). Too Big to Fail: The Insider Story of How Wall Street and Washington Fought to Save the Financial System from Crisis—and Themselves. New York: Viking. Stephens, J. D. (1979). The Transition from Capitalism to Socialism. London: Macmillan. Stone, M. (1987). “A Financing Explanation for Overfunded Pension Plan Terminations.” Journal of Accounting Research, 25/2: 317–26. Teece, D. J. (1982). “Towards an Economic Theory of the Multiproduct Firm.” Journal of Economic Behavior & Organization, 3/1: 39–63. Thelen, K. (2003). “How Institutions Evolve: Insights from Comparative Historical Analysis,” in J. Mahoney and D. Rueschemeyer (eds.), Comparative Historical Analysis in the Social Sciences. Cambridge: Cambridge University Press, 208–69. Useem, M. (1996). Investor Capitalism: How Money Managers are Changing the Face of Corporate America. New York: Basic Books. Villalonga, B. (2004). “Does Diversification Cause the ‘Diversification Discount’?” Financial Management, 33/2: 5–27. Walther, T. (1997). Reinventing the CFO: Moving from Financial Management to Strategic Management. New York: McGraw-Hill. Wernerfelt, B. and Montgomery, C. A. (1988). “Tobin’s q and the Importance of Focus in Firm Performance.” American Economic Review, 78/1: 246–50. Westphal, J. D. and Zajac, E. J. (1998). “The Symbolic Management of Stockholders: Corporate Governance Reforms and Shareholder Reactions.” Administrative Science Quarterly, 43/1: 127–53. Young, S. (2005). “SBC–AT&T Deal Relies on Savings Through Job Cuts.” The Wall Street Journal, February 2: A2. Zajac, E. J. and Westphal, J. D. (2004). “The Social Construction of Market Value: Institutionalization and Learning Perspectives on Stock Market Reactions.” American Sociological Review, 69/3: 433–57. Zuckerman, E. W. (1999). “The Categorical Imperative: Securities Analysts and the Illegitimacy Discount.” American Journal of Sociology, 104/5: 1398–438. ——– (2000). “Focusing the Corporate Product: Securities Analysts and De-diversification.” Administrative Science Quarterly, 45/3: 591–619.

chapter 4

busi n ess grou ps a n d fi na nci a l m a r k ets as em ergen t phenom ena 1, 2 b ruce k ogut

The study of the business group was once lamented for its paucity of research. The research of the past two decades has remedied this deficit quantitatively and qualitatively. However, the search for robust findings has proved often elusive, a challenge for comparative economic sociology in general due to the complexity of the subject and the uneven access to data. This chapter proposes an alternative perspective on business groups, and their relation to finance, to respond to this challenge. This perspective draws upon the sciences of complexity. The sociology of financial markets can be viewed as a search to link the emergence of the macrostructural patterns in economic markets to the micro-behaviors of participants, or agents, in these markets. The clues to this investigation are the signatures in these patterns that are known to be expressions of particular types of generating rules that guide the actions of these agents. While these signatures are statistical, their origins and dynamics are governed by the social relations among traders, investors, and entrepreneurs. Financial and economic markets are complex systems, and yet considerable progress has been made toward understanding their structural patterns and dynamics, and the micro-behaviors of traders and the rules by which they interact. Business groups are sociologically important because they are invariably associated with economic and political power through their control over sizeable business enterprises. They pose the interesting question of why this form is so pervasive across countries despite large institutional differences. Their common occurrence across many countries suggests that they are emergent phenomena arising from similar underlying dynamics. While pervasive, they come in many varieties and flavors. Therefore, a simple definition is valuable. Granovetter (2005) offers such a definition in the following: “ ‘Business groups’ are sets of legally separate firms bound together in persistent formal and/or informal ways.”

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Granovetter’s definition is useful for distinguishing business groups from other kinds of financial markets and organizations, such as venture capital or private equity. Venture capital and private equity share a common structure: a financial firm creates a fund in which private individuals or financial institutions invest as limited partners and this fund then invests in companies in return for equity. Venture capital investments target new and private firms; private equity is investment in established firms, some of which are already public with stocks that may be traded on formal exchanges. In addition, in both cases, funds can co-invest through syndications, though syndicates are more common in venture capital. These investments are intended to be of limited duration, with the goal to “exit” the investment in a few years by selling shares to the public through an initial public offering (IPO) or to private investors. Because they are of limited duration, venture capital and private equity funds do not meet the criterion of “persistent” in Granovetter’s definition. The activities of a business group are often similar to venture capital and private equity funds insofar that they are all types of entrepreneurial investments in new technologies or business models or in “turning around” existing businesses. In most countries, venture capital and private equity markets do not exist or are very new and small. Business groups provide a source of entrepreneurial finance. However, business groups are also very different from venture capital and private equity firms. Through favored access to capital (either due to relationships with external banks or to access to a “house” bank that belongs to the group), business groups can reinvest capital in entrepreneurial opportunities by redirecting capital from one firm to the other. To the contrary, venture capital and private equity firms treat each of their investments as stand-alone entities. The investment horizons of business groups are long-term and there is rarely any planning for a quick exit—often there are no public equity markets in any event. In addition to persistence, the Granovetter definition implies financial and business coordination through formal or informal ways. The definition appropriately leaves, as an empirical issue, the question of whether this coordination is primarily economic and financial (i.e., equity ties) or social, for example, through the ties of family, ethnicity, and identity. It is also sufficiently general to permit business groups to be horizontally or vertically organized. Horizontal means the group enterprises are specialized to different businesses, such as electronics, telecommunications, chemicals; vertical means that the enterprises are organized in a supply chain, such as in car production which includes suppliers of electronics, drive trains, and engines to a final assembler. This structural dimension is separate from the way in which financial control is legally exercised, such as through a single entity (such as a main bank), which may just hold portfolio shares, or through pyramidal ownership chains. There are then three dimensions to business groups: social type of the group; activity structure, for example, horizontal and vertical; and financial organization. For example, overseas Chinese businesses in East Asia are frequently family groups, horizontally diversified, and organized through pyramidal ties often lacking transparency. The classic German Konzern is frequently a portfolio company owned either by families, trusts

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(e.g., Zeiss, Bosch), or dominant owners; the portfolio holds controlling shares of equity in diversified businesses. The sociological distance between a Chinese family business group and a German Konzern is large, and yet the term business group applies to both. Even within a country, business groups can differ. For example, the Japanese keiretsu refers to the classic economic grouping of horizontally diversified firms with equity cross-holdings and debt financed by a main bank—but it can also mean a vertically organized tiered supply chain to a final assembler, for example, Toyota, who will hold equity in the first-tier suppliers but will not directly own equity in the second- or thirdtier suppliers.3 This distinction between horizontal and vertical keiretsu was briefly important to a somewhat fragile economic literature in the early 1990s that sought to attribute efficiency to the latter form, and inefficiency to the horizontal type (Lawrence 1993). The attraction of business groups as a subject of study to economics and sociology, and therefore to economic sociology, is not entirely mysterious. Since the entity is so variable in definition and the empirical heterogeneity is so vast, the subject provides multiple doors of analytical entry into this palatial domain. Thus, it is possible to have a lively discussion in many rooms in this palace, fairly untroubled by global consistency of argument or fact. This quip is, as all members of this rhetorical genre are, grossly unfair to the many excellent studies. Nevertheless, I will stand by it, for it suggests the importance of a healthy reliance on seeking common invariants across contexts rather than rushing too quickly into the heterogeneity. Both economics and sociology are guilty, especially in regard to examining the function–form question of the efficiency of business groups while neglecting larger structural questions. It may be profitable, as argued below, to analyze business groups as emergent from the social and cultural rules that guide entrepreneurial formation and ownership. Let’s begin, however, with the classic argument over the efficiency of the business group form before turning to a structural understanding of the business group as emergent.

Function–form efficiency: the Leff hypothesis As the literature on function–form efficiency is well developed in economics, it is instructive to summarize the polar views on this question. One side emphasizes the capture of private benefits by dominant owners. The other side sees the business group as providing an entrepreneurial response to the institutional deficiencies of the business environment. In either case, this argument is primarily about the functional efficiency of different forms.

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Morck, Wolfenzon, and Yeung (2005) summarize the arguments for the first side of this debate by starting with the position that business groups are most often pyramidal devices designed to extract cash from minority shareholders—who nevertheless volunteer to buy the equity or to make the loan. The size of business groups also leads to political power. This literature focuses heavily on the pyramid structure, whereby a root firm owns a controlling percentage in tier one firms, which own in turn a controlling percentage in tier two firms, and so on. This structure permits the root firm to extract cash or services (e.g., corporate jets) from lower tier firms, though ownership control is progressively weaker at each tier. A pyramid in which each focal firm at each tier owns 50 percent of the firms at the lower tier means that control of the root firm falls at a rate of αt where α is the percentage of ownership and t is the index for the tier level. Thus, if a root firm diverts $1 million from a tier firm to private benefits for owners (called “tunneling” in the literature), these owners only incur the cost of less than $80,000 (since αt < 0.08). This focus on the potential abuse by the pyramid form was observed by Berle and Means for the United States in the 1930s.4 This literature holds the following then: the business group form is a pyramid; its function is to divert private benefits to the ultimate owners. Predictably, the counter-position is that these groups are efficient, because they solve market and institutional failures, or they possess specialized managerial capabilities. This position can be called the “Leff Hypothesis” in deference to Nathaniel Leff ’s (1978) seminal paper that argued that groups consist of entrepreneurial and managerial capabilities to redress the institutional market failures in developing countries that impede entrepreneurship. “The institution of the group is thus,” he concludes, “an intrafirm mechanism for dealing with deficiencies in the markets for primary factors, risk, and intermediate products in the developing countries” (Leff 1978: 667). This hypothesis that business groups compensate for market and institutional failures is wider than Leff stated, and applies generally to the argument that corporate form compensates for failures in markets and institutions. When empirical questions are complicated, a good strategy is to look for simpler cases. The above contradictory explanations for the existence of business groups overlaps with the empirical debate in the field of strategy concerning the question of whether diversification, even for the unitary firm, adds value. The nomenclature for this question is whether there is a diversification discount. Consider first the statistical studies, largely based on US data, which ask if corporate headquarters have any effect. These studies show that the variance of profitability is determined largely by factors specific to an individual business or to the industry, with evidence indicating that headquarters account only for a modest portion of the variance (see, e.g., Rumelt 1991). Consider next if the mean effect of this contribution to profit variability is positive or not, that is, is there a diversification discount. Most studies find that diversification on average decreases the value of the firm. However, empirical studies on firms located outside the United States do not find this discount, and often find a premium

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(e.g., Lin and Servaes 1999). Context matters to the efficiency of the function–form relationship. The relevance of these studies to business groups should be self-evident—does it help to be a member of a large diversified business group? It is not surprising that many studies test if business groups earn a higher return to capital.5 Take, for example, the study of Khanna and Rivkin (2001), which found that for 14 countries, six showed evidence that business groups add value, three that the value was negative, and five evidenced no difference in added value. If we view each country as an experimental subject and the treatment is business groups, then we have an experiment of size 14, with only 42 percent of the subjects showing a positive benefit. On this basis, the null of no relationship is not rejected. There are surely moderating institutional factors, but no study has been able to identify this relationship. While many within-country studies show that belonging to a business group helps relative to independent firms in the same country (e.g., Keister 1997, for China), many studies do not.6 Less concerned by the function–form debate, the sociology literature ventures from the institutional perspective that countries are each led by particular logics and these logics are templates for the organization of business enterprises. This thesis has been usefully applied to the national design of railroad policy (Dobbin 1994) that differed in France, the UK, and the United States. Hamilton and Biggart (1988) developed a similar argument in pronouncing that capitalism in Korea, Taiwan, and Japan followed different institutional logics. They conclude in noting that “organizational structure is situationally determined, and, therefore, the most appropriate form of analysis is one that taps the historical dimension” (Hamilton and Biggart 1988: S87). In less careful hands than those of Hamilton and Biggart, this otherwise appealing argument has the tendency to slip toward a “vive la difference” claim, whereby countries are unique, following their own logics, and must be understood sui generis. The sociological literature is full of examples along these lines. This extreme institutional methodology has the important benefit of fostering deep country case knowledge. Still, the comparative analysis has rather modest goals, namely to assign countries to different (unique?) logics without isolating causal statements or providing analysis of micro-mechanisms. A classic example is the Reinhard Bendix (1956) methodological legacy of using two-by-two comparisons (that is, two causes that generate four causal or descriptive outcomes) of four countries; with two causes and four countries chosen to maximize variance, the design is perfectly saturated with no error. This design makes sense in the case of stratified randomized experiments; it is a purely descriptive model when four countries are assigned a priori to exactly four possible outcomes. Arguing from outcome to the selection of cause is a weak methodology to support the conclusion that (two) institutional factors unique to each country’s logic determine the existence of business groups. Charles Ragin (1987) proposed a qualitative comparative analysis in order to isolate feasible causal configurations to which countries can be assigned, thus allowing for an informed reduction of country cases to categories that are causally meaningful; these categories are more than just descriptive boxes.

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Structural signatures and the emergence of big diversified firms It is not surprising, as discussed above, that the business group literature is marked by profound disagreements. It is probably a good idea to step back and try a different avenue of attack. An alternative approach focuses less on the function–form comparison across contexts (i.e., countries) or on broad macro-institutional comparisons. Instead, this alternative focuses on the emergent processes by which large and diversified firms are produced. History matters to this analysis insofar as values and opportunity structures preserve the past. Feedback from the environment provides current information to local actors. As is characteristic of this kind of approach, the goal is to isolate viable mechanisms that relate micro-motives and macrostructures. There is, though, a more intriguing theoretical edge to this analysis in the following sense. Random behaviors of local actors do not aggregate to random macro-outcomes. There is invariably more structure and order in the macro-organization than suggested simply by observing random micro-behaviors. Random micro-behaviors are a baseline benchmark. Micro-motives such as business group relationships, which are often described as “cronyism,” are a type of “friend-of-friends” dynamic which leads to triangular closure and clustering; when this is coupled with male gender preference, the structural outcome is a “boys’ club.” These patterns are structural signatures in data that can usefully distinguish between bad and good candidates for mechanisms that give rise to business groups. These signatures can be thought of as “patterns of relatedness and coordination” that are “microsocial” (Knorr Cetina and Bruegger 2002: 907); patterns of relatedness and coordination are an excellent description of business groups, with the proviso that, to see these patterns, we need to look at the macro-aggregation to detect the regularity of these microsocial structures. Let’s focus on two structural signatures, which are almost law-like in their regularity, in regard to the distribution of firm sizes and diversification. Both of these are useful baseline models for understanding the dynamics that lead to the emergence of big diversified organizational entities labeled business groups. Why are baseline models useful? If the empirical data across different contexts (e.g., countries) reveal similar patterns, the suggestion is that there is a common process that generates the distribution. For institutional sociologists, this finding is a challenging result, for it says, “don’t tell me the institutional differences and I will still predict the outcome.” However, this challenge can provoke insightful responses, which we develop later. Business groups are characterized by at least two properties: they are collectively large—often with big individual companies—and they are diversified; it is undesirable to have competing companies within the same group. As one of the great early students of business groups noted, business groups are often the entrepreneurs in emerging markets and they expand in areas that suit their skills and advantages (Leff 1978). Since capital markets are weak, business groups frequently populate capital-intensive industries, such as transportation, heavy industries, and, of course, finance.

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The size distribution of firms Any student of business organizations comes to appreciate quickly that no matter the initial sizes of new firms, firms tend to quickly become power-law distributed. There are notable exceptions, for example Italy has not generated large firms to populate the extreme value tails that otherwise might be expected. However, the finding of a powerlaw distribution of sizes is nevertheless so common that an appropriate criticism is to accept this property as being as law-like as we are able to get in social science but then to ask, why is there is such variety in the exponent? This is prosaically asking why a few large firms tend to dominate industrial sectors and national economies—a precondition to the properties of business groups that make them important objects of study. Of course, the size distributions of countries differ in scale. There is a fractal quality to power laws due to their scale-free property. By scale free, it is meant that a scalar (lambda) increase in size proportionally scales the probability, such that P(λx) = K(λx)α = λαKxα = λαP(x), where K is a constant, X is the size of the entity, and α governs the skewness of the distribution. Consequently, the ratio of the scaled distribution to the original distribution is simply P(λx) / P(x) = λα. This relationship means that the shape of the distribution is not affected by the level of the sizes; large and small countries will differ in scale but not in the shape of the distribution.7 In other words, the global size distribution of all firms in the world can be power-law distributed, as can the sizes of firms within countries, within national sectors, and within business groups (if the population of components is sufficiently large). This repetition of a power-law distribution at every level of the hierarchy (global, national, sectoral, firm) is consistent with a fractal organization and it implies far more order than might otherwise be expected by purely institutional accounts of size distributions.

The relation of a firm’s size and the variance of its growth rate In addition to their size, a second property of horizontal business groups is their diversification. Again, to keep things simple, we start by considering simply the relation of diversification to size distributions. From an economic perspective, the motivations for businesses, to paraphrase our above quote from Granovetter, to persist in long-term relations is that there is a gain to this relationship. This gain may be due to shared resources, markets, or bargaining power via the state. If businesses persist in being bounded to each other but the gains to this persistence vary by firm, what should be the signature in the macrostructure? This structural signature is found in a relatively obscure pattern whereby the variance of growth of firm sizes is also power-law distributed (Stanley et al. 1998), such that σ2(σ/y) = Kyr with the exponent estimated to be in the vicinity of -0.15. Borrowing from statistical physics, Stanley et al. propose that mild “firm level” correlation among business units can explain this exponent, for which they find some evidence.8

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These results on the power-law distribution of firm sizes and the variance of growth of firms point to persistent binds among interdependent entities through formal ways, namely the unitary diversified firm. These statistical results suggest the existence of heterogeneous capabilities among firms who differ in their abilities to manage their internal diversification. We have noted above the studies in strategic management that indicate that corporate headquarters matter (though modestly) to the variance in profitability; that there is a diversification discount in the United States; and that some countries show a diversification premium. However, we have not said anything about whether it matters what firms diversify into. Teece et al. (1994) refer to the correspondence between the industry interrelation and the business portfolio of a firm as defining its “coherence.” This definition of coherence is a strong form of technological epiphenomenalism. This leads to the following research strategy. If successful firms benefit from combining businesses with overlapping technologies or markets, then the following pattern should be true at the macrostructural level: pairs of industries that frequently appear in the business portfolios of firms indicate that these industries are technologically or market related. Firms whose diversification portfolios reflect this relatedness are coherent. To test this proposition, Teece et al. analyze the industrial activities of a large sample of diversified firms to see if their portfolios “cohere.” The random baseline is to assume that every industry pair is equally likely to be conditioned on the marginal, that is, conditioned on the overall frequency of firms active in that industry. Coherence then is a type of Student-t statistic indicating the statistical departure from this random expectation. The authors subsequently construct a measure of coherence for each diversified firm. This measure represents the extent to which a firm is diversified into industries that mimic the interindustry correlations. This study is a nice example of using macrostructural data to investigate micro-behaviors and to apply a random baseline to generate the measure of the nonrandom departures. However, this top-down approach inverts our bottom-up proposal and comes at the cost of a circularity derived from their assumption of a survival bias—that the industry coherence is the aggregation of firm-level choices. A naïve test is simply to ask if the same patterns of industry coherence are observed in other countries. Kogut, Walker, and Anand (2002) provided this test, rejecting a common coherence across countries. Coherence, to the extent that it exists, is not determined by technologies, but most likely by market and institutional factors as well. If cross-national coherence varies for the diversified corporation under a unitary ownership structure, it is surely unlikely to hold for the business group either.

Counting business groups Having confronted two statistical regularities with empirical data regarding the unitary firm, let’s turn now to the more prosaic task of identifying business groups. Harry Strachan observed in his study of business groups in Nicaragua that, in response to the

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question “to what business group do you belong?” a businessman might say none, or name a group, but the question would not evoke the response of asking what a group is (Strachan 1976: 26–9; cited in Granovetter 1995: 99). In fact, many directories of business groups have been drawn up based on insider knowledge of the group structures. Another approach is focus on the ownership data published by investment houses, business press, or stock exchanges in reference to companies whose stock or debt is traded. Of course, pure private entities are not captured by these listings, thus Granovetter’s firms bounded by “informal ways” are excluded. Still, the advantage of this approach is to mine the data for groupings that do not rely upon judgment so much as statistical methods. Glattfelder and Battiston (2009) analyzed data on 48 countries using Bureau van Dijk’s ORBIS database. In all, the data consisted of 24,877 companies and 106,141 shareholders. The structure of an ownership-firm network is bipartite (sometimes called an affiliation network). Since the data include the percentage of the equity owned by the shareholder, they were able to construct a control index that identifies the ownership backbone of the global network. This backbone consists of the largest shareholders by their direct and indirect equity holdings. While the backbone analysis is helpful for identifying big shareholders, it does not directly count the number of business groups. Counting business groups is complicated by loops, since firms may have cross-holdings directly or indirectly via third parties. Since a pyramid is a root firm owning other firms, which may own other firms, one solution for counting pyramids is to identify the directed acyclic graphs (DAGs) in the networks. The procedure begins by removing the largest DAG, or pyramid, then turning to the next largest, until there are no DAGs left that meet our threshold criteria. If two root firms have cross-holdings or common investments, the largest DAG is first counted, then collapsed to a single node; then the second root is checked to see if it is a pyramid and, if so, is counted. This procedure was applied by Kogut et al. (2012). For the period around the year 2000, Chile was clearly the pyramidal champion, followed by Korea and Brazil. Denmark had many pyramids but they were relatively small. Nevertheless, these countries have more pyramids (uncorrected for network size) than other countries. As most studies show, pyramids are largely absent in the United States.

Local topologies and comparative analysis9 Counting the average branches to trees is a good first attempt at comparing the importance of business groups by country. A more ambitious program of research is to parse the institutional logics of micro-motives into clear rules. After all, a logic should be expressible by rules, or else why call it a logic?

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An emergent approach welds both together: it analyzes the correspondence of a country macrostructure and the micro-rules that could generate the structural signatures. An ideal answer to the question of what it means to be a country entails in my view an understanding of the micro-rules that guide the individual choice whether to own or to sell a firm or whether to be a member of a business group. If the way business groups are formally bound is through boards of directors, then the corresponding micro-question is what rules, or what logics, promote the appointment of directors. Multiple studies on directors show that the choice of a director is strongly conditioned on the social network, such as by homophily; in other words, “birds of a feather flock together”: men choose men, graduates of an elite school choose other graduates of the same university, and so on. Homophily is an excellent micro-rule candidate for explaining the sociological formation of business groups. Business groups are often associated with family, ethnic, and status affiliations. In any cross-section, the ties between the firms will reveal a tendency of triangular closure due to these affiliations. Triangle closure captures the social phenomena that “friends of friends are also friends.” By applying a statistical method called exponential random graph models (or ERGMs), we could estimate the coefficient to triangular closure in two countries called North and South. This estimation might, for sake of illustration, show that the coefficients to triangular closure differ by a factor of 2; everything else is the same. Then, by tuning this coefficient, it would be possible to grow the North from the South. Below, we develop further this idea of growing business groups. First, though, it might be useful simply to know if business groups are more common in one country than another. Earlier, we simply offered a count of the pyramids in the country normalized by the size of the network. Business groups, however, are broader than just pyramids. Moreover, a simple count does not reveal much about the micro-foundations. There is, however, a simpler way to post this question: Is the number of business groups in a country greater than would be randomly expected? If business groups can be detected by triangular closure, then is the number of triangles greater than would be expected if the ownership or social ties among firms were simply randomized? Maybe a given country has 20 business groups. Is this a lot for a country with N number of firms and K ownership ties between these firms? It is quite possible that a random graph consisting of N nodes (firms) and K edges (ties) will on average show the same triangular frequency. A random graph is the appropriate representation for the pure market economy and a baseline model: social ties should not matter. We will focus on one network statistic, clustering, as it captures well local differences, where local means the formation of neighborhoods and the rules by which neighbors are chosen. (Neighborhood has a technical graph definition: the nodes that are linked directly to any arbitrarily chosen node j belong to the neighborhood of j.) Clustering is an operationalization of Coleman’s definition of social capital, whereby a more connected neighborhood has the social properties of high trust as well as monitoring. Thus, a business group should be marked by clustering, indicating a high level of social capital and trust.

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Having chosen now the ideal type of a market economy as a random graph and defined clustering as the appropriate network statistic, we are prepared to analyze how a country differs from the random polar case. The measure we propose relies upon this proposition: the nodal-expected clustering coefficient for a random graph is the density of the graph. We exploit this property to measure how much a network differs from a typical random network as the difference between the empirical average clustering coefficient and the density for any given country. We call this difference “distance to random.” By applying this algorithm to data from over 20 countries, the findings showed that the ownership clustering found in Anglo-Saxon countries are relatively close to being random (Kogut et al. 2012). This approach can also be applied to board interlocks. Here, the observed clustering in countries is considerably different than their random graphs prediction. Boards indeed look clubby. A basic requirement for the comparative study of business groups should be evidence that their structural form is expressive of a social and cultural rule. The earlier section proposed counting business groups by looking for tree-like relationships in the ownership data; this section proposes that for many kinds of business groups, we should expect to see the social rules develop into relational patterns that reveal clustering. Some business groups, such as the vertical keiretsu in Japan, are better measured as (acyclic) trees; others, such as Chinese family enterprises, are best measured through clustering. This difference makes the larger point: it is by understanding the generative rules behind business groups that we will start to understand their sociological properties and origins.

Business groups and genealogical rules of culture This above illustration points to the utility of understanding the growth and prevalence of business groups across countries from the lens of an agent-based model (ABM). An ABM treats agents as pursuing particular strategies, which may be social or economic. A social rule might be to befriend friends of friends (to continue with the above example), or it could be economic in forming ties with economically powerful firms or people. Of course, social and economic motivations are often mixed together. The goal of an ABM is to explain the macrostructural patterns as generated by the behavior of rule-driven agents. Epstein (2007) has pithily summarized this goal in the following adage: if you didn’t grow it, you didn’t explain it. The astute observation is that the converse (if you grow it, you have explained it) is clearly not true since there may be, and often are, multiple models to grow a given topological structure. Still, the rule is useful as a deduction by elimination in order to disprove a causal claim. An ABM analysis can be useful to understand the sociological origins of business groups. By ABM type analysis, I mean that simply framing business groups as the

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product of a bottom-up generation from social rules can be useful. Here is the proposed framing. As noted above, the literature on business groups is contradictory. One camp to this debate claims that pyramidal groups violate good governance and permit powerful people, often families, to reap benefits to the economic detriment of the underlying businesses. As an example, here is a quote from a review article by Morck, Wolfenzon, and Yeung (2005: 55), published in the Journal of Economic Literature: In many countries, large pyramidal groups effectively entrust the corporate governance of substantial parts of their corporate sectors to a few extremely wealthy families. This can potentially magnify the poor governance of a few family patriarchs into inefficient economy-wide capital allocation, reduced investment in innovation, and retarded economic growth. Moreover, to preserve the status quo, these elite families sometimes appear able to influence public policies so as to curtail private property rights development, capital market development and economic openness. We dub this situation economic entrenchment. We argue that much existing work points to economic entrenchment as a significant issue in many countries.

The second camp in this debate argues for the capacity of groups to compensate for institutional weaknesses and to outperform alternative organizational forms. Since good data are notoriously difficult to acquire, neither camp has declared victory. A generative analytical approach does not resolve the above debate, but shifts attention to explaining the interaction of the rules by which such groups, especially familyowned, evolve. In the relation of social rules to structure—such as business groups—the study by Bertrand et al. (2008) presents one of the rare analyses of the generative rules of social structure (intergenerational family firms) and their economic outcomes. In their statistical description of the population parameters to business groups, they note that sons inherit the ownership of the firms inside the family group. Based upon their statistical description, they proceed to show that the performance of the family groups worsens, the higher the number of sons and daughters involved when the founder dies. Thus, they have delineated a social rule regarding a male patrilineal pattern and, from this, determined the economic consequences. A full agent-based model would consider not only the demographics, but the social rules by which property is inherited and by which firms are bound together; agents would be assigned utility functions which would guide their choice of linkages across firms. For our purposes, it is instructive to consider just the implications of fecundity on the predicted size of business groups. In other words, we would like to derive the size distribution of business groups for Thai family businesses using statistics we can estimate from the data.10 These statistics are simply the average number of children (λ) and the probability that a child will create a subsidiary (α); for simplicity, we do not distinguish between sons and daughters, though, in fact, this probability is very much a function of the number of sons. A lineage is a DAG, which is a tree that has a root parent from which branches a generation, which then branches into a second generation, and so on. We begin by generating the tree

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starting from the root (founder). To create the second generation, we choose the number of children randomly by using a Poisson distribution with a specified λ. We assume that the decision to start a new business is only made if the father owns a business; otherwise the entrepreneurial line dies. We repeat the process for each child to generate the third generation. This process goes on until a specified number of generations is reached. We can then count the size of the business group by the number of affiliated businesses. Figure 4.1 shows the prediction for the average size of Thai groups by running the simulation several thousands of times; for each instance, we calculate the size of the business tree and calculate the average given the size of the family. The λ value (6.8) used is the one found in empirical data; these are big families. We compared the simulation results with the numerical solution and they show that they are in close agreement. The interesting observation is that for low probabilities of alpha (probability of a child starting a business), there is little difference between the predicted size of the groups. Even in this deterministic model, the key factor driving the size of the pyramid is the entrepreneurial probability. We have assumed that this alpha is fixed across generations. The above exercise illustrates the idea of genealogy in the very strict sense: the lineage dynamics of the family generates the structure of the business group. Stark and Vedres (2010) propose a related idea in the context of the “intercohesion” within business groups in Hungary whose boundaries change through a process of splintering and folding. Business groups are defined through the sharing of directors on their boards (this is called “folding”); the more directors shared, the more cohesion. Stark and Vedres (2010) analyze the lineage of these groups by treating the member firms as genes in a sequence. When these sequences are unstable the dynamics are nevertheless coherent and preserve a genetic heritage through recombination.

Business size/family size

1.0 0.8 0.6 0.4

λ = 6.8 gen = 1 gen = 2 gen = 3 gen = 4 gen = 5 gen = 10 gen = 15 gen = 25 gen = 50 gen = 100

0.2 0.0 0.0

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0.4

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figure 4.1 Effects of Entrepreneurial Ability of a Family and the Growth of the Business Group (from Kogut 2012).

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Sociology has an important contribution to make here. The Stark and Vedres analysis returns to the primary interest of Leff: business groups are a form of entrepreneurship. In other words, this poorly explained phenomenon of entrepreneurship probably owes a lot to familial cultures. In a wider welfare analysis, this dynamic of the innovation function can compensate well for the inefficiency of the form. It is not obvious that if patrilineal practices were to be removed in the Thai case, the social incentives for innovation would be the same. In a universe of second bests, the optimal policy intervention is often not the one that appears to move the current state “toward” the best of a market, with no family firms but just atomistic competitors. Economics has a hard time separating this ideal type from an ideological predilection for competitive market solutions, even when such solutions are rarely available. A sociology of finance would have much to contribute to the understanding of development by analyzing the rules of lineage (be they familial or corporate) in financing entrepreneurship and innovation.

The state and business groups: linear versus exponential time The sociological literature on business groups has commented extensively on the role of the state in promoting business groups (see the excellent discussion in Granovetter 2005.) When the state is viewed as a static unitary actor, an agent-based model for understanding the emergence of the business group is problematic. However, in conditions when neither the state nor business is unitary, an agent approach can provide useful insights. Consider two related applications. The first is the observation from Gershenkron’s famous thesis of late industrialization that the state can speed up development, especially through an alliance with capital. Amsden (1989) adopts this idea when analyzing the role of the state in post-World War II Korea. Because of the Japanese occupation, Korea had an experienced factory workforce but a repressed indigenous entrepreneurial class. Buoyed in part by American foreign aid, the regime of Syngman Rhee created a state of patronage while relying on the business groups, or chaebols, that dated to, and sometimes before, Japanese occupation. The military coup of 1960 did not so much change the role of the state as switch allegiance to a new class of entrepreneurs who founded business groups under the tutelage of the state and its state-owned financial institutions. For Amsden, this political change transformed the modality of the economy from rent-seeking to investing (Amsden 1989: 20). Under this new regime, the state facilitated the financing of, and manipulated prices to steer, investment; the chaebols proved to have a strong capacity for learning and absorbing foreign technology given their already well-educated and hardworking workforce. Granovetter (2005) notes that the social distance between the military state and business eroded, particularly through intermarriages. Like the concept of network “folding” discussed by Stark and Vedres, Granovetter stresses the “network overlaps” between

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business, society, and the state. This similarity points to the potential of seeing these overlaps as the outcome of a genealogical sequence, as Stark and Vedres applied to Hungarian governance ties. But for many countries, the principal form of governance is not the board of directors but the family. Indeed, the chaebols have been family-owned businesses and an important element in the expansion of the businesses has been the number of sons; not uncommonly, the details of familial rivalries are sometimes subjects in the press. Thus, the genealogical dynamics driven by fecundity and by social class are pertinent to an analysis of the sustainability of the Korean chaebol as a familyowned business group. The second observation couples the earlier discussion of the tendency of firm sizes to be distributed by a power law and the time it takes a state to consolidate. The usual narrative for the Korean case is that the state fostered the business sector. Without questioning this particular history, consider instead the relations of the state and business in Russia after the fall of communism. The decision to distribute ownership through mass privatization led to a strikingly rapid rise of powerful financial industrial groups. By the late 1990s, only six years after the first wave of privatization, the size distribution of Russian banks showed the usual power-law distribution of firm sizes (Kogut 2012)— large and powerful financial actors had quickly emerged. Meanwhile, the central government faced substantial problems in the collection of tax revenues and curbing the rampant corruption not only in the provinces, but in Moscow. One way to understand the Russian case is to note that the power-law distribution suggests that the banks were growing in exponential time, but the state revenues were only growing linearly; in the 1990s, this growth was negative (Treisman 1999). The Russian government faced an essential divergence, by which their inability to consolidate their powers to tax was increasingly dominated by the growing fortunes of oligarchs who had seized ownership of vast swaths of Russia’s natural resources. The first decade of the twenty-first century in Russia has seen a struggle between a weak but dangerous central state and powerful oligarchs, with signs of a new political alignment. A simple point is suggested by the comparison of the Korean and Russian cases: it matters to the development of business groups and the state which one consolidates first. The development plan of the business group is not always the product of the state; sometimes the state is the hostage. An insightful way to understand how time matters to this struggle is to meter the generation of large firms against the consolidation of the state and its ability to tax and to spend.

Business groups and the moral economy One of the most intriguing dimensions by which Granovetter proposed to study business groups is the “extent of the moral economy.” “Groups may but need not,” he observed, “be coherent social systems in which participants have a strong sense of moral obligation to other members and a well-defined conception of what is proper

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behavior. Such conceptions are almost invariably accompanied by a strong sense of group identity, which confers a normative and extraeconomic meaning on economic action” (Granovetter 2005: 433). The notion of a moral economy dovetails with organizational theories that treat firms not simply as a “nexus of contracts” but as social communities in which members hold identities and common values. Surely, there are many business groups fabled for their public and philanthropic interests, such as the Tata business group in India. The empirical questions are twofold: Do business groups on average evoke more of a sense of moral economy than non-group firms, and does this economy indeed extend across the independent firms? The first question returns to the ambiguous results on the functional superiority of the business group form; the second is related to the notion of “relatedness” or “shared resources” that has occupied the attention of the economic and business literatures. A moral economy may have another kind of utility, though, namely in attracting and selecting a high-quality workforce. In many countries, the firms that constitute the business groups are among the most reputable enterprises in a country. The precocious study by Sakakibara and Westney (1985), comparing the rankings by college graduates of prospective employers, indicated almost exclusively a preference for firms belonging to business groups. Similar results no doubt could be found for many other countries, with the caveat that globalization (much like colonization before it) provides competition for the best graduates.

Implications for the sociology of financial markets Business groups are large, consisting of diversified firms that are persistently bound. Seen as isolated phenomena in very distinct institutional environments, their dominance is often inexplicable. The trick suggested by this chapter is to step away from the cross-section and to study the longitudinal bottom-up emergence of business groups, thus coupling statistical models with historical context. This approach is similar to the argument used in the now-canonical study for the sociology of financial markets by MacKenzie and Millo, “Constructing a Market, Performing Theory: The Historical Sociology of a Financial Derivatives Exchange.” They note first that the Black-Scholes-Merton option pricing model, which assumes constant volatility as a model parameter, predicts that the implied volatility should be invariant to price levels of the stock or more exactly to stock price relative to the call price (for a European call option). However, subsequent to the Black Monday crash of 1987, empirical studies found that this relation was U-shaped, poetically named “a smile.” This smile has remained a feature in the empirical data. MacKenzie and Millo proposed a narrative that iterated between particular macro-patterns in trading (e.g., the signature of

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“smiles”) and the micro-behaviors of traders (e.g., they followed the same script, they responded similarly to sudden downward jumps in prices). This methodological approach was applied in this chapter to propose that business groups are a type of signature. The interplay between law-like properties of firm-size distributions and the micro-motives of economic agents lead to the emergence of business groups. An approach that uses baseline models that describe the macro-patterns, such as the presence or absence of power-law distributions, is useful to bounding the number of candidates for micro-behavioral explanations. In the end, the analysis of business groups as emergent may reveal new, if not greater, commonalities across countries than are currently available through comparative institutional analysis.

Notes 1. I would like to thank Jordi Colomer for his considerable contributions to the analysis of business groups cited in this chapter, Karin Knorr Cetina and Alex Preda for their encouragement and patience, and Aharon Cohen Mohliver for his assistance and comments. 2. Since this essay is not a literature review, it may be useful to consult the excellent perspectives that already exist, particularly, Granovetter (2005); Khanna and Yafeh (2007); Morck, Wolfenzon, and Yeung (2005); and Brookfield et al. (2012). 3. Of the many excellent studies, see Gerlach (1992) on the horizontal keiretsu; Nishiguchi (1994) on the vertical chains; Hamilton and Biggart (1988) offer an early assessment of Japanese business groups along these lines. 4. The pyramid was already rare in the United States by the 1930s. 5. The best review of this literature is given in Khanna and Yafeh (2007). 6. Chang (2003) provides one of the best analyses of the internal advantages of business groups, as well as the ways that value is destroyed through excessive diversification. 7. Kogut (1998) removed the mean (level) effect from the sizes of the largest firms for several countries by a z-score transformation and then correlated the sector fixed effects by country, finding substantial correlations. 8. Sutton (2002) presents a model in which the business units are independent and yet a power law is found. 9. This and the next sections draw heavily from the chapters by Kogut et al. (2012) and Kogut (2012). 10. I would like to thank Krislert Samphantharak for providing the data and Jordi Colomer for the design and implementation of the simulation.

References Bendix, R. (1956). Work and Authority in Industry: Ideologies of Management in the Course of Industrialization New York: Wiley and Sons. Brookfield, J., Chang, S.-J., Dori, I., Ellis, S., Lazzarini, S. G., Siegel, J., and von Bernath Bardina, J. P. (2012). “The Small Worlds of Business Groups: Liberalization and Network Dynamics,” in B. Kogut (ed.), The Small World of Corporate Governance. Cambridge, MA: MIT Press.

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Chang, S.-J. (2003). The Rise and Fall of Chaebols: Financial Crisis and Transformation of Korean Business Groups. Cambridge: Cambridge University Press. Dobbin, F. (1994). Forging Industrial Policy. Princeton, NJ: Princeton University Press. Epstein, J. (2006). Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton, NJ: Princeton University Press. Gerlach, M. (1992). The Alliance Structure of Japanese Business. Berkeley and Los Angeles: University of California Press. Glattfelder, J. and Battiston, S. (2009). “Backbone of Complex Networks of Corporations: The Flow of Control.” Physical Review E, 80/3: 12. Granovetter, M. (1995). “Coase Revisited: Business Groups in the Modern Economy.” Industrial and Corporate Change, 4: 93–130. ——— (2005). “Business Groups and Social Organization,” in N. Smelser and R. Swedberg (eds.), Handbook of Economic Sociology (2nd edn). Princeton, NJ: Princeton University Press and Russell Sage Foundation, 429–50. Hamilton, G. G. and Biggart, N. W. (1988). “Market, Culture and Authority: A Comparative Analysis of Management and Organization in the Far East.” American Journal of Sociology, 94: S52–S94. Keister, L. A. (1998). “Engineering Growth: Business Group Structure and Firm Performance in China’s Transition Economy.” American Journal of Sociology, 104/2: 404–40. Khanna, T. and Rivkin, J. (2001). “Estimating the Performance Effects of Business Groups in Emerging Markets.” Strategic Management Journal, 22/1: 45–74. ——— and Yafeh, Y. (2007). “Business Groups in Emerging Markets: Paragons or Parasites?” Journal of Economic Literature, 45: 331–72. Knorr Cetina, K. and Bruegger, U. (2002a). “Global Microstructures: The Virtual Societies of Financial Markets.” American Journal of Sociology, 107: 905–51. Kogut, B. (1998). “Evolution of the Large Firm in France: France in Comparative Perspective.” Entreprises et Histoire, 19: 113–51. ——— (2012). “Epilogue: The Generative Analytics of Corporate Governance,” in B. Kogut (ed.), The Small World of Corporate Governance. Cambridge, MA: MIT Press. ———, Walker, G., and Anand, J. (2002). “Agencies and Institutions: Organizational Form and National Divergences in Diversification Behavior.” Organization Science, 13: 162–78. Kogut, B., Colomer, J., Belinky, M., and Hamadi, M. (2012a). “Generating Rules and the Social Science of Governance,” in B. Kogut (ed.), The Small World of Corporate Governance. Cambridge, MA: MIT Press. ———, Colomer, J., et al. (2012b). “Is there a Global Small World of Owners and Directors?” in B. Kogut (ed.), The Small World of Corporate Governance. Cambridge, MA: MIT Press. Lawrence, R. (1993). “Japan’s Different Trade Regime: An Analysis with Particular Reference to Keiretsu.” The Journal of Economic Perspectives, 7: 3–19. Leff, N. (1978). “Industrial Organization and Entrepreneurship in the Developing Countries: The Economic Groups.” Economic Development and Cultural Change, 26/4: 661–75. Lins, K. and Servaes, H. (1999). “International Evidence on the Value of Corporate Diversification.” The Journal of Finance, 54: 2215–39. MacKenzie, D. and Millo, Y. (2003). “Constructing a Market, Performing Theory: The Historical Sociology of a Financial Derivatives Exchange.” American Journal of Sociology, 109/1: 107–45. Morck, R., Wolfenzon, D., and Yeung, B. (2005). “Corporate Governance, Economic Entrenchment, and Growth.” Journal of Economic Literature, 43: 655–720.

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Nishiguchi, T. (1994). Strategic Industrial Sourcing: The Japanese Advantage. Oxford: Oxford University Press. Ragin, C. (1987). The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Berkeley: University of California Press. Rumelt, R. (1991). “How Much Does Industry Matter?” Strategic Management Journal, 12: 167–85. Sakakibara, K. and Westney, E. (1985). “Comparative Study of the Training, Careers and Organization of Engineers in the Computer Industry in the United States and Japan.” Hitotsubashi Journal of Commerce and Management (一橋大学), 12: 1–20. Stanley, M. R., Nunes Amaral, L. A., Buldyrev, S. V., Harlin, S., Leschorn, H., Maass, P., Salinger, M. A., and Stanley, H. E. (1996). “Scaling Behaviour in the Growth of Companies.” Nature, February 29: 804–6. Strachan, H. (1976). Family and Other Business Groups in Economic Development: The Case of Nicaragua. New York: Praeger. Sutton, J. (2002). “The Variance of Firm Growth Rates: The ‘Scaling’ Puzzle.” Physica A, 312: 577–90. Teece, D., Rumelt, R., Dosi, G., and Winter, S. (1994). “Understanding Corporate Coherence: Theory and Evidence.” Journal of Economic Behavior and Organization, 23: 1–30. Treisman, D. (1999). “Russia’s Tax Crisis: Explaining Falling Revenues in a Transitional Economy.” Economics & Politics, 11/2: 145–69.

chapter 5

cen tr a l ba n k i ng a n d the tr iumph of tech n ica l r ationa lit y m itchel y. a bolafia

More than any other financial institution, the central bank stands for technical rationality, the application of scientific thought to the solution of administrative problems.1 No other financial institution so fully frames its major policy decisions in terms of economic models. No other financial institution places these decisions in the hands of a committee of economists who meet on schedule to analyze the latest data and fine-tune policy. None employs such large research departments, even publishing their own prestigious journals.2 And in no other financial institution are the governors of that institution portrayed by the media as technical wizards—masters of an arcane knowledge that produces a public good. All of this suggests that central banking has become technically rational, thereby eliminating the social and political elements historically associated with controlling the supply of money and credit in a nation. This chapter questions how closely central banking has approached this ideal type. It sees instead a more idiosyncratic application of ideas based in a technical discourse. Elements of custom, compromise, and pragmatism mix with expert judgment in a social process of negotiation. The existence of confusion and uncertainty are strategically obscured from public view to maintain the more mythic view of technical rationality. The “scientization” of central banks has allowed them to “gain legitimacy and authority basing their views on, and applying, the language of science” (Marcussen 2009). It has allowed their analyses to become objectified and more readily reproduced by their target audience in the marketplace. But it has not allowed the control of the money supply to become “scientifically” managed. Rather, the aura of technical rationality that surrounds central banking disguises the limits to rationality and conceals the social character of its policy choices. The process of rationality identified in this chapter reveals a tension between central banks’ technical discourse and their employment of experience-based expert judgment. The

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result of this tension is an interpretive process for making sense of and giving sense to policy choices. This process is marked by the use of interpretive techniques that explain and justify these choices. These efforts include rationalizing techniques to justify expert judgments, and signaling techniques to shape the meaning of these judgments for public consumption. These techniques are tools in the construction of a consensus narrative that central bankers use to legitimate and objectify their claim to technical rationality. They reflect the fact that central banking is not just an economic function, but a political one. Nevertheless, this chapter accepts the premise that central banks, in this case the US Federal Reserve (the Fed), stand for a logic of action based in technical rationality. My concern is not to impugn the Fed’s intended rationality, but to explore what this rationality looks like in practice. I use verbatim transcripts of closed policy meetings to illustrate the Fed’s own form of technical rationality. Transcripts of meetings of the Federal Open Market Committee (FOMC), the Federal Reserve’s most important policymaking group, are ideal for this purpose. They provide real-time policy negotiations that the members believed at the time to be secret. Ten transcripts (485 pages) from November 1978 to October 1979 were analyzed. The transcripts were only released later as the result of a Freedom of Information Act suit. Even members of the FOMC had been unaware of the existence of the transcripts. The FOMC meets every six weeks for one or two days to interpret current conditions and set monetary policy for the coming period. The Committee has 12 voting members. Seven are members of the Board of Governors of the Federal Reserve, appointed by the President of the United States and confirmed by the Senate for 14-year terms. The other five voting members are presidents of one of the 12 regional reserve banks scattered around the United States in major cities, and are elected by bankers from their home regions. The presidents of all 12 regional reserve banks attend the meetings and rotate onto the Committee as voting members for terms of one year.

Historical context: changing modes of control The Federal Reserve, as a central bank, is responsible for controlling the supply of money and credit in the United States. The goals of this control are the legislatively mandated pursuit of price stability and economic growth. The nature of the control of the money supply in the United States has changed over the course of its history. This change has generally been in the direction of increased government control over the market for money, but it has not been without conflict. Farmers, merchants, bankers, and political parties representing their interests have contested the appropriate means and degree of control. Class, occupational, and region-based conflict preceded the bureaucratic rationalization of the twentieth century. The conflict over control of monetary policy can be divided into three stages: market-based control, bureaucratic control, and

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technocratic control. Each form of control is accompanied by its own politics: marketbased control by class politics, bureaucratic control by intersectoral politics, and technocratic control by organizational politics.

Market-based control The Constitution of the United States (1787) gave the Federal government the power to “coin money and regulate the value thereof.” To the Founders this meant that the value of currency in the United States would be defined as a certain amount of precious metal, gold or silver. Such legal tender could be used to pay off all obligations. This system was considered self-regulating in that the supply of currency in the economy would not grow without an increase in the supply of precious metal. As such, the Constitution contemplated no other regulatory device. But the Constitution was better designed to maintain political stability than economic stability, and economic interests were rarely content to rely solely on the benefits of self-regulation. The monetary history of the nineteenth century is one of severe dislocation wrought by the bank panics of the 1830s and 1870s. Political conflict over how the currency should be valued was nearly continuous (Friedman and Schwartz 1963; Timberlake 1993). Farmers in the south and west of the country fought to expand the definition of which metals could be exchanged, while merchants and bankers in the east fought for the stability and predictability of “sound money.” The Federal Reserve has its direct roots in the Panic of 1893 and the resulting economic crisis. In the wake of this panic and years of economic instability, an alliance of reform-minded bankers, businessmen, and economists called for an “elastic currency” that could be mobilized in economic crisis. This idea, when married to the idea of “sound money” based on the gold standard, was critical to the birth of central banking in the United States (Livingston 1986).

Bureaucratic control The Panic of 1907, in which J. P. Morgan famously tried to supply the urgently needed monetary liquidity, provided the critical incentive needed for the creation of a central bank. In the final legislation, enacted in 1913, a system of eight to 12 regional reserve banks was to be created and run by the regional bankers, overseen by a Board in Washington. Although this degree of banker control was to erode over the course of the twentieth century, the long efforts of the banking community paid off for them in the creation of a central bank that could provide for an elastic currency that created enhanced financial stability. In its early years, the Board in Washington was weak and the regional reserve banks, run by the private bankers, took the lead in controlling the Federal Reserve System. The efficacy of the System, as well as the distribution of power between the Board and the 12 reserve banks, was somewhat ambiguous. On the one hand, Congress expected the

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Federal Reserve to be an adjunct to the self-regulating gold standard. On the other, it expected it to intervene in short-term seasonal disruptions when currency was needed. From the beginning, the New York Reserve Bank was more powerful and important than the other 11 regional banks and the Board in Washington. But the retirement of Benjamin Strong as Governor of the New York Bank in 1928 left a leadership vacuum (Friedman and Schwartz 1963; Meltzer 2003). During the numerous bank failures of the early 1930s, the Fed remained passive. Friedman and Schwartz (1963) famously blame this passivity on the leadership vacuum left by Strong in New York and the organizational ineptitude of the Board in Washington. More recently Allan Meltzer (2003) has argued that the ineptness can be explained by the widespread acceptance of a misguided economic discourse, the “real bills doctrine.” According to this ideology, the underlying cause of bank failures was loans made for speculative purposes, and the proper response was to purge the economic system of its excesses by letting banks fail. With this approach, depression was the inevitable consequence of speculative excess. As a result of the crisis and the Fed’s failure to mitigate it, Congress turned to reforming the Fed itself. The Banking Act of 1935 both changed the structure and broadened the power of the Fed.3 The ambiguities over the distribution of power in the Federal Reserve System were resolved in favor of the Board in Washington. The Federal Reserve Board was renamed the Board of Governors of the Federal Reserve System, and members were given higher salaries and longer terms. At the same time, the Secretary of the Treasury and the Comptroller of the Currency were removed from the Board in an effort to make it less political, “independent within the government.” All the pieces were in place to make the Fed an independent regulator of the money supply. But monetary policy had taken a back seat to fiscal policy in the New Deal, which focused on using government revenue to influence the economy. The Fed became the servant of policy set at the Treasury department.

Technocratic control The Federal Reserve chafed under Treasury control. By the early 1950s, many in Washington believed it was time for an effective monetary policy that did more than maintain a low price for government securities. The Treasury-Federal Reserve Accord in March 1951 gave the Fed its first chance to use the bureaucratic powers it had been given in the 1935 Banking Act. There was another, more subtle, shift occurring at this time. Congress affirmed the expectation of an activist Fed. Rather than being an adjunct of the self-regulating gold standard, which had been abandoned in 1933, the Fed was expected to adapt to cyclical conditions using its discretion to identify those conditions and create policy. The automatic discipline of the gold standard was to be replaced by what Allan Sproul, President of the Federal Reserve Bank of New York, referred to as “the discipline of competent and responsible men” (Timberlake 1993: 324). With this and the earlier structural reform of 1935, Congress laid the groundwork for the techno-

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cratic, relatively autonomous Fed of modern times. Competence as a central banker was increasingly associated with one’s knowledge of economic theory. In 1960 none of the seven governors were economists. In 1970 four of the seven were, and by 1980 all but one were economists. The major monetary event in the latter half of the twentieth century, one that continues to affect monetary policy today, is known as the Great Inflation. It is this event that provides the immediate macro-context for our close analysis of technical rationality at the Fed. Inflation refers to the rate of increase in the general price level of all goods and services. Inflation rose at the low average rate of 1.2 percent from 1952 to 1964. Between 1973 and 1981, the worst years of the inflation, it averaged 9.2 percent. At the time, many blamed the steep rise in oil prices, but Japan experienced the same oil shocks and only modest inflation. Others blamed the defense spending of the Vietnam War, but defense expenditures were actually lower as a percentage of gross national product than they were in the noninflationary 1950s. Today it is widely agreed that the inflation is a direct result of the monetary policies of the Federal Reserve. The money supply can only grow if the Fed lets it. Why then did the Fed adopt inflationary monetary policy? If it were in the agency’s or governors’ self-interest, then we would expect to have seen many more inflationary periods than we have since the birth of the Fed. Thomas Mayer (1998) argues it was another misguided discourse, popular among economists at the time, which influenced the Fed to adopt a more inflationary monetary policy. He found that economists were more concerned about unemployment and the stagnancy of the economy than they were about inflation. They believed that the economy was being dominated by what was called “cost-push inflation.” This was inflation caused by the wage-setting power of strong unions and the price-setting power of large corporations that passed along increased costs to maintain profits. These were considered structural causes beyond the reach of monetary policy. At the same time, policymakers also believed that they could obtain lower levels of unemployment by making more money available. Their bias toward lower levels of unemployment led them to increase the availability of money and credit, allowing inflation to grow. Mayer shows that a significant number of Board members, especially Chairman Arthur Burns, shared these views.

Stagflation: confusion and conflict at the Fed The 1970s were a period of confusion and conflict in economic policy at the Fed, and in the United States more broadly. Concern with the rising rate of inflation was accompanied by stagnating growth, high unemployment, and a severe recession in 1974–5. “Stagflation” was coined to describe the seemingly contradictory situation that was not predicted by the dominant Keynesian perspective. In 1977, the Joint Economic Committee

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of Congress issued a stinging report blaming the Fed for the depth of the recession and for obstructing recovery (Cowan 1977). Senator William Proxmire, in dissent from the Committee majority wrote, “Personally, I would be somewhat more humble than the report is in its relative certitude that there is an answer to the present problem of both excessively high unemployment and excessively high inflation. Economists may not know the answer to stagflation. Perhaps there is no answer” (Cowan 1977: 51). This confusion and conflict outside the Fed were matched by confusion and conflict inside it. The Fed’s efforts to control inflation were being blamed for the slow recovery from the recession, but as the decade continued inflation would not abate. The typical recovery after a recession did not occur. The economy continued to stagnate. By 1978–9, members of the FOMC, especially the Chairman of the Fed, G. William Miller, were openly admitting their confusion. mr. morris: Mr. Chairman, I don’t think we understand what is really going on in the economy. chairman miller: I’ll go along with that. mr. morris: I think it’s because we haven’t had enough experience judging the reaction of both the consumer and the investor to an economy with a high rate of inflation. chairman miller: That’s right; we haven’t had any experience. (FOMC 1978b: 11) mr. smoot. Yesterday in meeting with my own staff on this, I think I suffered an information overload. One of the alternatives that was presented to me was called “the pure ignorance theory.” That is, we don’t know how the economy got here and we don’t know where it’s going. And I must say that I felt embarrassingly comfortable with that view. Nevertheless— chairman miller. That is the most honest comment we’ve had today! (FOMC 1979b: 12)

In the midst of efforts to control inflation, some members began to fear the onset of another recession. Toward the end of 1978, private sector forecasters began predicting recession. The Committee’s focus on the rising inflation had kept them raising interest rates to tighten the money supply. Over the course of 1979 more members and regional bank staffs changed their forecasts. As a result, some members began to advocate for easing policy, that is, lowering interest rates. ms. teeters. Well, gentlemen, there’s a reason why the econometric models are predicting a recession. They’re based on history. And these are conditions in the past that have always produced a recession. Only twice, in the latter part of 1963 and in the latter half of 1966, did we ever have growth this low without having a recession. You are all sounding like the final quarter before the downturn, quite frankly. I think we should take more account of the commercial projections because the econometric models are summaries of past history and there’s good reason why they’ve turned this way. (FOMC 1978a: 12) mr. morris. If it’s our objective to avoid a recession, I think we have to move today; I don’t think we can wait for another month. One thing I’ve found around

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this table is that one can always make an impressive case for waiting for another month. But the evidence suggests to me that the time to move is now. I think the issue is whether we seriously are concerned about avoiding a recession or not. (FOMC 1979a: 21) mr. mcintosh. Our own view is that we are heading toward a recession later this year, and that view is shared by most other forecasts. We think the choice is between easing or staying put. Historically the Federal Reserve has had a tendency to overstay its policy at peaks and troughs, and it’s our fear that we’re about to repeat that performance. Therefore, we would argue in favor of a modest move in the direction of ease at this time in the interest of moderating the impact of the recession that we’re expecting. (FOMC 1979b: 17)

By the August and September 1979 meetings, as the members increasingly feared a recession, the confusion turned to conflict. Most members assumed that the economy had already entered a recession, but they were divided on whether to increase the supply of money (ease), as they normally would in a recession, or to tighten it to prevent the inflation from getting any further out of control. Many held that it was time to ease their policy. mr. rice. Mr. Chairman, probably not surprisingly, I would associate myself with the remarks made by Dave Eastburn, Nancy Teeters, Frank Morris, and Chuck Partee. I can therefore be very brief. I think it’s time to give more weight to what is happening in the real economy. The economy is clearly weakening; the staff analysis is very clear on this. It’s really very hard to see where the strength in the economy is that some people are worrying about. Most of the indicators seem to me to point toward weakness and further weakening in the economy. (FOMC 1979e: 28)

Other members felt just as strongly that inflation was the bigger problem and that easing would exacerbate that problem. In 1978, continued tightening was the expected policy, but over the course of 1979, this position became less clear and more conflicted. As the fall of 1979 approached, inflation and inflation psychology—that is, the fear of uncontrolled inflation—increasingly appeared to be getting out of hand. mr. mayo. . . . I, therefore, find it even more difficult than usual, as I guess Ernie mentioned as well, to try to interpret this for policy. Yet I think we have no alternative on the psychological side but to maintain our resolve in keeping restraint in place even at the chance that we’re going to be accused of causing any recession anyway at this point. I don’t say that in a defeatist attitude, but I think we still have to edge rates up just a little tighter partly because it’s expected of us in the whole aura here of worrying about what to do about inflation. We are the last bastion in the eyes of a great many people and I think it would be a mistake just to hold still right now. (FOMC 1978b: 15) mr. rankin. Mr. Chairman, our concern is oriented more toward the inflationary picture than the apparent increasing recessionary tendencies that we see. It seems to us that the markets both here and abroad will no doubt be watching carefully to see whether our recession fears will wear down our determination to do something

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about inflation. Our position here at the Richmond Bank is that we should continue to give a high priority to the inflation problems; even though the economy may be moving into a recession, we think it’s important to hold a tight rein on the aggregates at this time. (FOMC 1979c: 6) mr. timlen. I don’t think I will comment in depth on all the areas you touched on, but certainly foremost in my mind are the level of inflation, the strong growth in the aggregates, and the tentative position of the dollar in the foreign exchange markets. Sure, we have to be concerned about the prospect of a recession and high unemployment, but now is a time when psychology is a very important factor. I think the perception of the Federal Reserve’s resolve may be at issue and I believe it’s timely to give an indication of the direction in which we may be going. It’s my judgment that there should be a continuing gradual process of tightening and we should adjust to developments over time as they occur. (FOMC 1979d: 26)

The most consistent advocate for strong anti-inflationary policy was the Vice-chairman of the Committee, Paul Volcker. He wanted the FOMC to continue its tightening of the money supply. As the year progressed, he continued to state his belief that easing would be a mistake. In August of 1979, President Carter appointed Volcker to be Chairman of the Fed. His appointment was widely supported by the business community in the expectation that he would be more aggressive in dealing with inflation than the two previous chairmen, Arthur Burns and G. William Miller. At his first meeting as Chairman of the Fed in August 1979, Volcker was very explicit about his doubts about easing and his deep concern about inflation. vice chairman volcker. Well, I guess I come out slightly differently than you do, Mr. Chairman. I really have one concern when I look ahead at the 4-week period until we meet again, and that is that we adequately back up the program that has already been announced. I think it has had a good effect internationally. I think it has had a good effect domestically in terms of—“breaking” the inflationary psychology is much too strong a word but I think it has at least shaken thinking of the inevitability of more inflation anyway. And everybody is looking to see whether we will carry through. (FOMC 1978a: 22) vice chairman volcker. We may be one month closer to a recession than we were last month and I think we are late in tightening, but I still am of the view that some greater degree of restriction would be more appropriate than the reverse and more appropriate than standing still. (FOMC 1979b: 15–16) chairman volcker. When I look at the past year or two I am impressed myself by an intangible: the degree to which inflationary psychology has really changed. It’s not that we didn’t have it before, but I think people are acting on that expectation of continued high inflation much more firmly than they used to. That’s important to us because it does produce, potentially and actually, paradoxical reactions to policy. Put those two things together and I think we are in something of a box—a box that says that the ordinary response one expects to easing actions may not work, although there would be differences of judgment on that. They won’t work if they’re interpreted as inflationary; and much of the stimulus will come out in prices rather than activity. (FOMC 1979d: 20)

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October 1979: the Fed fights inflation Although the Fed had been raising interest rates gradually since mid-1977, it had little of the intended effect. The rate of inflation continued to rise. Despite unusually rapid growth in measures of the supply of money during the summer of 1979, this gradualism had continued at the September 18, 1979, meeting of the FOMC. The divided votes at that meeting signaled that Chairman Volcker might have trouble creating the anti-inflation policy that the banks and financial markets were expecting. As a result, inflationary expectations increased considerably. Prices in the silver, gold, and other commodities markets rose dramatically. This set the stage for the policy change introduced and voted on at the next meeting. The October 6, 1979, meeting of the FOMC was a rare unscheduled Saturday gathering of the members. Chairman Volcker called the meeting to discuss his proposal for a dramatic change in the operating procedure. In this proposal, the Fed would change the target of its major regulatory tool, open market operations, from a short-term interest rate known as the Fed funds rate, to a measure of the non-borrowed reserves held by banks. The change was intended to signal a more direct control over the supply of money and a heightened commitment to reduce inflation. Chairman Volcker was determined to see action taken at this meeting because of the agitated state of financial markets. In an unusual departure from custom, the chairman lobbied the governors for their support before the meeting (Greider 1987). The regional bank presidents only received a summary of the proposed change the day before the meeting. In most scheduled meetings, the chair moderates the policy discussion and identifies a consensus position. In this meeting Volcker defined two possible outcomes for the meeting almost from its beginning. chairman volcker. Now, when it comes to our action here, I think there are broadly two possibilities. One is taking measures of what might be thought of as the traditional type. That would include a discount rate move and so far as this Committee is concerned a significant increase in the federal funds rate—The other possibility is a change in the emphasis of our operations as outlined in the memorandum that was distributed, which I hope you’ve all had a chance to read. That involves managing Desk operations from week to week essentially, with a greater effort to bring about a reserve path that will in turn achieve a money supply target. (FOMC 1979f: 6)

A lively discussion lasting the better part of the day resulted in the ratification of the latter option. This discussion will be used to explore the nature of technical rationality at the Fed more closely.

The dialectic of technical rationality Technical rationality is generally focused on some relatively complex and uncertain object of knowledge. In the case before us, the technical experts are predominantly

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focused on a locally recognized set of statistical indicators and predictive models. These objects of knowledge are so well institutionalized that their importance is often taken for granted. Yet these objects of knowledge are variable, their measures uncertain, and their relationship to other objects of knowledge understood to be changeable. In periods of high market volatility, the synthesis of expert judgment and technical discourse can be contentious, confused, and exploratory. Nevertheless, the demands of an environment laden with expectations require that the experts offer interpretations, take action, and maintain credibility. The result is interpretive techniques that legitimate and objectify the interpretation. This objectification is reproduced by Fed-watchers on Wall Street and in the financial media. More importantly, economic actors, nationally and internationally, make consumption, production, and investment decisions based on it. In the application of technical rationality, the object of knowledge is a means of controlling a desired outcome. Thus, technical rationality often has a proximate object of knowledge and a more remote object of knowledge. The former is chosen for its immediate efficacy in having an influence on the latter, less accessible goal. In the case of the Fed, the proximate object of knowledge is a target over which the Fed has some direct control and the remote object is the supply of money and credit in the United States. mr. black. I often think of our position as being analogous to that of a monopolist in the sense that we control the money supply. A monopolist has a choice of controlling either price or quantity but he can never control both. I believe we’ve been trying to control the quantity of money by setting the price and we have misjudged. We’ve jiggled the price, in terms of the federal funds rate, one way or the other, and we’ve usually met with less than complete success in judging what quantity of money will be forthcoming from that. (FOMC 1979f: 22)

Mr. Black uses the discourse of economics to frame the means of control in terms of price and quantity. The Fed had been using the price of money (interest rates) as the proximate means of control. The alternative means is to more directly influence the quantity of money. The remote object of control, the money supply, is elusive as it is ultimately a function of the market and market psychology. The effectiveness of Fed announcements and policy is dependent on a multiplier effect generated by the extension of credit by banks for the expansion or contraction of the money supply. This means that the Fed is not only concerned with the target, but with shaping the expectations of banks and potential borrowers. In October 1979, the Fed feared that inflationary psychology was spinning the markets out of control and with it the Fed’s ability to control expectations. chairman volcker. We wouldn’t be here today if we didn’t have a problem with the state of the markets, whether international or domestic. They were pretty feverish last week—or beginning in the previous week, really. And the phone calls have begun to escalate, reflecting a kind of extreme nervousness in all directions. I think the rumors that were floating around in the market yesterday—first that I had resigned and then that I had died and then that I was mad at Governor Schultz—are

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It is under such conditions, where the object of knowledge is “open, question-generating and complex” (Knorr Cetina 2001: 181), that expert judgment is most in demand, dominating in its dialectic with technical discourse. Routine techniques are called into question. In the quote below, Mr. Partee expresses skepticism about the Fed’s current interest rate targeting and the Committee’s ability to operate it successfully. The relatively routine interaction of expert judgment and the operating model is no longer trusted or credible. mr. partee. [I]t seems to me that our traditional method, which is to estimate the short-term market rates that will adjust the demand functions for various kinds of money on a lag structure, has inherent in it the danger that we are going to miss. Either we will miss an intensification in the demand for money and be behind the gun, as we have tended to be here over the last six months, or we will miss a decline in the demand for money and overstay and be behind the gun, as we traditionally have done going into recessions. It’s an extremely dangerous, risky proposition to change our operating mode. But even though it is extremely risky, I think it’s the less risky course than to stay with our traditional system. (FOMC 1979f: 14)

Mr. Partee doubts that they have the knowledge and skill, that is, the expert judgment, to hit their target. But such doubts must be overcome if policymaking is to proceed. In arguing for reserve targeting, Volcker seeks to convince the members of the FOMC that the new object of knowledge can be operated successfully, and that expert judgment will be adequate to the task. He attempts to reassure them that their judgment will be effectively fine-tuned as the context merits. chairman volcker. [I]nherent in the situation today, and I’ll just put it very simply, the Committee has to have faith that it can give some general guidance and that we—basically the staff here at the Board under Mr. Axilrod’s direction—will translate that as best they can, within these general parameters, into operational numbers. And then, it has to have faith that Mr. Sternlight will use his best judgment in taking the figures that are produced here in Washington and deciding on precisely which day he will provide how many reserves to the market. (FOMC 1979f: 41)

The discussion of the Committee suggests that there is agreement that they are in a situation that the prior discourse, “the traditional method,” cannot dictate. The old operating model has failed and creative action is necessary. But they do not really blame their judgment. It is the discourse or traditional method that has failed. In fact, in thinking about reserve targeting they do not even consider the formal monetarist approach of rigid targets that would “perform” the money supply. Rather, they are protective of their

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prerogative to fit models to context, thereby maintaining their discretion. As the dialectic between judgment and discourse yields a consensus around reserve targeting, interpretive techniques are offered to rationalize the choice and to signal its logic to external audiences.

Interpretive techniques Interpretive techniques reflect the fact that technical rationality is not practiced in a vacuum. Not only are the actions of the FOMC highly consequential, they will be closely examined and provide the basis for considerable economic activity. The interpretive techniques at the FOMC respond to the question “How do we justify and explain this action?” The products of these techniques are crafted narratives using the elements of judgment and discourse. In this sense, they are retrospective explanations of a choice that has been made. These explanations may reflect efforts to construct an internal consensus within the policymaking group or efforts to communicate credible and trustworthy intentions to the external audience. In the October 1979 meeting, Chairman Volcker made it clear, by calling a Saturday meeting, that markets were sufficiently unsettled that strong action was needed. He effectively employed his agenda-setting authority. But it remained for the Committee to rally around this assertion of authority, rejecting the old discourse and anointing the new. Much of the discussion in the Committee involves a validation and rationalization of this choice. The results of the interpretive techniques are a consensus narrative for rationalizing the outcome. Rationalizing techniques attempt to link favored actions with ultimate goals. They reflect the efforts of experts to justify an ambiguous choice. Members of the FOMC explain their support for their choice in the pragmatic language of consequences, carefully disclaiming any conviction about either the old or the new model’s general validity. What is important is the ability of the model to justify the favored action. In an earlier quote Chairman Volcker referred to the markets as “feverish, nervous, and ready to crack.” The goal of policymaking is strong action to alleviate these symptoms. But, as Volcker explains, the remedy involves risky choices. The Committee is forced to choose between fighting inflation and resisting a slide into recession. chairman volcker. . . . [W]e’re dealing with a situation where that’s an imminent danger on the one side as is the possibility of a recession on the other side. Mr. Schultz had an apt description the other day of where we are—and I certainly share the feeling—in saying that Scylla and Charybdis have now come together. There is clearly no risk-free course for us here; there are risks on both sides. The idea that we can absolutely thread the needle between the risks is probably a nice hope but it may be an illusion. At this stage you’ve got to place your bets one way or the other and move. I certainly conclude from all of this that we can’t walk away today without a program that is strong in fact and perceived as strong in terms of dealing with the situation. (FOMC 1979f: 5)

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Despite the dilemma, strong action is needed that will be perceived as forceful by market participants. Changing the operating mode, although risky, is justified in that it allows stronger restraint of the money supply. Governor Wallich is one of several members of the Committee that rationalize this choice based on the belief that it will allow the most vigorous anti-inflation action: “I think the main argument in favor of the reserve strategy is that it allows us to take stronger action than we probably could by the other technique. We are much more constrained in the other technique by the appearance of very high interest rates. In the new strategy interest rates become almost a byproduct of a more forceful pursuit of the aggregates” (FOMC 1979f: 19). The logic of such rationalization is intended only for the local audience of policymakers on the FOMC. Mr. Wallich is telling his colleagues that the new strategy will allow them to raise interest rates without really appearing to do it, thereby bringing down inflation faster at the cost of a worse recession. They will literally use the discourse of the new strategy to disguise their intent. So although they have the legitimate power to raise interest rates, they will use a new method that allows them to offer a less politically fraught interpretation. They are manipulating the discourse to achieve a valued goal. In this context, rationalizing techniques involve an effort to explain a policy’s efficacy. The primary mechanism of efficacy is persuasion that establishes legitimacy. Interpretive techniques are intended to change how people think about what is true and important. In the following quotes, members emphasize that their policy choice must redefine expectations thereby cooling the inflation fears that have resulted in a speculative mania in commodities. As Chairman Volcker and Mr. Rice explain, their traditional method of raising interest rates seems to have exhausted its ability to tame those fears. chairman volcker. I must say that the thought of changing our method of operations germinated—in my mind at least—before the market psychology or nervousness reached the extreme stage it reached over the past week or so. My feeling was that by putting even more emphasis on meeting the money supply targets and changing operating techniques in order to do so and thereby changing psychology a bit, we might actually get more bang for the buck. . . . the traditional method of making small moves has in some sense, though not completely, run out of psychological gas. (FOMC 1979f: 8) mr. rice. First of all, the psychological impact of a change in operating technique will be strong. . . . The good thing about moving to this operating technique is that . . . we introduce new uncertainty into the market. I think that’s a good thing. The new uncertainty will have the effect of cooling some of the speculative activity and perhaps have an impact on those demands for credit that are based purely on inflationary expectations and on the assumption that money will always be available at any level of interest rates that the Fed tries to establish. (FOMC 1979f: 22)

As Mr. Rice suggests, Wall Street, and in particular the banks, had to be convinced that the Fed was serious about controlling inflation and that it might raise rates to a place where banks would stop offering credit. Only this sort of dramatic shift in operating

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technique would put an end to the credit expansion by banks that was funding the speculative mania. With this set of rationalizations, the Fed began a sustained assault on inflation and an unprecedented display of power. Signaling techniques reflect actors’ efforts to shape the meaning of the object of interpretation for public consumption. The message communicated by the signal conveys the organization’s interpretations and intentions. The object of interpretation is often a numerical target, an institutionalized indicator of performance that is well known to the organization’s audience. The use of such targets in signaling calls for skill and experience similar to those employed earlier in expert judgment. Signaling has both routine and creative aspects. In stable periods, the signal reinforces prior messages about the organization’s intentions. Under conditions of uncertainty, the object of interpretation, that is, the target, is often used to probe the environment as a guide to further action (Shotter 1993). Signaling elicits reactions that provide the critical information for further action. This sort of technique seeks to “capture” its object of knowledge in the sense that it tries to shape and control it, taking advantage of the information asymmetry between the organization and its audience to construct the definition of extant conditions. Once the FOMC has a consensus narrative of causes and consequences, it moves on to a calculation of how to signal that interpretation to the markets so that buying or selling in the market is consistent with the group’s intentions, thereby leading the economy in the desired direction. Given the multiple possibilities of (mis)interpretation, members try to carefully craft that signal. They discuss what words to use and what values to convey. There is also an issue of how much of this thinking to reveal. They want to confirm their commitment to a dominant value without revealing more about their thinking than necessary. In this instance, moving to a new operating model, the members want to get, as Chairman Volcker put it, maximum “bang for the buck.” In the quotes below several members advocate a tactic of calculated transparency in which they explain how the new operating model will get the money supply under control. mr. timlen. I’d say it is very important that the announcement connect this new technique with an effort to control the rapid growth in the money supply. The total package must not be perceived, as some have been in the past, as a flash in the pan. I’m not sure how well this will be understood. As a result, I would endorse those people who have strongly recommended that we have an in-depth explanation of this technique and its relationship to coping with the aggregates growth. (FOMC 1979f: 19) chairman volcker. I will just give you my interpretation of a non-mechanical application, as I put it from the beginning, of the new technique. The difference isn’t all that dramatic. There will be more emphasis on the new technique in the press announcement because it will be, in effect, a warning that the federal funds rate is going to be permitted to fluctuate over a wider range. Of course, we can say that in either announcement, but it will be said a little more strongly with the announcement of the new operating method.

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mitchel y. abolafia mr. schultz. I think we are going to get a bigger psychological impact than you think we’re going to get. mr. black. I do, too. (FOMC 1979f: 51)

Both Mr. Timlen and Chairman Volcker put emphasis on communicating the Committee’s intention to control the growth in the money supply. It is a signal that is intended to shift perception and ultimately change the inflationary psychology in the market. This response suggests that the Committee’s announcement be somewhat less obscure than is customary. By the end of the meeting, there is consensus that the announcement of the new operating model will involve more explanation than is usual. Members seem confident that the calculated transparency will yield the desired effects. This tactic of calculated transparency is somewhat ironic in this instance given that it is accompanied by a simultaneous tactic of strategic misdirection. Strategic misdirection refers to a signaling technique in which elites temper the signal so that it directs audience attention away from something that is controversial. In its weak form, such a strategy is merely obscuring, in its strong form it is misleading. The purpose is to make the organization’s intended action seem ordinary, even natural. Organizations employ misdirection when they feel compelled to take actions that may be unpopular or too revealing. In our case, the Fed, concerned with being seen as intensifying the risks of a steep recession, is not prepared to publicize this consequence of the policy. The members employ strategic misdirection to craft a signal that will provide cover for the organization. In the earlier quote from Mr. Wallich we saw that a major argument for adopting the new policy was that it allowed stronger action against inflation. The reason that the new operating model allows stronger action is that it disguises the Committee’s efforts to raise interest rates, which are politically unpopular. In the following quote Mr. Mayo goes so far as to suggest leaving out any mention of the Fed funds rate target from the signal, thereby allowing the inference by observers that rising rates were market-driven: We could decide—to use an extreme example—that we don’t want to say anything about a federal funds range in the directive today, but keep to ourselves the idea that the (trading) Desk should have plenty of leeway. If the market dictates—in the way it responds to what we’re doing—that the federal funds rate should go temporarily to 15 percent, we’d let it go. I wouldn’t worry about that. (FOMC 1979f:17)

The effectiveness of strategic misdirection is dependent on the knowledge and technical skills of the audience. The members of the FOMC are well aware that their arcane discourse is opaque to most of the audience. The Fed’s pronouncements are famously obscure. Mr. Black points out the ongoing advantage of the new method in that very few of the Fed’s stakeholders would be able to infer information about interest rate intentions from announced reserve targets: If we were to announce on the day of the meeting what in fact the federal funds band was, I think we could have some very disquieting effects in the market, whereas

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the announcement of a change in our money supply target would not really tell the market a great deal. Only the most sophisticated or lucky would be able to figure out the interest rate implications of that. (FOMC 1979f: 24)

The final vote was unanimous (12–0). The announcement received widespread media attention and general approval in the business press. Many journalists interpreted the new procedures as an acceptance of monetarism, an alternative theory of monetary policy most associated with Milton Friedman. But Friedman himself was skeptical that it was anything more than what it was: an alternative means to raise interest rates (Friedman 1979). The new operating procedures produced highly volatile markets, but the Fed stuck with them. The economy experienced successive recessions in 1980 and again in 1981–2 and inflation declined dramatically.

Discussion: technical rationality and interpretive power “The substance of domination is not dissolved by technical control. To the contrary, the former can simply hide behind the latter” (Habermas 1968: 61).

This chapter suggests that technical rationality at the Fed is not a neutral form of action, but rather a tool whose use has significant political implications. This relatively unobtrusive form of power became increasingly important as control moved from the market to bureaucracies and ultimately to the technical elite on the FOMC. By October 1979 that technical elite was capable of engineering a major policy change designed to elicit a dramatic shift, if not reversal, in market psychology. What was explained in the press as a change in economic theory was really a shift in policy emphasis from a concern with unemployment to inflation and a willingness to tolerate very high interest rates in order to crush that inflation. In the dialectic of technical rationality, both expert judgment and technical discourse have political implications. It is expert judgment that assesses the relative risks of one policy over another and places values on the outcomes. At the same time, technical discourses carry within them the competing interests of various stakeholders. In October 1979, expert judgment seems to have dominated technical discourse. Chairman Volcker’s willingness to lead the Fed into stronger and perhaps riskier action than it has ever taken, action that would surely deepen the recession that was coming, reflected a choice that the risk of higher inflation was greater than the risk of deepening recession. It is a political judgment call, not a scientific one, as to who in an economy should bear the risk and for how long. As effective as this application of technical rationality ultimately was, our analysis suggests limits to its efficacy and to the rationalization of technical control. The limits

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include uncertainty, politics, and unintended consequences. Uncertainty is inherent in the application of economic models to understanding and predicting the behavior of the money supply. As Davies and Green (2010: 25), two British central bankers, recently explained, “The absence of empirical certainty of relationships over any extended period means that the conduct of monetary policy can only be the continual exercise of judgment. It is inevitably based on incomplete and imperfect information and can never be an exact science.” The following statements by Mr. Coldwell and Mr. Guffey suggest that sense of uncertainty and its associated costs. mr. coldwell. The risks are large, of course, and primarily on the side that whatever recessionary tendencies are already there might be compounded, creating a greater decline. . . . I think the risks are equally strong on the other side in that if we don’t put out something fully credible, we face a potential blow-up via a speculative move in the metals commodities that spreads out from there—in effect a flight from dollars. (FOMC O1979f: 12) mr. guffey. For us to move to a new technique that has never been tried will be viewed by the markets, it seems to me, as our grasping at the last straw, so to speak. And if indeed it doesn’t work to get the aggregates in better position by the end of this year I think we would have shot our last round and missed. I think that’s putting the Federal Reserve as a system in a very, very precarious position . . . If we can get the public reaction that we’re trying to get by operating with our present procedures, I would prefer to go that route rather than go into something that we know very little about. (FOMC 1979f: 18)

There is uncertainty in acting and there is uncertainty in not acting. But as a quasigovernmental agency with a mandate from Congress, the Fed is compelled to shift uncertainty to risk. Much of this risk is political. The “precarious position” mentioned above by Mr. Guffey refers to the legitimacy of the agency and its credibility as a manager of the money supply. The Fed’s efficacy is dependent on firms’, consumers’, and investors’ faith in its interpretations and the commitments they enact to its announced policy goals. The effectiveness of technical rationality is inherently tied to the Fed’s ability to maintain their reputation for credible action. The more a technical elite departs from routine action, the more it puts itself in this precarious position. It is therefore compelled to depoliticize its signals as much as possible, even to the point of misdirection. Finally, we must directly address the issue that lies only slightly below the surface of this chapter, that is, the dangers of empowering a technical elite to make presumably apolitical decisions. Today, the Fed’s willingness to fight inflation in 1979 is remembered as its finest moment. It took decisive action that ended a decade of inflation. It is rare that government is capable of acting so decisively on an economic issue. Democracy often requires compromise and inhibits the kind of risk-taking in domestic policy discussed above. By empowering a technical elite to interpret the situation and promote that interpretation to the public, some of the sluggishness of democracy is sidestepped. In this case, expert judgment informed by technical discourse was both efficient and effective, though painful for those who bore the brunt of a double-dip recession.4

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But what of moments when the outcome is even less positive? Twenty years later, under Chairman Alan Greenspan, the reputation of the Fed was even stronger. Its interpretation of financial bubbles in high tech and then real estate was instrumental in causing the greatest economic crisis since the Great Depression (Abolafia 2010; Stiglitz 2010; Taylor 2009). The danger is that proficient masters of spin become so confident in their technical discourse that the restraints of uncertainty and legitimacy are no longer sufficient to encourage prudent questioning of the current operating models. The result is that discourse dominates the dialectic of technical rationality and the pragmatism of expert judgment is neglected. The dogma of efficient markets has been singularly successful in its capture of disciplinary authority. The threat is that the domination of any technical discourse inhibits the power of judgment to the point where the discourse is performing the policy rather than the experts operating a discourse. This can only occur when such discourse is allowed to become an isolated knowledge domain. In an era of technocratic control, technical rationality is increasingly ascendant, but this makes the responsibility and power of those who wield expert judgment that much greater.

Conclusion This chapter has explored the application of technical rationality to control of the money supply. It argues, on the one hand, that developed economies, like the United States, have moved inexorably toward greater control of the money supply by technocrats. On the other hand, we are struck by the dangers of that technocratic control. A technical elite, with significant autonomy from oversight, has interpretive techniques of considerable power. In the end, the Fed’s performance in October 1979 can be seen as a brilliant piece of political theater. But, as in the recent financial crisis, the performance is not always going to be reviewed so admiringly.

Notes 1. Following Weber, technical rationality is defined as applying scientific knowledge to solve problems. I am indebted throughout this chapter to Habermas’ (1968) close reading of this concept. 2. The Federal Reserve employs over 250 economists at its headquarters in Washington and more at each of the 12 regional banks. Among its journals are The Federal Reserve Bulletin, Economic Policy Review, and the journals of the various regional reserve banks. 3. It is noteworthy that the Fed’s failure in the recent financial crisis has also led to a broadening of its powers. 4. The author was entering the job market at that moment and found his opportunities severely reduced.

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References Abolafia, M. Y. (2010). “The Institutional Embeddedness of Market Failure: Why Speculative Bubbles Still Occur,” in M. Lounsbury and P. M. Hirsch (eds.), Markets on Trial: The Economic Sociology of the U.S. Financial Crisis, Part B. Bingley: Emerald, 177–200. Cowan, E. (1977). “Joint Economic Committee Says Fed Blocks Recovery.” The New York Times, September 26: 51. Davies, H. and David, G. (2010). Banking on the Future: The Fall and Rise of Central Banking, Princeton, NJ: Princeton University Press. FOMC (Federal Open Market Committee) (1978a). “Federal Open Market Committee Meeting November 21, 1978.” Board of Governors of the Federal Reserve, Washington, DC. —— (1978b). “Federal Open Market Committee Meeting December 19, 1978.” Board of Governors of the Federal Reserve, Washington, DC. —— (March 1979a). “Federal Open Market Committee Meeting March 20, 1979.” Board of Governors of the Federal Reserve, Washington, DC. —— (April 1979b). “Federal Open Market Committee Meeting April 17, 1979.” Board of Governors of the Federal Reserve, Washington, DC. —— (June 1979c). “Federal Open Market Committee Meeting June 27, 1979.” Board of Governors of the Federal Reserve, Washington, DC. —— (1979d). “Federal Open Market Committee Meeting August 14, 1979.” Board of Governors of the Federal Reserve, Washington, DC. —— (1979e). “Federal Open market Committee Meeting September 18, 1979.” Board of Governors of the Federal Reserve, Washington, DC. —— (1979f). “Federal Open Market Committee Meeting October 6, 1979.” Board of Governors of the Federal Reserve, Washington, DC. Friedman, M. (1979). “Has the Fed Changed Course?” Newsweek, October 22: 39. —— and Schwartz, A. (1963). A Monetary History of the United States, 1867–1960. Princeton, NJ: Princeton University Press. Greider, W. (1987). Secrets of the Temple: How the Federal Reserve Runs the Country. New York: Simon & Schuster. Habermas, J. (1968). Toward a Rational Society: Student Protest, Science, and Politics. Boston, MA: Beacon Press. Knorr Cetina, K. (2001). “Objectual Practice,” in T. Schatzki, K. Knorr Cetina, and E. von Savigny (eds.), The Practice Turn in Contemporary Theory. London: Routledge, 175–88. Livingston, J. (1986). Origins of the Federal Reserve System. Ithaca, NY: Cornell University Press. Marcussen, M. (2009). “Scientization of Central Banking: The Politics of A-Politicization,” in K. Dyson and M. Marcussen (eds.), Central Banks in the Age of the Euro. Oxford: Oxford University Press, 373–1. Mayer, T. (1998). Monetary Policy and the Great Inflation in the United States. Cheltenham: Edward Elgar. Meltzer, A. (2003). A History of the Federal Reserve. Chicago: University of Chicago Press. Shotter, A. (1993). Cultural Politics of Everyday Life. Buckingham: Open University Press. Stiglitz, J. E. (2010). Freefall: America, Free Markets, and the Sinking of the World Economy. New York: Norton. Taylor, J. B. (2009). Getting Off Track. Stanford: Hoover Institution Press. Timberlake, R. (1993). Monetary Policy in the United States: An Intellectual and Institutional History. Chicago: University of Chicago Press.

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chapter 6

w h at is a fi na nci a l m a r k et? gl oba l m a r k ets as microi nstitu tiona l a n d post-tr a ditiona l soci a l for ms k arin k norr c etina

Few concepts today are as widely used as the concept of a market, few are accorded more importance, and few slip away more easily when closely examined. Financial markets in particular have a stunning and ever more ambivalent presence in our world.The financial crisis of 2008–9 surely made it apparent that financial markets have become a measure of well-being in countries where individuals depend on them for pensions, credit, and income, and governments and corporations depend on them for growth and investments. Yet, when we search for a market concept that captures what we observe in a financial market, we will not readily find it in sociology or even economics. What is a financial market from a behavioral rather than a functional perspective? Is there a special “finance motive” that characterizes financial markets but not other kinds? Is a financial market in some sense a coordinated collective form? Think of the common contrast between markets, hierarchies, and networks. Markets feature in such distinctions as the least structured entity; in fact, the mechanism of supply-and-demand that guarantees a balanced, working market in economics is not a principle of social coordination at all, but an invisible hand that works through self-interested, dispersed participants who adjust their choices to price signals. This chapter looks at the ways in which a financial market is not an empty configuration at all but rather a densely structured and coordinated cultural form. Empirical research has long suggested various action-level components of financial markets (e.g., Abolafia 1996; Baker 1984; Knorr Cetina forthcoming; Knorr Cetina and Bruegger 2002; Preda 2009a, 2009b; Smith 1999, 2007, this volume; Zaloom 2006). This chapter

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builds on this research; it specifically tries to capture key characteristics of those financial markets that are now global in nature and based entirely on electronic trading. Before outlining these features, I first look at existing market concepts,which are based on how we view markets in the primary economy. I argue that financial markets are not like the primary markets of a production economy; if production, consumption, and their interface, exchange, are the three pillars of the economy, finance is a fourth pillar. The next two sections clarify this, and the following two look at the architecture of global financial markets. In contrast to what the idea of an atomistic market suggests, financial markets appear to be coordinated by a central media mechanism which is “scopic” and functions like a mirror—coordination is based on a projected, augmented, and continually updated electronic rendering and image of the market. On participants’ side, this corresponds to the coercive demand for continuous observation and responsiveness; financial markets have a microsociological “build,” which is highlighted in the regime of attention by which they are governed. The next section explores how such markets, which are systems outside organizations, intersect with firms. The last section illustrates the temporal vectors of financial markets: I discuss analytic time as a feature of a market that runs forward at its own speed and schedules; the market flow across time zones; and the global communities of time the regime of attention creates. All of these characteristics identify financial markets as nontraditional in terms of the mechanisms involved, which are nonhierarchical, mediative-scopic, and extended from the very intimate face-to-face situation. They also identify financial markets as a collective social form—a forerunner, perhaps, of an organizational design that is both genuinely global and postindustrial in nature.

Market concepts What notions have been used to conceptualize markets? As Swedberg (2003: 104–5) pointed out, much of the literature has in fact assumed rather than theorized or analyzed markets in a systematic fashion (e.g., Coase 1988: 7, cited in Swedberg 2003: 104–5; North 1977: 710). Notions that are common in the literature associate the market with (1) a place, (2) a mechanism of price discovery and allocation, or (3) a form of exchange, or they see it as (4) an institution, often without analyzing markets concretely as organized structural forms. Historians have shown that marketplaces first materialized in early Greece at the periphery of settlements in the form of “silent trade” between persons who left and retrieved their goods at a sacred stone or analogous landmark (Agnew 1986: 20). Following these anonymous silent markets were the noisy central place markets that resulted from the movement of markets to the center of settlements, a process accomplished fully in England only by the seventeenth century. When we talk about the European Union market, we also use a spatial notion, but we clearly have a large territory in mind, and we define the market by a set of (potential) buyers rather than a central place. Before the neoclassical revolution,

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according to Swedberg (2003: 105–9), economists such as Adam Smith, David Ricardo, and John Stuart Mill also viewed markets as synonymous with a geographical area or a place—just as they saw prices as emerging from the amount of work it took to produce a commodity, rather than from supply and demand in markets. It is noteworthy that dealing outside public marketplaces also existed and expanded in Europe in the sixteenth century, drawing on connections and business relationships between merchants, financiers, and commercial explorers (Agnew 1986). Such widening of scope illustrates the expansion of the specialized role of traders who are not producers, and the emergence of markets that reside in “invisible” networks rather than in specific locations. The spatial notion of a market starts from concrete imagery, and it also harbors a functional connotation. The specified place serves a coordinating function—it solves the problem of bringing together the geographically dispersed and diverse interests of buyers and sellers, or of those who dispose of a good and those who need or want it. The second idea with which modern markets have come to be associated is entirely functional and abstract in nature. Since the end of the nineteenth century, Walras and later economists began to define the market in hypothetical and functional terms—as a mechanism of price discovery (the pricing function) and resource allocation (the allocative function; see, for example, Debreu 1959). Accordingly, in general equilibrium theory, the market is synonymous with the intersection of unobservable and merely hypothesized demand and supply curves and is devoid of any spatial, institutional, or social features (Rosenbaum 2000: 459). Buyers’ demand and sellers’ supply are viewed as forces operating in the market. The relative prices of goods adjust themselves according to the laws of supply (all other things being equal, sellers will tend to supply more at a higher price) and demand (all other things being equal, the quantity demanded of a commodity is inversely related to its price) until a mutually acceptable price emerges to balance these forces. When this happens, the market is said to “clear” and a state of equilibrium is attained. The equilibrium price is something to be discovered in this market, but the price also coordinates the interests of buyers and sellers by allowing them to satisfy their needs through pushing supply and demand in the right direction. The model conceives of markets as tending toward a state of rest, though this state may only be attained through complicated processes of adjustment and negotiation among players who react to various signals. The reference to a specific place is also lost in the third widespread notion that sees markets as synonymous with a form of (commodity) “exchange.” Economists, sociologists, and anthropologists invoke the idea when they define the economy as consisting of production, consumption, and exchange as the mechanism that assures the distribution of goods (e.g., Dholakia and Oza 1996: 7; DiMaggio 1994: 28; Hillebrandt 2007; Lie 1992; Portes 1995: 3; Smelser and Swedberg 1994: 3). Accordingly, “A market exists whenever two or more individuals are prepared to enter into an exchange transaction, regardless of time or place” (Gravelle and Rees 1992: 3, cited in Rosenbaum 2000: 459). In such definitions, exchange not only refers to the functional role of markets in bringing together producers and consumers, but suggests

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that exchange is the type of action that characterizes markets. It is this reference to a particular type of action that we need to take seriously if the concept is to be more than a vague synonym for “market.” The fourth idea, the market as an institution, has met with renewed interest in economics and other social sciences in the last decades. Institutionalism models institutions abstractly in terms of legal rules and social norms, which is exemplified in the contractual arrangements of markets (e.g., Aspers 2011: 4–5). Recent institutionalism in economics sees institutions as efficient solutions to economic problems emerging from the pursuit of self-interest by rational, more or less atomized individuals who economize on transaction costs (Williamson 2000). Straightforward, non-repetitive transactions not requiring transaction-specific investments (one-time purchases of standard equipment, for instance) will more likely take place between firms, that is, “across a market interface,” while transactions that are uncertain in outcome, recur frequently, and require substantial “transaction-specific investments”—for example, money, time, or energy that cannot be easily transferred to interaction with others on different matters—are more likely to take place within hierarchically organized firms (Granovetter 1985: 493–4). While this approach has brought firms out of their “shadowy” existence in economics and specified core characteristics of firms (e.g., hierarchy), markets remain in the shadow—they appear simply negatively defined as an alternative to firms and are what economists have long thought them to be—individual actors’ strategic operations in a competitive environment. Sociology’s recent institutionalism, in contrast, relates institutions less to norms and legal rules than to the operation of cultural scripts in organizational contexts that promote role-following behavior with a view to what counts as culturally appropriate and legitimate (Powell and DiMaggio 1991). Applied to markets, the approach suggests that we should ask to what degree perceptions of cultural appropriateness rather than strategic decision-making and rational choice inform the behavior of market actors (Scott 2001: 51–2, cited in Ebner and Beck 2008: 4). Preda (2009a: chs 2 and 4) comes closest to illustrating this perspective. A different kind of institutional approach in sociology is more historically contingent and relates markets to the political–economic governance arrangements and larger cultural structures to which they may be subject (e.g., Fligstein 2001; Hamilton and Biggart 1988). This approach may see markets as creations of government and pay primary attention to market regulation (see Fligstein, this volume; Ebner and Beck 2008: 4). A third type is distinctly organizational with the dominant line of research specializing in the analysis of interorganizational ties. This, in effect, joins organizational analysis and market analysis using network approaches that look at the nature of relationships and their effects as well as at “upstream” (e.g., supply chain) and “downstream” markets composed of such networks (Baker 1990; Bandelj and Purg 2006; DiMaggio and Louch 1998; Uzzi 1999; White 2002). For example, White’s (2002) model stresses the existence of networks of sellers monitoring each other to find distinctive niches for their products. In conventional market theory, producers may be oriented toward consumers in monitoring demand; they may also drive prices down and homogenize their products (Collins 1988: 432–3).

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Finance as the fourth pillar of the economy: the credit core of financial markets When most people think “market,” they think of primary or production markets—the domain where goods and services produced in one sector of the economy are sold to consumers. The literature surveyed is no exception; most analysts either directly refer to production markets, or appear to have them in mind when they talk about markets. When the economy is defined in terms of the three categories of production, consumption, and distribution/exchange mentioned before, the market appears as “purely an intermediate activity between production and consumption, facilitating the distribution of goods and services and thereby satisfying certain human wants” (Dholakia and Oza 1996: 7). Yet finance and financial markets are not simply a subcomponent of a distribution system; the markets that help goods find their way from producers to consumers have to be distinguished from markets that create the financing for these and many other economic functions. The market environment in Western societies is highly differentiated; production markets and financial markets, for instance, have distinctive histories, respond to different needs, and exhibit different regimes of action and coordination. In other words, definitions of the economy in terms of the three pillars of production, consumption, and exchange are incomplete. They neglect the fourth pillar of economic activity, finance. As Bernanke put it: To expand and modernize their plants and increase their staff, most firms must turn to financial markets or to financial institutions to secure this essential input. Families rely on the financial markets to obtain mortgages or to help finance their children’s educations. In short, healthy financial conditions help a modern economy realize its full potential. For this reason, one of the critical priorities of developing economies is establishing a modern, well-functioning financial system. (Bernanke 2007: 1)

The parents, homeowners, and firms Bernanke talks about all need financial capital, or in other words, they need credit. The function of the fourth pillar of the economy, of finance and financial markets, is the control of credit (Strange 1994: 30). Keynes was among the first to address the nature and role of credit; he maintained that what is invested in capitalism is not money or savings that must first be accumulated, but credit, which can be created, for example, by stock issuance. Production requires prior investment in capital goods and other expenditures; a Robinson Crusoe without means of investment could not hope to produce much. He would have to invest his own time and labor in order to build the rudiments of a productive capital structure to successfully start up production (Shapiro 1985: 77). Only after production had been financed could it result in employment income, part of which could then be used to generate savings. Thus credit and credit needs are prior to savings, and savings are generated only at the end of a credit-financed production cycle. Keynes also spoke of the “finance motive,”

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which Carvalho (1976: 72–6) describes as “related to investment plans adopted because of expectations of future profit rather than to current income.” Keynes’ point is interestingly borne out by recent quantitative historical research that suggests the United States’ development of a complex, articulated financial system may have been a key driver of the rapid manufacturing growth of the nineteenth century (Perkins 1994). Previously, historians had regarded manufacturing technologies, the railroads, and the opening of the west for settlement as driving forces for that growth. In contrast, Sylla (1998) argues these last developments mostly occurred after 1815 and relied substantially on the financial system developed earlier. Credit can be obtained through two channels—bank lending and financial markets. Manufacturing-oriented economies, such as that of Germany and Continental Europe more generally, historically developed a financial organization in which bank lending dominated. In the United States, as in Anglo-Saxon countries generally, a different pattern emerged with less emphasis on bank lending, while money markets and securities markets each provided important credit channels. During the financially revolutionary period at the turn of the eighteenth century in the United States, the number of banks rose from three in 1790 to 327 by 1820. Interestingly, this hundred-fold increase in the number of banks also implied the rise of the financial market channel. Unlike in other countries, banks raised their capital by issuing securities in the United States. They also accepted securities as collateral for bank loans. Based on an analysis of securities market prices reported over a period of four decades, Sylla, Wilson, and Wright (1997) conclude that an effective financial market emerged that priced securities efficiently, involved inter-market arbitrage between the major cities, and paved the way for capital influx from Europe that reached huge proportions in 1820–30. The United States led the world in the proportion of financial assets held in the form of stocks after these became bankable assets in the same period of financial growth. The Keynesian argument then provides reasons for seeing the financial system as prior to and functionally differentiated from production, and for understanding the credit basis of Western economies. The historical argument shows the desynchronization of finance and production during axial stages of industrialization and points to the early importance of the financial market channel in obtaining credit. A third process, deregulation, also helped launch financial markets as a source of financing and an investment alternative to bank savings; it decoupled these markets, particularly over-thecounter markets, not only from production, but also from national regulatory environments. Financial markets enjoyed successive waves of liberalizing capital flows and financial services from the control of individual nation-states (documented by Geisst 1995: 9; Swary and Topf 1992)—while at the same time depending on government policies for their uptake (see also Fligstein, this volume). The removal of barriers between national financial markets, for example currency markets in the last decades of the twentieth century, enabled a system to emerge that economists consider to have minor frictions and that appears beyond the control of any regulatory structure. Deregulation continued in the United States until recently, though the financial crisis of 2008–9 also prompted reregulation. Production systems remain more deeply embedded

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in national regulatory environments that affect many aspects of the workforce, production plants, equipment, ecological externalities, and so on. Banks and bank lending also are subject to close government oversight. Such oversight carried forward in the United States from the late eighteenth and early nineteenth centuries, when not only were banks important sources of finance, but bank notes and deposit liabilities served most of the functions of money. Thus, governments had reason to be concerned with licensing and regulating these banks’ money creation (Carruthers and Babb 1996; Sylla 1998: 84). Since then, the market channel has developed into the centerpiece of the global financial architecture and the financial organization of Western economies. In fact, capital markets have become major funding alternatives to banks as a source of debt financing for industrial corporations. In the United States and the UK, less than 30 percent of corporate finance came from commercial banks before the turn of the century (Chernow 1997). Though bank credit is still important in some of today’s more complex economies, it is itself deeply enmeshed in financial markets through banks’ own investment and financing strategies. Only a small fraction of the money lent to credit-seekers actually comes from clients’ deposits of money. The market for repackaged subprime mortgage debt and for credit derivatives, and default obligations more generally, is a case in point. A major factor in the crisis was the expansion of credit available to banks, which expanded their leverage through the use of such instruments to a volume several orders of magnitude larger than their deposits, and this injection of credit massively increased the trading of, and risks incurred by, these instruments (e.g., Taylor 2009: ch.1).

Financial market action: not simply exchange The functional specificity, historical desynchronization, and deregulation of financial markets suggests that they are best seen as systems in their own right in which financial instruments, which are contracts, are created and grown, tested, multiplied, and expanded in transactions. The actions involved also speak for the distinctiveness of financial markets. Markets, as indicated before, are often characterized as the place for exchange transactions—and this may be warranted when we have the primary economy in mind. When we go to a weekend market, for instance, we buy produce for money through a paradigmatic exchange transaction. Its most important characteristic is that when we are finished with the transaction, we are quits, as Slater put it (2002: 237). Exchange implies that the objects that change hands are defined to be of equivalent value so that the transaction can be brought to a close once the payment has been made. The core activities in financial markets, however, are investment and speculation. This follows directly from the credit core of finance. What is bought and sold in financial markets are not consumer goods but “financial instruments” (e.g., stocks, bonds, etc.)

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that directly or indirectly provide credit to a borrower (firms, states, etc.) for which the lender hopes to get dividends, interest payments, or value changes of a credit instrument in a profitable direction over time. Thus, the buying or selling of a financial instrument initiates an engagement or contract that lasts as long as one holds the instrument, and invariably involves risk (since the future is uncertain, outcomes cannot be guaranteed). When we have finished buying a financial instrument we are typically not quits; rather, we find our fate related to the credit receivers and their economic policy and success. Financial market actions are thus relationship-initiating (or ending) time transactions that connect the fates of lenders, borrowers, and the market, binding them to future outcomes. A financial market does not exist when two or more individuals are prepared to enter into an exchange transaction, but rather when these actors are prepared to enter into promissory engagements: claims and commitments exercised over time based on the promise of future outcomes. The action structure of financial markets has implications for the demand–supply perspective. Financial market transactions are oriented not to the present price of an instrument but to its imagined and expected returns at future points in time. Hence, demand may rise rather than fall, even when the price is high, if participants expect it to rise further (this is one element in the explanation of financial bubbles). We may denounce this as the “irrational exuberance” of investors, which leads to overpriced assets unjustified by economic performance and to mean reversions that bring a lack of available capital when bubbles burst (Shiller 2000: 31ff.). But if we see financial market actions as inherently speculative, which in a morally neutral language means as actions that are forward-looking to envisaged outcomes, then valuations that are based on hopes and promises rather than on present values are a structural feature of this action. Economists have generally seen financial markets as advantageous, despite the speculative nature of financial action, arguing that these markets have led to the pooling of wealth into larger amounts for capital use, decreased cost of corporate finance through disintermediation (the elimination of banks and their pricing structures as lenders; see Chernow 1997), a wider spread of risk to obtain credit through the splitting of shares, and derivative products that can be used for hedging risky investments (e.g., Merton and Bodie 1995: 13–15). There appears to be a consensus that the system has developed in distinctive ways fueled by factors as diverse as government debt seeking financing, changes in pension systems, or a democratic interest in extending the basis of home ownership through subprime credit. There also appears to be a consensus that the economic growth in the last decades and the growth of high technology and knowledgeintensive industries are linked to the proliferation of financial market credit to the extent that such growth could never have been financed without the creation and intensification of this credit (Strange 1994: 30). As these factors show, financial markets clearly have a role to play in the economy and society. My point has been that they play this role by inhabiting a world very much of their own making—organizationally, technologically, and on the level of agency and action.

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The architecture of financial markets Adam Smith famously wrote that markets are coordinated by an invisible hand. This section is about the visible hands of contemporary financial markets: the structures and scaffolds that make markets into a distinctive structural form and enable a level of coordination and integration. Financial markets come in two types: exchange traded markets, and over-the-counter (OTC) markets. Exchange traded markets, for instance, have a central location in which demand and supply become concentrated: the exchange. Exchanges are themselves corporations or membership-based organizations of brokers and traders that have exclusive rights to trade at the exchange. Exchanges provide matching and trade execution facilities that are not only tied to a place (computers and clearing functions may be located in additional places), but also fixed in time— exchanges have opening hours, schedules, and times when prices may get settled— meaning they are not continuous but discontinuous trading facilities. In order to be traded, instruments have to be standardized; companies have to meet the listing requirements of the exchange (e.g., minimum market capitalization, earning requirements, number of shares issued, auditing requirements), along with being subject to specific disclosure regulation. The exchange itself is also subject to oversight by bodies such as the US Securities and Exchange Commission and to regulation designed to restrict opportunism such as insider trading, price manipulation, and failure to disclose information. For example, regulation may attempt to ensure and safeguard: fair, orderly, and efficient business operations; price formation that conforms to exchange rules and the prevention of price manipulation; documentation of all business for a number of years by the exchange and by listed companies; defined rules for publishing prices, turnover, and so on; and investors’ access to constitutive information (SEC 2010). Exchanges illustrate how organizing and regulating elements are structured into markets. Yet, the market itself is not interiorized in exchanges. In fact, large and small investors may trade at a public exchange, and, consequently, large numbers of actors participate in such markets. The exchange simply realizes a function that markets need through a human organization by bringing together buyers and sellers and executing trades. The second type of financial market, over-the-counter markets, mostly realize the same functions today in electronic form—they use electronic brokers for the matching and ordering of buying and selling interests in the market. A financial market, then, is always larger than any particular organization that may be part of it. But how should we conceptualize this larger entity? Partial organization theory may lead a step further; it suggests that we may see a market as an organization outside organizations, which is partial in sense that it may include some, but not all, elements that we commonly associate with formal or complete organizations (Ahrne and Brunsson 2010). Decided-upon membership, rules of behavior, sanctions, monitoring, and formal authority or hierarchy are defining elements of formal organizations. Financial markets have most of these elements. However, the hierarchy is a status hierarchy rather than deriving from formal

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authority; most rules in an OTC market, for instance, are rules of trading practice corresponding to the legal category of a lex mercatoria, and membership is definitional— and sanctioned by consequences—rather than being controlled by authority: a market participant is anyone taking and holding a financial position in the market. Thus, a financial market is an organized social form, complete with strong insider–outsider distinctions, membership criteria, potentially stable status hierarchies, and interiorized forms of monitoring and regulation. Yet there is a crucial difference to the formal organization: market structure appears to be institutionalized on the execution and agency level, rather than on a formal level. In more theoretical terms, financial market’s institutional foundation is microsociological in nature, converging with Goffman’s and others’ interaction-level structures. Over-the-counter markets illustrate this most clearly as they are not centralized but decentralized; they are not built around exchanges. In an over-the-counter market, transactions typically occur between traders on the trading floors of global banks in global cities (Sassen 2001; see also this volume). The laws of trading practice in such a market are maintained through the structural use of interaction means as traders warn, reprimand, and sanction one another using linguistic formats and threats to prevent the rules of trading practice from being broken. However, it would be wrong to understand a financial market purely as a field of interaction. Imagine a federation of computers and a set of electronic screens: the screens form a synthetic, ring-like medium through which tasks flow horizontally—from time zone to time zone—and vertically as things scroll down the screen. The screens sit on an electronic infrastructure that interconnects trading floors and serves as a scaffold, on which various interaction-level systems—devices for performing a task—have been mounted. To draw on the analogy of molecular manufacturing (Heller and Guttman 2002: 265), we can consider this screen setting as resulting from a historical pick-and-place process by which heterogeneous action, communication, and information functions needed for financial markets to perform have gradually been grafted onto screens. Examples of these functions are conversational dealing systems that offer the possibility of dealing through talk—they are used also for sharing gossip and information, and for organizational communication. Another system is the electronic broker (EBS) dedicated to processing, ordering, storing, and displaying trading opportunities—volumes and prices indicated on screen which can be traded at the click of a button. We can deal through the EBS, but not talk. A further set of systems offers accounting capacities and delivers news, commentary, and analysis, and provides access to trading data and charts, and calculation capabilities. Analysts, strategists, and economists on the trading floor provide additional analysis through studying and reanalyzing the information on screen, and looping their analysis back onto the screen. The pick-and-place world still requires human information feeds and supplements. The screen only provides organizational, communicative, and analytical functions; its content comes from information providers and traders who bring the various capacities alive as they engage with the market. Yet the screen has another effect that is crucial in understanding the architecture of financial markets: it acts like a scope—a central mirroring device that projects the market and coordinates trading.

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We may see a financial market as a tightly coordinated response system that is based on a regime of attention and perception. Let’s define a response system as a sequential transaction system in which responsiveness is mandated. Conversations are examples: they are dyadic response systems for which turn-taking rules and the visual and cognitive orientation of participants toward each other provide the scaffold. Conversationalists take turns in contributing utterances that acknowledge and react to previous utterances. Global markets are like far-reaching, distance-overcoming conversations among many conversationalists. What brings such conversations together and directs their sequence is the scopic work of trading screens. The most developed OTC markets have become global, unified arrangements in which participation is enabled and coordinated by a scope, a central monitoring and mirroring medium that distills the market, focuses attention and perception, and coordinates trading. Scopic algorithms also aggregate market interests and transactions into one continuous stream of best buy and sell deals. As a consequence, participants conduct dealing conversations not only through the electronic medium with concrete others, but also with the screen itself—with an algorithmically enabled aggregate of dealing possibilities, presented to them by an electronic broker. With the notion of a scope, I am offering a simplifying term for the constellation of hardware, software, and content feeds, which are packaged together and delivered to participants in a global market through the common platform of their shared computer screens. The “scoped” reality is projected to everyone connected simultaneously; the screen content places all those observing it (as professional traders must) instantly into an identical world. There is no need to call a contact and draw on one’s network of relationships to learn where the market is and what else is going on. The answers to these questions are delivered to everyone instantly, and they are continuously updated within fractions of seconds. Not all financial markets are as yet of this nature; exchange traded markets, for example, have moved only in the last decade from their open outcry system to embracing scopic media and to transnational arrangements (Muniesa 2005; Zaloom, this volume). For example, the $10 billion all-stock merger between the New York and the Frankfurt Stock Exchange, designed to create a market presence in 14 European countries and the United States, was concluded only in February 2011—and abandoned later. An OTC market that fits the description is the currency market—it has been a unified global market since the 1980s, when Reuters’ “Monitor,” the first comprehensive electronic dealing and information system, was introduced. With a daily average turnover of currently approximately 4 trillion dollars (BIS 2010), the currency market is one of the largest markets worldwide; it is not traded in exchanges but is an over-the-counter “private” market (an analogy here is the private trade that developed between merchants and others since the sixteenth century in the primary economy). Up to the 1970s, the currency market appears to have been a network market: trading occurred through networks of relationships which were needed to find out “where the market was,” that is, who wanted to trade and what the prices were. At that time, arbitrage—the exploitation of information differences about prices and volumes between participants—was routine in currency trading. A strong indicator of today’s one global system is that this sort of

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arbitrage is no longer possible. Market members today need not go through networks to find the market; they participate in one global market conversation, which is enabled and directed by a scopic mechanism of coordination. Scopic markets of this sort are not relationship markets but instead are based on a regime of attention and perception: of watching the market on screen continuously, synchronously, and in immediacy. Attention to the screens is mandatory and coercive—the equivalent of a scopic mechanism on the human side, and a behavioral pattern that identifies professional market participants. It is illustrated by the habits of vigilance and concentration Abolafia (1996: 230) observed among bond traders who develop this skill to be able to respond to market moves on a moment’s notice; by the coercive monitoring Knorr Cetina and Bruegger (2002: 920ff ) report among currency traders; and by the primary attention Preda (2009b) found day traders working from home devoting to the screen. The cries traders shout out in response to screen signals are suggestive here too. Through such cries traders appear to embody market turns (Knorr Cetina 2009: 76–8), and keep themselves and others alert to market moves on screen (Laube 2008). Coordination results from the simultaneous injection of bursts of content onto a collective of observers—or, to put it the other way round, from the simultaneous and continuous exposure of an attentive and expectant group of market participants to bursts of information. The exposure results in collective cognition—a shared awareness and distributed conversation within a bounded market environment of the state of the market, and the world relevant to it. We can think of this collective cognition in informational terms, visualizing it in terms of the strange swarm intelligence of the market (for various aspects see Callon 1998; Fama 1970; Hayek 1945; Knorr Cetina 2010; Preda 2009c; Smith 1999). We can also visualize this collective cognition as a social membrane of the market field. The screens feed and renew the membrane—and they provide a sophisticated feedback and support system for the market discourse that develops around their bursts of information.

Traders and trading floors: the intersection of markets and firms I have argued that financial markets should be seen as global response systems looped together by mutual and reflexive observation enabled by scopes. Indeed, the central organizing mechanism of contemporary financial markets are not the authority structures of firms or interfirm arrangements, but the “authority” of screens, their continual, contextually augmented, and algorithmically enhanced projection of the market to which participants become oriented and to which they react. The theoretical argument here is that the regime of joint orientation and attention—the shared response presence of participants (Knorr Cetina and Bruegger 2002: 909) and its outcomes, for example the resulting market conversation—is the sociological underpinning of the market process;

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it provides the glue, if you will, for a market that is organized but extends beyond formal organizational elements such as firms and exchanges. Attentional integration (see below) is a mechanism fundamentally different from that of network connections (which may have characterized earlier markets), and from coordination by hierarchy and control manifest in firms. Firms (other than exchanges) remain in the picture, however, as indicated before; their role in markets hinges on how we understand trading floors, those parts of global investment banks, for instance, which are directly engaged in market activities. Trading floors are units of firms, but I see them as institutional hybrids halfway between market and firm, and as adapted to markets. In other words, trading floors are not simply subdivisions of firms in which corporate tasks are performed. Rather, the crucial question here is that of the control of the financial transactions performed on floors. A financial market is an intermediary arrangement involving hardware, software, and human components whose performance and outcomes are not controlled by any of the firms involved. Traders, not bankers, are the key operators in these arrangements; agency shifts from the firm to individual traders when it comes to market-making and managing. Traders, whose social role is absent in producer markets and traditional bank lending, represent and embody the nature of financial markets (see also Zaloom, this volume). In the aforementioned OTC market, traders are market-makers; they take their own positions in the market in trying to profit from price differences, while also offering trades to other market participants. Traders thereby provide liquidity to the market and sustain it—if necessary against their own position and interest. In other words, traders act as custodians of the market—they fulfill bridging and liquefying functions when gaps arise and activities seem to gel, and they may also try to revive markets when they break down. Although banks limit traders’ losses and the volume of instruments they can trade, traders are not constrained by any of the banks’ views on the development of price movements but instead develop their own stance on the instrument they trade. Indeed, as participants confirm, it is quite common for the trading book and banks’ proprietary position to be at odds with one another (Goodhart 1988: 456; traders in hedge funds may have less autonomy). Traders’ entrepreneurial inclinations, frequent turnover, bonus pay structure, and the distinctive face-to-screen set up of trading floors all reflect the market. The bonus, for instance, which we may see as the entrepreneurial part of their pay, may be several times higher than traders’ salary given by a bank—and firms like it because it is not part of their fixed costs, transcending company functions. If the bonus does not “compute,” does not reflect the size of their earnings in the market, traders are likely to leave the firm. Thus, traders may formally be categorized as belonging to the group of feeearning capital market intermediaries who provide various services in financialized capitalism. However, intermediaries are not a coherent group of actors. If we define intermediation as “a relation in which one actor mediates the flow of resources or information between two other actors who are not directly linked,” as in brokerage (Fernandez and Gould 1994: 1457), traders are not a good case in point, since they initiate deals proactively, and take and manage their own speculative positions. One way to define traders’ role is to see them as agents for their own and firms’ interest. Traders (and firms) see these interests as aligned when both parties capture substantial shares of the turnover and

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profit. For traders, bonus day is when this alignment is tested, and, if it is found faulty, adjustments are sought. Traders in the foreign exchange market studied, for instance, were market actors with generally no obvious external client, operating as marketmakers in their own right, and “in pursuit of the next value-enhancing move” (Folkman et al. 2008: 155). Though they were not owners of the positions they took for the firm, and hence not principals according to a principal–agent distinction, traders surely had the full power agents customarily wield based on their market-insider status, expert skills, and moment-to-moment market knowledge.

Attentional integration and the market flow There is a powerful element still missing from the micro-institutional concept of financial markets I have offered: the temporal nature of these markets. Financial markets of the sort described are temporalized systems, and the temporal vectors of these markets are interlinked with the regime of attention. Consider that traders perform their activities in a moving field constituted by changing dealing prices, shifting trading interests (indicative prices), scrolling records of the immediate past that are continually updated, incoming conversational requests, newly projected market trends, and emerging and disappearing headline news, commentaries, and analyses. In other words, they perform their activities in a streaming world; as the information scrolls down the screens and is replaced by new information, a new market reality continually projects itself. The screen reality, in these markets, is like a tapestry, small sections of which are woven in front of us. More generally, the screen reality—the tapestry—is a process, but it is not simply like a river that flows in the sense of an identical mass of water transferring itself from one location to another. Rather, it is processual in the sense of an infinite succession of nonidentical matter projecting itself forward through the changing screen. The market’s “flow,” as I use the term here, refers to this rolling projection of change; the scopic architecture enables the seemingly unstoppable dynamic of an electronic financial market. Everyday time does not “clock” such markets, although it is never fully suspended and operates in the background, grounding, among other things, traders’ work schedules and the opening hours of exchanges. What clocks them is an “analytic time,” that of the speed and clustering of incoming messages. Analytic time has specific features. For example, its rhythms are not even; it may suddenly speed up as message intervals get shorter and more items stream onto the screen. It is punctured by specific calendars and schedules, dates and hours set for important economic announcements and for the release of periodically calculated economic indicators and data. At these occasions, analytic time intersects with everyday time as developments in the primary economy break into the financial economy, encapsulated in indicators of the former’s state and “fundamental” characteristics.

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The market’s temporal nature is closely intertwined with the attentional regime. First, markets mandate such a regime because they change continually, and do so according to a time of their own, that of the streaming aggregate patterns of algorithmically processed transactions and contextual activities. Second, traders who take positions in the market put themselves (their financial well-being and employment) on the line with every move the market makes, and they can see their developing fate recorded on screen. This combination of high personal stakes and of a quickly moving market explains the need for continuous attention to the latter. Third, the attentional regime can be brought into contact with the concept of the flow experience—a highly focused subjective condition of concentration implying an altered state of consciousness and an almost automatic task performance (Csikszentmihalyi 1990). Thus, we may assume that the unforgiving temporality of the market and the attention this requires engenders subjective states of flow, and needs them for optimal performance. Flow experiences also involve feelings of selfactualization as well as the disappearance of self-reflexivity, distractions, and worries of failure. This may help explain the risk market actors often embrace and the disregard they may have for concerns and rules of those external to financial markets. A global market, to be sure, flows not only in analytic time but also across territories from one time zone to another. This type of flow captures the mobility of the market. The market’s visit in various time zones implies an intersection of residential physical life-forms—that of the embodied operators of the system (e.g., traders) and of system facilities (e.g., trading floors)—with the nonresidential level of this specialized world: actions, transactions, and accounts which are all in symbolic form and on the move. In response–presence terms, markets are released from the attention of a previous time zone and seized by the attention of the next. Moving the market across time zones involves work, for example the production of summary accounts which transfer attention-demanding trends from one time zone to the next for processing—these trends are encapsulated in closing rates, index values, volume statistics, intraday trading indicators, and so on. As a consequence of this alerting work, the market appears to arrive “whole” (encapsulated in summaries) at every time zone and takes off “whole” to the next one. And as it “arrives,” attentional resources are activated to amplify the task of engaging the market until it becomes the exclusive content of a timezone-centered system. These include technological resources, such as auditory and visual signals that can be switched on and off on screen, and organizational resources, such as transnationally conducted morning meetings that highlight certain developments, or lunch being served at trading desks so as to not interrupt traders’ concentration. The attention and responsiveness participants bring to the market joins them together across institutions and space, and here too, time matters (Abbott 2001). As professional traders observe the market continuously (virtually without interruption), in synchronicity and temporal immediacy (they see the same market simultaneously in real time), a level of integration emerges among them that is based on reciprocal attentiveness— participants recognize the presence of others in the market evidently paying attention to the same events, which are visible on screen. How do they recognize others’ copresence? Through the deal requests counterparties make, the messages others send, and the price movements they trigger. A significant part of traders’ observational activities goes into

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identifying and reading the signals of mediated presence with a view to market players’ possible moves and intentions. Another significant part goes into conveying what they observe to other market players with whom they maintain relationships. In this sense traders transmit and amplify signals of reciprocal attentiveness, contributing to their spread. In other words, the regime of attention governs not only individual behavior, but, in connection with signals of reciprocity, is the source of a level of collective integration in global fields. Attentional integration requiresco-temporality, participants’ copresence over time as they watch the same event (the market) unfold in time. Schutz (1964: 24–6) associated co-temporality with the emergence of a “We-relation”: participants may feel “we have seen the same things together,” or “we have been in this together.” This We-relation need not involve other types of communality—it does not assume a communality of thought, the sharing of interpretations and communications, or solidarity among participants. This lack of strong assumptions would appear to be an advantage in a concept of sociality that targets a globally distributed population.

Conclusion It is plain that the emergence of such attentionally integrated communities is premised on the presence of scopic media—on the screen as a device that continually rolls out the market, “flowing” it to viewers as a reality of its own. Markets are transactional worlds connected not only via traditional organizational media, such as networks or rules of trading practice, but via reflexive mirroring systems that gather up transactions, augmenting and embodying them as “market” for an audience of observers. While humanto-human trading remains a possibility in these markets, human-to-screen/market trading appears dominant, and trading by algorithms (market-to-market trading) is an increasingly important component. The concept of a coercive response system intends to capture the micro-institutional foundation of these markets, while also seeing them as scopic environments in which media and media feeds have become embedded in human interaction. The scopic mode of life raises research questions not addressed in this chapter, for example the question of how the attentional resources located not only on an organizational, technological, and interactional level, but also on a cognitive (information processing) and neural level, supplement and interact with one another. Another vector in the scopic realm which I cannot discuss here concerns the emotional and libidinal underpinning of trading—and how it relates to the sociology of greed as a relevant phenomenon in the trading ecologies of finance.

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Folkman, P., Froud, J., Johal, S., and Williams, K. (2008). “Intermediaries (or Another Group of Agents?),” in I. Ertuk, J. Froud, S. Johal, A. Leaver, and K. Williams (eds.), Financialization at Work. London: Routledge, 150–62. Geisst, C. R. (1995). Exchange Rate Chaos: Twenty-Five Years of Finance and Consumer Democracy. London and New York: Routledge. Goodhart, C. (1988). “The Foreign Exchange Market: A Random Walk with a Dragging Anchor.” Economica, 55: 437–60. Granovetter, M. (1985). “Economic Action and Social Structure: The Problem of Embeddedness.” American Journal of Sociology, 91: 481–510. Gravelle, H. and Rees, R. (1992). Microeconomics (2nd edn). London: Longman. Hamilton, G. G. and Biggart, N. W. (1988). “Market, Culture and Authority: A Comparative Analysis of Management and Organization in the Far East.” American Journal of Sociology, 94: 52–94. Hayek, F. A. (1945). “The Use of Knowledge in Society.” American Economic Review, 35: 519–30. Heller, M. and Guttman, A. (2002). Integrated Microfabricated Biodevices. New York: Marcel Dekker. Hillebrandt, F. (2007). “Kaufen, Verkaufen, Schenken: Die Simultanität von Tauschpraktiken,” in J. Beckert, R. Diaz-Bone, and H. Ganßmann (eds.), Märkte als soziale Strukturen. Frankfurt and New York: Campus, 281–95. Knorr Cetina, K. (2009). “The Synthetic Situation: Interactionism for a Global World.” Symbolic Interaction, 32/1: 61–87. ——— (2010). “The Epistemics of Information: A Logic of Knowledge Consumption.” Journal of Consumer Culture, 10/2: 1–31. ——— (forthcoming). Maverick Markets: The Virtual Societies of Financial Markets. ——— and Bruegger, U. (2002). “Global Microstructures: the Virtual Societies of Financial Markets.” American Journal of Sociology, 107: 905–95. Laube, S. (2008). The Sounds of the Market: How Traders Keep the Pace with a “Silent” Market on Screen. Unpublished paper, University of Constance. Lie, J. (1992). “The Concept of Mode of Exchange.” American Sociological Review, 57: 508–23. Merton, R. C. and Bodie, Z. (1995). “A Conceptual Framework for Analyzing the Financial Environment,” in D. B. Crane, R. C. Merton, K. A. Froot, Z. Bodie, S. P. Mason, E. R. Sirri, A. F. Perold, and P. Tufano (eds.), The Global Financial System: A Functional Perspective. Boston, MA: Harvard Business School Press, 3–32. Muniesa, F. (2005). “Contenir le marché: la transition de la criée à la cotation électronique à la bourse de paris.” Sociologie du travail, 47: 485–501. North, D. C. (1977). “Markets and Other Allocation Systems in History: The Challenge of Karl Polanyi.” Journal of European Economic History, 6: 703–16. Perkins, E. J. (1994). American Public Finance and Financial Services 1700–1815. Columbus: Ohio State University Press. Portes, A. (1995). “Economic Sociology and the Sociology of Immigration: A Conceptual Overview,” in A. Portes (ed.), The Economic Sociology of Immigration. New York: Russell Sage, 1–41. Powell, W. W. and DiMaggio, P. J. (eds.) (1991). The New Institutionalism in Organizational Analysis. Chicago: University of Chicago Press. Preda, A. (2009a). Framing Finance: The Boundaries of Markets and Modern Capitalism. Chicago: University of Chicago Press.

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——— (2009b). “Brief Encounters: Calculation and the Interaction Order of Anonymous Electronic Markets.” Accounting, Organizations and Society, 34: 675–93. ——— (2009c). Information, Knowledge, and Economic Life: An Introduction to the Sociology of Markets. Oxford: Oxford University Press. Rosenbaum, E. F. (2000). “What is a Market? On the Methodology of a Contested Concept.” Review of Social Economy, 58: 455–83. Sassen, S. (2001). The Global City (2nd edn). Princeton, NJ: Princeton University Press. Schutz, A. (1964). Collected Papers II: Studies in Social Theory, ed. and intro. Arvid Broodersen. The Hague: Nijhoff. Scott, W. R. (2001). Institutions and Organizations (2nd edn). Thousand Oaks: Sage. SEC (U.S. Securities and Exchange Commission) (2010). “The Laws That Govern the Securities Industry.” (accessed September 21, 2011). Shapiro, M. M. (1985). Foundations of the Market-Price System. Lanham: University Press of America. Shiller, R. J. (2000). Irrational Exuberance. Princeton, NJ: Princeton University Press. Slater, D. (2002). “From Calculation to Alienation: Disentangling Economic Abstractions.” Economy and Society, 31: 234–49. Smelser, N. and Swedberg, R. (eds.) (1994). Handbook of Economic Sociology. Princeton, NJ: Princeton University Press. Smith, C. W. (1999). Success and Survival on Wall Street: Understanding the Mind of the Market (rev.edn). Lanham, MD: Rowman & Littlefield. ——— (2007). “Markets as Definitional Practices.” Canadian Journal of Sociology/Cahiers canadiens de sociologie, 32/1: 1–39. Strange, S. (1994). States and Markets. London: Pinter. Swary, I. and Topf, B. (1992). Global Financial Deregulation: Commercial Banking at the Crossroads. Cambridge: Blackwell. Swedberg, R. (2003). Principles of Economic Sociology. Princeton, NJ: Princeton University Press. Sylla, R. A. (1998). “US Securities Markets and the Banking System, 1790–1840.” Federal Reserve Bank of Saint Louis Review, 80: 83–98. ——— Wilson, J. W., and Wright, R. E. (1997). “America’s First Securities Markets: Emergence, Development and Integration.” Paper presented at the Cliometric Society Meetings (Toronto), May 1997 and the NBER Summer Institute, July 1997. Taylor, J. B. (2009). Getting Off Track: How Government Actions and Interventions Caused, Prolonged, and Worsened the Financial Crisis. Stanford: Hoover Institute Press. Uzzi, B. (1999). “Embeddedness in the Making of Financial Capital: How Social Relations and Networks Benefit Firms Seeking Financing.” American Sociological Review, 64: 481–505. White, H. C. (2002). Markets from Networks: Socioeconomic Models of Production. Princeton, NJ: Princeton University Press. Williamson, O. E. (2000). “The New Institutional Economics: Taking Stock, Looking Ahead.” Journal of Economic Literature, 38: 595–613. Zaloom, C. (2006). Out of the Pits: Traders and Technology from Chicago to London. Chicago: University of Chicago Press.

chapter 7

auctions a n d fi na nce c harles w. s mith

Introduction This chapter has four main interconnected objectives: (1) to provide concise, descriptive, sociologically informed accounts of financial markets and auction markets with particular attention to their interconnections, similarities, and differences. These accounts will be grounded primarily on extensive ethnographic and participant observation research that will highlight how participants experience these various markets;1 (2) to illustrate the central role that “pricing”2 plays in both structuring and validating these markets; (3) to examine the different ways in which market narratives and practices mold pricing; and (4) to review some of the various changes associated with technological developments and globalization that have transformed these markets including the way they price. We will begin with a few brief vignettes. (I) It is mid-morning on a Tuesday in early August and Professor Elaine Bradley is on the telephone from Florida with her long-term financial adviser and broker in Philadelphia discussing the upcoming ten-year treasury note auction. She has decided to move a large portion of her retirement funds, presently in stocks, into government fixed-income securities. They have agreed that she should invest these sums in sevenyear and ten-year treasury notes. They are discussing how much to put into each and whether she should enter competitive or noncompetitive bids, as well as the prices and amounts for the competitive bids. (II) Meanwhile, Henry Comstead is trying to block out the noise about him coming from the chatter of the other traders sitting around him in their London office in order to focus his attention on the three computer screens in front of him as he contemplates initiating a short-term three-way arbitrage of euros, dollars, and sterling.3 The pound is clearly being traded at a discount to the dollar as compared to the euro, but its spread is larger than normal and jumping around. Time to contact Switzerland and perhaps New York if he can get through to his buddy there.

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(III) The atmosphere is quieter and calmer for Ellen Garden and Max Stein as they sit in front of their screens in their Greenwich office. As comanagers of a small hedge fund working primarily with endowment funds from various nonprofit institutions, they are partial to making long-term equity investments. They have been long-term holders of IBM stock and have recently been adding more shares to most of the portfolios they manage. The stock has opened off this morning, and while Ellen is monitoring a score of limit-buy orders that they have entered, Max has his finger on his “trade” button as he has simultaneously been entering various market orders for the same accounts. After ten years in the business, they still debate the relative strengths and weaknesses of market versus limit orders. (IV) The atmosphere is equally quiet and calm as Jerry, with a cup of coffee in hand and still in his pajamas, flips on his computer in Arizona. As a retired broker and trader with over 50 years’ experience in the stock market, Jerry continues to watch and trade the market. For the past ten years or so he has pretty much limited his trading to options of highly diversified, index-based instruments.4 Individual stocks make him nervous. He has been watching the market slide for a few days and feels that it should be ready for a lift of some sort. With the market holding steady, he is contemplating putting on a 2-by-1 ratio call spread on the QQQQ,5 providing it was wide enough, sufficiently up and away, and could be done for no cost. Even then if the QQQQs exploded up, he would be at risk. A 2-by-1 ratio put spread ten points down would be simpler and much safer. A simple 1-by-1 ratio call spread would be even safer, but would cost a fair amount. It is usually a nice, tight market, but the volatility is such that you can always get burnt with market orders. What to do? How to know? “What to do? How to Know?” All the actors presented in these vignettes, not just Jerry, are faced with making decisions and taking actions. While situated in different places, involving diverse populations, and revolving around different types of financial instruments, the four vignettes share other things in common. All four are grounded in a financial market, and all are auction markets to one degree or another. The particular type of financial market, however, varies from one vignette to another, as do the particular auction components. That is not surprising given that auctions— markets in which goods and/or services are monetarily priced6 and allocated through some form of open, competitive bidding among buyers and sellers—and financial markets—markets that deal with particular financial instruments—have a symbiotic relationship reaching back to the early Greeks and Romans (Bang 2008; Chancellor 1999; Smith 1989). This symbiotic relationship has both become more intense and undergone changes during the past 40 years, due in large measure to the dramatic growth and visibility of financial markets; this growth has itself been related to globalization, particularly economic globalization, and technological advancement, particularly in the areas of computerization and the Internet. These developments provide a rich data source for exploring these overlapping markets and their relationships. In order to properly grasp what has been occurring, however, it is necessary to describe each in more detail.

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Auction markets Auction markets are commonly named in terms of the items auctioned (as in horse auction, art auction, house auction, tobacco auction, fish auction), but what defines them as auctions is not what is auctioned but rather the rules and practices that govern the ways items are priced and allocated. It is these rules and practices that distinguish an auction, whatever particular form it may take, from what are commonly called fixed-price transactions and private-treaty transactions (Cassady 1967; Smith 1989: 14–19; Smith 1993). In fixed-price transactions, which characterize most retail sales, sellers set the price, which buyers can either accept or not. If these fixed prices fail to garner buyers, the seller is apt to lower these prices, but the prices are not negotiated with potential buyers. This is how most stores, be they food supermarkets, department stores, or neighborhood drug stores, operate. While not part of the actual transactions, the acceptance of fixed prices is itself grounded on the implicit assumption that the prices have been established according to some rational legitimate principles. The situation in private-treaty exchanges such as those in a flea market is quite different. In these situations, the buyer and seller actively negotiate the price. Most people recognize this system as bargaining. The seller may offer an item at one price; the buyer may counter with another, lower price until a mutually agreed-upon price is established. While the price is the focus of such bargaining, the discussion tends to extend over a wide range of factors pertaining to the item for sale, the resources of the buyer, costs to the sellers, and other things that each party hopes will either increase or decrease the price of the item. Though privatetreaty transactions seldom rely upon the implicit assumption of “fair pricing” that operates in fixed-price transactions, they normally minimally require some shared criteria for evaluating some aspects of the items; without some common grounds for evaluating the item, such transactions will not be executed. Auctions differ from both fixed-price and private-treaty systems in the comparative absence of applicable principles and criteria of evaluation for establishing prices in a particular circumstance. This often reflects a broader ambiguity regarding the criteria and principles for defining and classifying the item(s) being auctioned. The system works somewhat in reverse of the process used in fixed-price and private-treaty exchanges. It is the price determined by the competitive auction bidding that serves to underscore and identify what criteria and principles—a certain quality, scarcity, size, or other trait—apply. Prior to the actual auction, it was generally assumed that the price of Jacqueline Onassis’s imitation pearl necklace would be perhaps twice the normal price of similar used imitation pearl necklaces, given that it once belonged to Jacqueline Onassis. When it sold for 20 times this price, however, the auction had determined that Jacqueline Onassis’s ownership, and consequently celebrity ownership in general, was worth considerably more than a doubling of the normal price. While both fixed-price and private-treaty forms of pricing and exchange allow for price adjustments in response to market conditions, they lack the public competition and social interaction among

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buyers and sellers in which price is determined by what is offered and accepted. The term auction is used specifically to refer to such price-governed, public, competitive transactions. While all auctions have the capacity to reframe the way items are priced and evaluated, they vary considerably in the ways they implement the competitive, public pricing practice that they all employ. Auction bidding can be categorized by two major features: (1) the form in which bids are made (written, visual or oral), and (2) the sequence rules for bidding (bid increases, bid decreases, or simultaneous bidding) (Smith 1989: 16–18). Though written, sealed-bid auctions are very common, the word “auction” indicates for most people a mixture of oral and visual bidding with bids increasing. What is normally considered critical is that participants have the opportunity to adjust their own bids in response to the bidding, or lack of bidding, by others. The “normal” ascending sequence form is commonly referred to as an English auction. The familiar cry, “I have ten dollars, will you say twenty? I have twenty, now thirty, . . . forty, I have fifty . . .” is the cry of an English auction. In Dutch auctions, a descending sequence is used. Here the auction begins with the item offered at a high price, usually too high for there to be any bids. The price is then dropped sequentially by some established quantity until a bidder accepts the offer. Such auctions are used primarily where there are many similar items for sale, as is the case in the traditional Dutch flower auctions from which the title is derived, and where the first winning bidder is allowed to select which of the items she wants. This process is commonly referred to as “preference and choice.” The bidding then continues to the remaining items at the last price at which the winning bid is allowed to exercise the right of “preference and choice” until all goods are gone. There are other auctions in which bids are made simultaneously at different prices. Most “sealed bid” auctions function this way insofar as all bids are opened and entered “collectively,” though they may have been submitted at different times and even actually opened at different times. There are other auctions where such simultaneous, or minimally overlapping, bids are made orally or by signs, which allows other bidders to adjust their bids in response. Such bids, depending upon the particular auction, may represent offers to sell or to buy. In these situations it is generally the responsibility of other participants to accept bids with the “auctioneer” or “market-maker” certifying and recording each transaction. It is further understood in these auctions that all bids exist only at the moment they are made. If not immediately accepted, they cease to exist. As with Dutch auctions, this auction format is primarily used in auctioning a series of similar goods, where multiple sales occur together and sequentially. In this way the bidding in each transaction feeds into that of the next transaction, creating a type of price sequencing across transactions. Where English auctions tend to dominate in the sale of one-of-akind items such as fine art, thoroughbred horses, and collectibles, and Dutch auctions in a range of agricultural commodities, “simultaneous” auctions dominate most financial auctions where multiple bids and offers are commonly offered at the same time.7 Whatever the particular format of any given auction, the primary objective remains the same, namely to price and allocate given items in some form of “public,” “competitive”

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bid/ask structure. Whereas the neoclassical economic model understands this process as a means for “revealing” the preexisting preferences of the participants, a more sociological view sees such auctions as means for generating a consensual and hence socially legitimate price under conditions of ambiguity (Smith 1989: 80–107).8 Through their ability to resolve price uncertainties over a wide range of prices, auctions also serve to draw both potential buyers and sellers. When there is a general consensus as to what a particular item is worth, there is no need for an auction of any form. This relationship between ambiguous evaluations and auctions is a key factor in explaining the pervasive use of auctions in financial markets. That the prices of financial instruments, which are the items traded in these markets, should be subject to major ambiguities might, on the surface, seem minimally counterintuitive given the predominant role price plays in defining them. The problem with these instruments lies in the difficulty of getting a stable, consensual price, which is accentuated by the wide impact that these prices have in the larger economy. In short, very minor differences can have major implications. To properly appreciate these difficulties it is necessary to understand the highly abstract and complex nature of these instruments and their prices.

Financial markets Financial markets are defined differently, but they are generally understood to be markets that trade exclusively, or at least primarily, financial instruments, which are themselves defined primarily in monetary terms. The most common of these instruments are sovereign currencies, financial debts of varying types, equities, and, more recently, a wide range of “derivative” instruments linked to such items. These derivatives are generally constructed in the form of “options” or “futures,” which entail various contractual rights and obligations to the underlying financial instruments to which they are tied. While the great majority of financial instruments are primarily traded through exchanges, many are also traded through over-the-counter (OTC) markets in which buyers and sellers negotiate directly with each other. This is particularly the case with currency transactions, including currency derivatives. Such transactions conform more to the “private-treaty” format than the public “auction” format and tend to be limited to very large transactions between large financial institutions, transactions that are highly informed by reigning exchange prices. Most other financial markets, such as equity, bond, commodity, and their associated derivatives, in contrast, tend presently to be primarily exchange markets of one sort or another. While these different types of instruments are commonly traded individually, they are often linked to each other in a variety of ways, as is the case when particular currencies entail precious metal guarantees or bonds entail rights to buy stocks at particular prices.9 Financial instruments of different sorts are also commonly linked through various arbitrage strategies. Whatever these links might be, each instrument is assigned its own monetary value in its own market(s).

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Though financial markets are defined primarily in terms of what they exchange and auctions in terms of how they exchange, they share one key thing: they are both primarily focused on how items are priced and allocated, with primary attention on pricing. The ability of auctions to generate consensually legitimate prices in highly ambiguous situations has bestowed upon them primacy in this area theoretically, practically, and legally. As such, it is not surprising that auction formats have served to mold practically all financial markets, where ambiguities, uncertainties, and price prevail. These uncertainties and ambiguities are linked to the significance and weight of a range of constantly changing, often opaque, factors normally at play in the pricing of the items. Such uncertainty plays a negligible role in most fixed-price transactions and a lesser role in most private-treaty transactions due to the shared acceptance of a broad spectrum of narratives that serve to locate the objects in a manner that enables them to be consensually priced. While a range of narratives can generally be identified as pertinent to most financial and nonfinancial auction markets, they seldom are capable, in practice, of generating agreement on prices; interpretive differences bearing on all sorts of factors commonly persist. The ability and genius of auction formats is that they reverse the process by seeking to attain an agreement on price that can then be used to generate a range of more concrete narratives that are consistent with this price (Smith 1989: 162–84). The monetary price determined in the auction functions as the perfect evaluative “fudge.” The “fudging” capacity of monetary prices is directly related to their innate abstractness noted by Simmel ([1907] 1990: 120): money as a pure, abstract measure of worth can combine the various qualities that might pertain to the item. Prices speak to one facet only: economic/monetary value. As such they are able to subsume under their umbrella a wide range of different subjective and personal values and the various complex narratives that weave these preferences together. Though both financial auction markets and nonfinancial auctions are primarily concerned with prices, they tend to frame these prices in different ways. This difference in framing is due primarily to the significant differences in the ways financial instruments and nonfinancial instruments are embedded in the world. In nonfinancial auctions, contexts, uses, history, and other factors that locate items in the concrete world are generally recognized as relevant to their price. There need not be, and generally is not, a consensual agreement as to the specific contribution of these facets in pricing, but they clearly are seen as related to and relevant to the price. Financial auctions and financial instruments differ insofar as they tend to be more self-referential. While financial instruments are also embedded in the world and, as such, also affected by external factors, their monetary value is nearly always highly dependent upon the various rights and obligations built into each instrument that filters these factors. Put slightly differently, prices in nonfinancial auctions tend to be linked to outward-oriented narratives whereas prices in financial auctions tend to be more linked to inward-oriented narratives. Clearly, external happenings play a role in how these instruments are priced, but these happenings are processed through the rights and the responsibilities of the instruments themselves in a way that seldom occurs with nonfinancial items. As such, with

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financial instruments, it is more likely for happenings to be perceived as changes pertaining to the rights and obligations of the financial instruments themselves rather than external changes per se that affect their prices. In the highly abstract world of financial instruments, rights and obligations tend to pertain primarily to the “return” and “risk”10 that a particular instrument entails. Financial instruments have no utility beyond that as financial instruments. They cannot be turned into goods. As financial instruments they can only be held for their financial return or exchanged for some other financial instruments, which likewise can only be evaluated and priced in terms of their return and risk. There was a time when the currencies of certain nations were guaranteed or minimally “backed” by precious metals, usually gold or silver, but in recent decades the face value of a particular currency is only backed by its government to be worth its face value in that currency. While historically different currencies were commonly linked to each other according to a fixed ratio set by their respective governments, in recent years these ratios have been determined in currency markets open to major banks, including government banks, and large private participants. Nearly all non-currency financial instruments are issued in association with a particular currency and their prices are measured in terms of this currency. These prices, in turn, are determined within the markets that they are traded in. How this is done is, of course, the grand secret of the market, which continues to baffle in varying degrees all those who have tried to unravel it. What can be said, however, is that two factors continue to play a central role in how these prices are determined: the expected comparative return on capital and the expected comparative risk of loss. Theoretically and empirically grounded opinions and judgments abound as to how they should be measured and combined to generate proper prices. Nevertheless, there is little overall agreement on how these factors should be weighted in any given moment. Similarly, there are differences of opinion on how proper prices should be determined in nonfinancial auctions where relevant parameters tend to be more concrete if also more numerous, covering such things as “uniqueness,” “quality,” “rarity,” “provenance,” and even “lineage” and “genius” in some instances. In the end, however, one judgment tends to dominate in financial markets, and that is the judgment of the marketplace.

The impact of narratives and practices on pricing While financial markets are defined in terms of financial instruments and auctions in terms of the rules and practices that govern the ways items are priced and allocated, they share four central characteristics: (1) they are primarily engaged in pricing the items they trade; (2) they operate under conditions of significant ambiguity; (3) they employ competitive, comparatively open and transparent bidding systems to generate consen-

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sual prices for that moment;11 and (4) they both utilize overlapping but different narratives and practices in generating prices. It is in the ways that these different narratives and practices have modified each other that the symbiotic relationship between these markets has been and continues to be played out. To properly appreciate this process, a few additional facets of both deserve attention. Narratives and practices are two of the primary vehicles and carriers of meanings, the third being minds. The two former are structured by meanings and both commonly modify these meanings. There are differences in the ways this is done not only between them, but also within each.12 In markets of all types, narratives function essentially as they function everywhere else: they provide a meaningful, ordered, and unified account of how particular events unfold. As such, they tend to focus upon those things assumed to be the causally most relevant and recognizable patterns. In nonfinancial auctions where the items being priced and allocated exist in the concrete world, the governing narratives likewise tend to focus upon concrete things such as the condition, provenance, rarity, and history of items, the attitudes and resources of buyers and sellers in general and known major buyers and sellers in particular, related transactions, and so forth. In contrast, in most financial markets, given the highly abstract character of the financial instruments traded and their global nature, self-referential narratives that focus on the assigned rights and responsibilities and hence the risks and rewards of the particular instrument tend to play a more central role. In both cases, the primary function of governing narratives, however, is to “make sense” out of what is happening by providing accounts that can be used in generating transactional prices. Market practices, for their part, also serve in generating transactional prices, but in their case the objective is to establish behaviors that foster such results. It is the implicit “mindedness” of these practices that serves to link activities together, however, rather than the more explicit “sense” of governing narratives. These practices provide nittygritty, step-by-step linked acts. Narratives and accounts provide governing overviews. A particular practice such as how an auctioneer ends a particular sale that has not reached its reserve price, and as such has resulted in a non-sale, needs to be properly linked to a range of other activities that are part of that auction. At a Kentucky horse auction the auctioneer will yell “sold” as he signifies the end of the sale by hammering down. To do this at a Sotheby’s art auction would be illegal. Such an extreme difference is due to the fact that different practices are necessary to enable the two different auctions to proceed properly.13 Narratives and practices both seek to balance and resolve factors that are apt to generate ambiguities and uncertainties that would thwart consensual pricing. How they do this, however, varies. Narratives rely upon integrative accounts that are capable of resolving or minimally fudging ambiguities and inconsistencies; practices rely upon behavioral routines to bridge what otherwise might be behavioral gaps or dead ends. While narratives and practices are both used in establishing consensual/auction prices, their importance varies from situation to situation. Not surprisingly this difference is itself related to the overall importance of narratives and practices in the pricing process. The more continuous, regular, and inclusive a particular auction market, the more authoritative and commanding are the prices generated by actual sales

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(i.e., transaction practices). In contrast, the prices of items auctioned sporadically are highly subject to the continuous flow of narrative-grounded evaluations generated by “experts” and others commentators (Smith 1989: 166–74). Financial auctions are fundamentally commodity auctions, which tend to be the most continuous, regular, and inclusive, and, as such, are markets in which transactional prices are quite universally accepted as “the” price. In less inclusive and regular auctions—collectible and one-of-akind auctions—a given market price may be seen as a market aberration of some sort and be overridden by a narrative price of one sort or another.14 In the context of this book, it is worth noting that though narratives and practices generate prices differently, both types of prices are socially generated. This is fairly obvious in the case of narrative-generated prices given that narratives are socially constructed accounts. Prices generated through the auction practices of the offering and accepting prices are equally social insofar as they not only involve a plurality of participants, but also entail their tacit acceptance, even if silently given; they do not contradict the price with another bid. This social component is not only central in generating prices, but also crucial in legitimating prices. It is their social pedigree that enables them to be accepted collectively, if only momentarily. Individuals are incapable of generating a price without an “other”; for the price to be seen as a “correct” price, a community of some sort is nearly always required. In recent years the exponential growth of financial auction markets has been marked by a number of transformative developments in the ways in which auction and financial market narratives and practices have influenced each. Unfortunately, the multifaceted, quite irregular history of these interplays thwarts a simple accounting. Hopefully a few concrete examples will provide a glimpse and taste of how they have shaped each other in recent years and some of the implications for the future.

Payback: pedigree for procedure As indicated earlier in this chapter, the growth of financial markets could arguably be credited in large measure to their adoption of fundamental auctioning procedures.15 It was by and large a one-way transaction. In recent years, however, financial markets have figuratively repaid various auction markets, particularly what are often referred to as high-end sales auctions such as Sotheby’s, Christie’s, and even Keeneland. They have done this by standardizing and legitimizing auction-pricing procedures to the level whereby such prices, whatever their fluctuations, are accepted as denoting “fair value.” Whereas traditional auction procedures emerged and evolved haphazardly in a wide range of nonfinancial markets, within financial markets, as a result of their central public and economic weight, these procedures have been legalized and formalized. Coupled with the growth, breadth, depth, and regularity of different financial markets, auction pricing has acquired a legitimacy that transcends that which it had within specific nonfinancial auctions, which generally tended to be more closed, more opaque, and less continuous.

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Financial markets, as such, served to equate “auction-priced” with “legitimately priced.” A corollary of this has been that various auction-priced items, such as paintings, antiques, racehorses, and collectibles previously not seen to be inherently financial in nature, have been able to acquire the pedigree of being financial instruments. It might be said that auctions bestowed financial markets with auctioning practices, upon which financial markets generated a narrative of legitimacy and liquidity that was embraced by various auction constituencies, enabling them to relabel their merchandise. Relabeled as financial instruments, these items cannot only be bought and sold but also traded. They can also be valued for the assumed liquidity they provide by being tradable. Objects that once were owned for the pleasure they might provide can now be used as investment and speculative instruments as well as commission-generating objects for others. It is not surprising, therefore, that the ability to price and trade various new and often quite exotic financial instruments has spread beyond the financial world. An object that is auctioned, priced the way financial instruments are priced, and augmented with past volatility data, risk analysis, and market liquidity can be treated as a financial object. What better objects for this new identity than paintings and antiques that have not only been collected as precious possessions, but have been subject to auction sales for centuries? It is not surprising to learn, therefore, that art objects of varying sorts have for some time now been acquired more as financial investments than as art objects, with gallery owners and art connoisseurs serving as agents (Coslor 2010; Velthuis, this volume). The same can be said for a wide range of collectibles and other items. If something can be consensually priced and packaged as a financial instrument, it can generally be treated as a financial instrument, a process commonly referred to as “financialization” (Krippner 2005). The growth of financial markets has given numerous more traditional auctions a whole new persona. Given the discontinuous nature of the markets for these items, their liquidity, critical to most financial instruments, remains dubious.

Repackaging versus relabeling: from practice to narratives While auctions, drawing upon financial market rhetoric, have succeeded in marketing a range of items as financial instruments, financial markets have succeeded in adopting a comparable (insofar as it modifies the way items are perceived) innovative marketing procedure traditionally limited to auctions: repackaging. For auctions, which commonly deal with a variety of items, repackaging—the practice of separating and mixing items—has proven to be a successful practice by highlighting particularly choice items or combining items in a manner seen to compliment each other. Such changes in the composition of what is being auctioned can also serve to alter the mix of bidders, which can, in turn, generate greater competition and prices.

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In contrast, financial markets have tended traditionally to deal with only one kind of financial instrument, be it equities, bonds, or currencies. Perhaps more importantly, auction repackaging evolved as an extemporaneous practice rather than as a theoretical design; different auctioneers in different situations engaged in this practice and found that it often worked. Such informal, often spontaneous, modifications in managing transactions are contrary to the image that financial markets have sought to generate. For innovative mixing and separating to be acceptable, there would need to be an appropriate narrative.16 In recent years such narratives have emerged, which explains in large measure why financial markets have enthusiastically embraced repackaging in which they historically showed little interest. One such narrative, which speaks primarily to mixing and grouping financial instruments, revolves around “diversification” and its relationship to “risk” and “participation.” Diversification and repackaging are linked to each other by virtue of the fact that both entail reorganizing the composition and mix of the items being priced and exchanged. Whereas repackaging in and of itself is primarily a practice, diversification grows out of a governing narrative.17 Although repackaging tends to occur as separate behavioral adjustments to particular situations, it becomes part of an overall investment strategy when linked to a diversification narrative. By mixing instruments together one can provide a wider participation in different markets; by increasing the diversity of the composite instrument one can also claim that risk is better managed, or at least that is how the narrative goes. From the perspective of those generating these repackaged composite financial instruments, there is the added benefit of having additional products to market. As a rule, the more products, the more transactions, the more transaction fees in one form or another. It should come as no surprise, therefore, to realize that this has been one of the, if not the, central development area within financial markets over the past few decades. It began with a wide range of mutual funds that sought to combine various stock portfolios, and quickly expanded into mixed equity and bond funds, index funds, and a multitude of proprietary financial instruments. In recent years we have seen the introduction of numerous exchange traded funds (ETFs), and more recently exchange traded notes (ETNs). Many of these funds have themselves been mixed together to generate funds of funds. Layered funds have also been created mixing short-term, mid-term, and longterm bond funds together. Numerous mixes have been generated to serve as retirement vehicles that are intended to adjust the equity and bond mix as well as the degree of risk over time to match the perceived requirements of the owner. While the mixing and grouping of distinct financial instruments has changed the financial world significantly, these changes pale in comparison with the transformations that have occurred as a result of the algorithmic increase in the separating or splitting of traditional financial instruments into discrete parts through the advent and use of financial derivatives. This development has not simply generated additional financial instruments; it has given rise to new genres of financial instruments, which lend themselves to a whole range of yet other combinations. Such transformations do not occur often; something quite special is generally required. In this case what was required was a truly

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innovative and game-changing narrative. This narrative, generally referred to as the Black-Scholes pricing model, laid the foundation for separating—extracting is actually more accurate—a particular type of “financial risk” from particular types of financial instruments, though its impact clearly transcended the particular instruments to which it was intended. Moreover, it did this not solely as a narrative; it provided the framework for implementing the narrative into a practice. Each part of this innovation deserves attention.

Pricing option derivatives: a very special repackaging narrative The importance of risk in pricing financial instruments has previously been noted; the problem has been determining how to calculate it. It is not only extremely difficult to calculate the probabilities of future events occurring, but nearly impossible to identify what are likely to be relevant events. That all monetary evaluations are themselves highly abstract does not make the task any easier. It is not surprising, therefore, that monetary risk was generally assumed to be unmeasurable. The emergence of the Black-Scholes pricing model during the 1970s and 1980s and its secular blessing with a Nobel Prize in 1997 served to upend this consensus. A pricing model had been created that could price risk in the form of equity options. It is beyond the scope of this chapter to expound in detail on this model, including the various modifications made to it over the years. The essential point in the context of this chapter is that a pricing model using an innovative mathematical/algorithmic narrative linking prevailing interest rates, lengths of time involved, the price differential between the underlying stock’s present price and the option strike price, expected dividends, and equity volatility for equity option derivatives was broadly accepted. While all of the factors noted are important, the factor that clearly plays the crucial role is volatility—the annualized daily standard deviation of an instrument’s price—as it speaks most directly to the issue of price variations that constitute the risk entailed (for more detailed sociologically oriented accounts see MacKenzie 2006; MacKenzie and Millo 2003; and Smith 2007). While a major academic success, the model’s market success was even greater. By providing what was accepted as a legitimating narrative for the public trading of equity options, it transformed equity markets from top to bottom. Where previously trading in equity options was seen as little more than gambling, options now took their place alongside other rationally grounded financial instruments. The growth in equity option trading has been exponential, starting with slightly more than 1,119,177 contracts traded in 1973; 34,277,350 in 1978; 82,468,750 in 1983; 111,760,234 in 1988; 140,348,955 in 1993; 206,855,991 in 1998; 283,946,495 in 2003; and 1,193,355,070 in 2008 (CBOE 2010). Equally significant has been the evolution of the nature of the transactions accompanying this growth. Simple call (the right to buy) and put (the right to sell) options have

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been combined to generate scores of option-related transactions such as spreads, straddles, collars, butterflies, buy-rights, and even more exotic mixes. Moreover, these derivatives have been combined with more traditional financial instruments to create yet other innovative financial instruments such as the ETNs mentioned earlier. One particularly heavily traded ETN that itself focuses upon the volatility of volatility is the VXX, which reflects the degrees of complexities, often nearly impossible to follow, that these new instruments can entail.18 And there is, of course, an active option market on the VXX itself, if the VXX seems a little too concrete for you. Something else relevant to the themes of this chapter, however, accompanied this exponential growth in option transactions. The pricing practices initially derived from the Black-Scholes pricing model underwent their own transformation. Practice subsumed narrative, which constitutes the second half of this innovation.

From historical volatility to implied volatility There is considerable debate regarding exactly how “volatility” was intended to be understood in the Black-Scholes pricing model. It is clear that in the model historical volatility—the annualized daily standard deviation of price from the daily mean of the underlying stock—is used. Whether historical volatility was intended only to serve as a proxy for future actual volatility can be debated. However one may elect to modify the basic model—and it has been modified in all sorts of ways—the model was intended to support the view that options could be rationally priced and hence rationally traded by the proper weighting of price fluctuations and a range of other factors such as time to expiration, dividends, and fixed income return. The market supported this view as it sought to gain approval of options as legitimate trading vehicles. Within the market, however, volatility took on a significantly different persona: it became implied volatility. Rather than reflecting past volatility, it sought to capture future volatility. To do this, current option prices were used to calculate volatility values. Rather than past historic volatility telling us what current market options prices should theoretically be, current market option prices are telling us what the market, or more specifically market sentiment, believes future volatility will be. The growth of derivatives and the morphing of historical volatility into implied volatility has transformed financial markets, particularly equity-grounded markets, in a number of significant ways. The existence of a plurality of linked financial instruments, puts, calls, futures, and a variety of index funds, has created a situation in which any given transaction can be offset by a range of other transactions. As such it has become extremely difficult, if not impossible, to interpret most market movements, even for market insiders who historically were often capable of doing so. The great majority of market professionals accept this and, as a consequence, are more prone to maintain

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more market-neutral positions. The growth of derivatives, meanwhile, has enabled market participants to offset their overall market positions, be they highly bullish or bearish, by buying and selling market volatility directly by means of VIX- or VXX-like instruments of one sort or another. As such, volatility has itself become a major, if not the major, commodity being traded in various financial markets. What is of particular significance in all of these developments is that a range of market practices has altered a narrative that was intended to govern these practices. The ascendancy of market practices over theoretical models offers a cautionary note to “economic performativity theory,” in which financial accounts prescribe what happens rather than describe what is occurring in markets (Callon 1998; MacKenzie, Muniesa, and Siu 2007). As a sociologist, fully accepting the power of narratives to mold behavior, I am sympathetic to this claim. Financial markets, however, particularly those subject to implied volatility, would indicate that practices also have causal powers to modify narratives. The growth of technology, particularly computer technology, has played a significant part in this in its impact on both market practices and narratives.

The impact of modern technologies on market narratives and practices Auction markets, particularly financial markets, have become reliant on modern computational and communicative technologies over the past few decades. These technologies enable participants around the world not only to monitor multiple markets simultaneously but also to execute transactions with each other in split seconds. They enable complex multileveled transactions that would have been impossible to manage previously. Without this technology, multimillion-share transaction days would be impossible, as would be the international and national networks linking buyers, sellers, and market-makers. Without handheld computers capable of instantaneously calculating volatility figures in accordance with various pricing models, most derivative markets could not exist in anything like their present form. In acknowledging the transformative capabilities of these technologies, it is important to recognize the extent to which they have entailed both narrative and behavioral/practice functions. They do so, however, in fundamentally different ways than humans. Computerized narratives are not governed by basic themes continually being woven together in an attempt to cover and unify streams of information, as are most ongoing human narratives. Computerized narratives are governed algorithmically; each new input is algorithmically decoded and processed in a manner that contributes to how further inputs will be entertained. Computerized practices operate similarly. In fact, computerized algorithmic narratives and mechanical processes mirror each other as two sides of the same coin. The process by which a decision is made to buy a particular

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instrument at a particular price is the same process that executes that decision. Narrative and practice are, for all practical purposes, merged into a single process. Notwithstanding the speed, calculative powers, and reach, there is a crucial element missing in how the most cutting-edge computer manages even quite simple market transactions. What is missing is the social component noted earlier, which is intrinsic to all human narratives and auction transactions. Computers cannot “take the role of others” (Mead 1934: 135–44), nor can they interpret information (Collins 2010: 25–31, 125–6). Computers are limited to algorithmically processing the data, or what Collins (2010) calls “strings,” with which they are provided. They are not able to understand meanings as humans do insofar as such meanings require a social context in which to be understood. As such, market computers can calculate what appear to be the “best” prices under a wide range of very complex conditions, but they have no way to determine if they are “legitimate” prices. This limitation, of course, in no way hinders the ability of these computers to generate prices. There remains, however, a very real question as to whether these prices are endowed with the “legitimacy” that auction-generated prices have historically been assumed to have, given that they lack the implicit social consensus associated historically with such prices. There are various indications that this question, especially when linked to the type of “flash crash” that occurred on May 6, 2010, has become a growing concern of various market constituencies. How broadly and how deeply this concern might become or how seriously it should be taken is hard to judge. Nevertheless, it deserves our attention. Financial markets have played a central role in the emergence and success of modernity and the democratic and rational principles that have been associated with modernity. A key factor in this has been their auction pedigree, which enabled them to forge broad consensuses regarding worth and price where more established traditional social and cultural ideologies could not. Given the developments described above, we may be witnessing a transformation in the way these markets function, whereby social consensus, be it narrative or in practice, gives way to algorithmic decision-making.

Notes 1. Given its primary reliance on ethnographic type data, this chapter draws heavily upon the author’s own participant observation research. For a taste of some other, often overlapping and sometimes quite different, perspectives bearing on financial markets see Abolafia (1996), Baker (1984), Beunza and Stark (2003), Callon (1998), Fligstein (2001), MacKenzie (2006), MacKenzie and Millo (2003), Stark (2009), White (2002), and Zaloom (2006). 2. Pricing is deliberately placed in quotes in order to distinguish this process from its twin sister process of “valuing.” The two processes commonly mirror each other as prices are generally seen to be quantified monetary measures of value. In placing pricing in quotes, I am attempting to restrict the process to the assignment of a monetary value, ignoring issues bearing on possible underlying valuations. Hopefully, the reasons for this distinction will become evident as the chapter proceeds.

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3. Such screens and the computers to which they are attached play a very significant role in modern financial markets (Knorr Cetina 2003; Knorr Cetina and Bruegger 2000, 2002). It is an issue to which this chapter will return. 4. Equity options are “rights” to buy (calls) or sell (puts) particular stocks or other equity financial instruments at a particular price (strike price) within a particular time period (expiration date). See note 5 for more detail on index funds. 5. The QQQQ symbol stands for the shares of an EFT, referred to as the Qs, that mirror/ track the NASDAQ 100 index. EFTs and other similar financial instruments will be discussed in greater detail later in this chapter. 6. While it is theoretically possible to “price” goods and services in a variety of different ways (e.g., “Grandma will give you the chocolate for a big hug”), pricing is generally understood to mean monetary pricing. Unless otherwise stated, this is the way “pricing” is used throughout this chapter. 7. There are a variety of other auction types, including Vickrey second-highest bid price auctions. While the high bid has historically not only been the winning bid but also the price paid in most auctions, in a Vickrey auction, which various auctions have adopted, the high bid wins but pays the second highest price. For a fuller discussion of this issue see Smith (2007). 8. That meanings and values are socially constructed is one of the core principles for the great majority of sociologists as it is central to the grand visions of Durkheim (1933), Mead (1934), and many others. It might be noted that it is also central to Wittgenstein (1953). 9. It is worth noting that while currencies of all sorts are commonly part of these other transactions, be they stock, bond, commodity, or derivative transactions, currency-to-currency transactions tend, for reasons noted earlier, to occur in OTC markets. 10. The use of the term “risk” is itself somewhat contentious as it is commonly used in two quite distinct ways. In both cases, the underlying factor is an unusual or unexpected event that has a direct impact on the value of the thing. For some people, however, “risk” denotes an unexpected event that has a calculable probability. For others it refers simply to an uncertainty. This distinction is generally credited to Frank Knight (1921), who argued that while casinos were subject to risk, economic life was subject to uncertainty. Somewhat ironically, the dominant economic view today is that financial markets are primarily subject to risk. For another more concrete perspective on the role risk plays in financial markets see Smith (2005). 11. The major exceptions to such “open, competitive” bidding are OTC currency markets, as discussed earlier. 12. Given that all practices embody narratives to some degree and all narratives entail practices of some sort, the demarcation line between them is sometimes quite hazy. 13. The reasons why it is “legitimate” to claim “sold” in the horse auction and not the other auction is that there are other sales yet to occur involving the same sire, buybacks by owner are allowed, underbidders’ identities are made public, and the overall expectations of buyers and sellers differ (Smith 1989). 14. While practically all prices are hybrids to some degree, being both narrative-generated and practice-generated price, most fall clearly into one camp or the other as narrative/ practice relationships are seldom balanced. 15. As noted earlier, not all financial markets are, strictly speaking, auction markets. This is not only true of most currency markets, but also of a range of various debt markets including debt-derivative markets. As such, these markets are really not included in the discussion that follows.

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16. For a more detailed account of the way narratives work in stock markets, perhaps the premier financial markets, see Smith (1981, 1999). 17. The economic, financial, investment, and sociological literature dealing with diversification has become a growth industry all by itself, as even a very brief Google excursion will reveal. 18. The VXX is constituted by a daily rolling long position in the first and second month of futures contracts of the VIX, which is itself an index of all of the options of all of the stocks that make up the S&P 500.

References Abolafia, M. Y. (1996). Making Markets: Opportunism and Restraint on Wall Street. Cambridge, MA: Harvard University Press. Baker, W. E. (1984). “The Social Structure of a National Securities Market.” American Journal of Sociology, 89: 775–811. Bang, P. F. (2008). The Roman Bazaar: A Comparative Study of Trade and Markets in a Tributary Empire. Cambridge: Cambridge University Press. Beunza, D. and Stark, D. (2003). “Tools of the Trade: The Socio-Technology of Arbitrage in a Wall Street Trading Room.” Industrial and Corporate Change, 13/2: 369–400. Callon, M. (1998). The Laws of the Market. Oxford: Basil Blackwell. Cassady, R., Jr. (1967). Auctions and Auctioneering. Berkeley and Los Angeles: University of California Press. CBOE (Chicago Board Options Exchange). (2010). Annual Market Statistics, (accessed July 7, 2011). Chancellor, E. (1999). Devil Take the Hindmost: A History of Financial Speculation. New York: Farrar, Straus & Giroux. Collins, H. (2010). Tacit and Explicit Knowledge. Chicago and London: University of Chicago Press. Coslor, E. (2010). “Hostile Worlds and Questionable Speculation: Recognizing the Plurality of Views about Art and the Market,” in D. Wood (ed.), Economic Action in Theory and Practice: Anthropological Investigations (Research in Economic Anthropology, Volume 30). Bingley, Yorkshire: Emerald, 209–24. Durkheim, E. (1933). The Division of Labor in Society, trans. G. Simpson. New York: Free Press. Fligstein, N. (2001). The Architecture of Markets. Princeton, NJ, and Oxford: Princeton University Press. Knight, F. H. (1921). Risk, Uncertainty, and Profit. Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin. Knorr Cetina, K. (2003). “From Pipes to Scopes: The Flow Architecture of Financial Markets.” Distinktion, 7: 7–23. ——— and Bruegger, U. (2000). “The Market as an Object of Attachment: Exploring Postsocial Relations in Financial Markets.” Canadian Journal of Sociology, 25/2: 141–68. ——— (2002). “Global Microstructures: The Virtual Societies of Financial Markets.” American Journal of Sociology, 107/4: 905–50. Krippner, G. R. (2005). “The Financialization of the American Economy.” Socio-Economic Review, 3: 173–208.

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MacKenzie, D. (2006). An Engine, Not a Camera: How Financial Models Shape Markets. Cambridge, MA: MIT Press. ——— and Millo, Y. (2003). “Constructing a Market, Performing Theory: The Historical Sociology of a Financial Derivatives Exchange.” American Journal of Sociology, 109/1: 107–45. ——— Muniesa, F., and Siu, L. (2007). Do Economists Make Markets? On the Performativity of Economics. Princeton, NJ: Princeton University Press. Mead, G. H. (1934). Mind, Self and Society. Chicago: University of Chicago Press. Simmel, G. ([1907] 1990). The Philosophy of Money. London and New York: Routledge. Smith, C. W. (1981). The Mind of the Market: A Study of Stock Market Philosophies, Their Uses and Implications. Totowa, NJ: Rowman & Littlefield. ——— (1989). Auctions: The Social Construction of Values. New York: Free Press. ——— (1993). “Auctions: From Walrus to the Real World,” in R. Swedberg (ed.), Explorations in Economic Sociology. New York: Russell Sage Foundation, 176–92. ——— (1999). Success and Survival on Wall Street: Understanding the Mind of the Market. Lanham, MD: Rowman & Littlefield. ——— (2005). “Financial Edgework: Trading in Market Currents,” in S. Lyng (ed.), Edgework: The Sociology of Risk-Taking. London: Routledge, 187–200. ——— (2007). “Markets as Definitional Practices.” Canadian Journal of Sociology, 32/1: 1–39. Stark, D. (2009). The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton, NJ: Princeton University Press. White, H. C. (2002). Markets From Networks. Princeton, NJ, and Oxford: Princeton University Press. Wittgenstein, L. (1953). Philosophical Investigations. New York: Macmillan. Zaloom, C. (2006). Out of the Pits: Traders and Technology from Chicago to London. Chicago: University of Chicago Press.

chapter 8

i n ter actions a n d decisions i n tr a di ng a lex p reda

Introduction Until now, the sociology of financial markets has only sporadically paid attention to how interactions intervene in trading decisions, although, to be fair, a number of recent field studies (discussed in detail in the following sections) have started to compensate for this deficit. It is also true that a number of studies have tackled these aspects in the 1990s and earlier (Heath et al. 1995; Abolafia 1996; Smith 1999). Momentum, however, has been gained only recently. The growing prominence of behavioral economics and of experimental game theory—which claim interactions as the keystone of their theoretical architecture—has made researchers even more aware of the significance of interactions in decision-making processes. We encounter thus a situation where, within the domain of finance, a classical sociological topic—that of the interaction order as sui generis domain of social life (Goffman 1982)—has been acknowledged as crucial by the social sciences, albeit with different theoretical and methodological implications. The unavoidable questions are then: What is sociology’s specific contribution to the study of decision-making in financial trading, and how can it gain a distinct voice in the conversation with behavioral economics and experimental game theory? The present chapter will try to provide an answer to these questions, based on a review of recent empirical studies. The empirical focus is on interactions and on decision-making in financial transactions, as we know them from the traditional trading floor or, more recently, from online trading platforms. For lack of space, important types of transactions such as merging and acquiring corporations, or bank loans, will not be discussed here (but see Vargha 2011). The cross-disciplinary perspective is provided by sociology, by behavioral economics, and by experimental game theory. For reasons of space and focus, only three significant topics will be discussed in more detail, and with respect to decision-making: emotions and cognition in trading; price recognition, judgment, and

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valuation; the use of models and calculations. The roadmap is as follows: the first mile or so consists of an argument about the importance of studying the interaction order. Afterwards, I will provide an overview of the relevant sociological and game-theoretical concepts, and show how the study of interactions provides sociologists with genuine analytical tools. I narrow down the focus to the set of issues enumerated above: cognition and emotions; judgment and valuation; use of models. The next segment of the journey mobilizes recent empirical studies, highlighting how the sociology of interactions has dealt with these issues, and how sociological solutions contribute to understanding the issue of decision-making. The final leg investigates how a sociological research program on trading interactions can be developed and sustained as a meaningful body of research.

Why studying trading interactions is important In his contribution to the Handbook of Experimental Economics, Alvin E. Roth (1995: 303) compared anonymous decision-making experiments with the use of glass vessels in chemistry labs. Glass vessels are apparently less volatile and do not interact with substances in the same way clay vessels do (the latter were used in chemical experiments before glass came into vogue among chemists). Roth was motivated to introduce this metaphor by a set of experimental results he had reported earlier—results had shown that when subjects were allowed to have face-to-face interactions during experiments, their decision-making was dramatically altered (more about this below). The metaphorical pair glass vessels/anonymity versus clay/face-to-face interaction was meant to underline that some features (pertaining to rational decision-making) were better captured under conditions of anonymity in the lab. Keeping volatile clay away allowed a better comparison of the bargaining decisions made by individual subjects with predictions derived from a theoretical model of optimizing gains. Nevertheless, continued Roth (1995: 303), “while there is ample reason for preferring glass to clay for conducting most experiments, this certainly does not mean that it is not interesting to study the chemistry of clays. . . . the fact that face-to-face bargaining may be difficult to study does not mean that it is unimportant . . .” This reminder, coming from a behavioral economist, indicates the opportunity for positioning sociology in a research program on decision-making in financial markets; to stay within this metaphor, “volatile” clay is ubiquitous in markets. Studying its chemistry close up can provide key insights into the building blocks and dynamics of financial transactions. Experimental economists, aware of the considerable force of interactions, may go to great lengths to keep them away from lab experiments. Sociologists, however, are concerned precisely with such “volatile” elements. In market habitats—as opposed to experimental labs—financial transactions cannot exist but as interactions. Even the

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apparently arid landscape of online, anonymous markets is brimming with interactions (more about this in the following sections). It would be completely misleading to think that market automation and electronic trading platforms have edited interactions out of financial transactions. Quite the contrary: recent studies show that electronic trading platforms are at least as rich in interactions as the trading floors of old were—only the interaction format of online environments differs from the face-to-face format. While the importance of studying interactions is broadly acknowledged—economists and game theorists being included in this chorus—we need a theoretical and methodological scaffolding to support, stabilize, and give concrete shape to this notion.

Actors and decisions in theoretical and in experimental games In the following, I discuss how game theory, on the one hand, and sociology, on the other, conceptualize market players and interactions. For game theory the primary notion is that of actors endowed with a set of well-defined properties. Among these, a key feature is the ability to make optimal choices given a finite set of resources, constraints, and rules for action. Choices are made by actors while engaging in strategic games with other participants. Generally speaking, we can distinguish among at least three kinds of games, each with various subsets: theoretical, experimental, or naturally occurring. The economists’ focus is on the first two kinds. A game is a sequentially organized, finite system of interactions involving two or more actors, a system characterized by a set of rules and constraints, a set of resources, and an incentive structure (aka a goal). That is, there must be something to be gained from a game, and while in experimental games this something is mostly equated with a monetary reward, naturally occurring games are, as we shall see, more complicated than that. At a very general level, economists see games as “a taxonomy of strategic situations, a rough equivalent for social science of the periodic table of elements in chemistry” (Camerer 2003: 3). Strategic situations in games are characterized by interactions “in which the behavior of agents is derived by assuming that each is choosing a best response to the actions of other agents” (Gintis 2009: 229). The essence of decision-making is thus seen as response choices made by actors in games (that is, response to other actions) under conditions of uncertainty. These responses do not exclusively imply competition. Cooperation is part of games too. Therefore, decisions in games are seen as sequentially organized responses and counter-responses of the players, sequences which (a) generate uncertainties and (b) determine the outcomes of the game. Uncertainty here means occurrences which cannot be exactly foretold, but which can be ascribed to a finite class of possibilities. For instance, the outcome of rolling a fair die (this specification is important) cannot be foretold, but we expect it to belong to the set {1, 2, 3, 4, 5, 6}. Actors participating in games are seen as rational, in the sense that they

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have finite classes of beliefs, consistent preferences, and constraints (Gintis 2009: 234). Based on them, actors make choices (aka decisions) at every sequence in the game, while trying to anticipate the responses of other participants. Anticipation rests on a shared pool of expectations: that is, actors in a game possess reciprocal knowledge of their skills, past plays, access to resources, and so on, and mutually adapt, so that they are able to anticipate responses as belonging to a finite class of distinct possibilities. Games are in a Nash equilibrium when “the strategy of each player is a best response to the strategies chosen by all the other players” (Gintis 2009: 35). This means that “players would adjust their strategies until no player could benefit from changing. All players are then choosing strategies that are best (utility-maximizing) responses to all the other players’ strategies” (Camerer 2003: 2). In other words, after a period of reciprocal adaptation, players in a game get to know each other’s routines, and their responses become predictable. Internalized social norms and roles are not simply constraints in a game, but also informational devices, serving to build up and consolidate reciprocal expectations (Gintis 2009: 232) and thus routinize strategies. Let us keep in mind here that this is the normative model of a game, where “volatile clay” is actually kept out—a model which can be tested in the lab (that is, under a specific social organization of the experiment, not identical with naturally occurring games). In games, then, knowledge, cognition, and information play a crucial role. Unavoidably, interactions and decisions are also shaped by these elements. Knowledge comprises the tacit elements—such as skills and routines—that allow participants to develop a shared pool of expectations. Cognition consists of the operations—observations, classifications, calculations, and memorizations—performed by players in each game sequence. Information consists of the signals players send to each other during the game (a move in a game, for instance, is a signal eliciting a response). Armed with a model of games involving participants with perfect cognition and information, it then becomes possible to devise laboratory experiments and, based on their results, study how participants deviate from the predictions of the model. Results have indicated—perhaps unsurprisingly—that participants have limited calculative abilities, as opposed to the unlimited ones postulated by the model (e.g., Camerer 2003: 167; Ricciardi 2008a: 93). These limited abilities are compounded by judgmental biases and by the stickiness (i.e., resilience) of perception frames, which shape preferences (Camerer and Lowenstein 2004:12). These latter appear as unstable and not necessarily consistent over time. What is more, when the track record of participants is part of the informational set of experimental games, reputation appears to be a significant factor in the decisions made by participants (Camerer 2003: 156). All in all, experimental games are set to show how—due to psychological imperfections—the outcomes reached by participants in laboratory games deviate from theoretical predictions about allocation. With respect to decision-making in finance, behavioral economics has focused, among other things, on judgmental biases generated by aversion to losses and on the ways in which emotions generate cognitive biases and (negatively) influence risk perception (e.g., Ricciardi 2008a: 94, 2008b: 29). These biases have been explained with respect to the structure of the human brain (Peterson 2007: 2), while emotions have been

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seen as having a negative influence on decision-making in trading (e.g., Lo, Repin, and Steenbarger 2005; Peterson 2007: 4). Experimental games have also shown that when participants are allowed to talk to each other as part of the experiment, not only is efficiency dramatically enhanced (that is, more transactions were made than predicted by the model, and more quickly), but intentional misrepresentations also emerge. Another observed feature is the tendency to reach socially acceptable outcomes—that is, to divide the incentive in a way that is seen as morally acceptable to the parties involved (Camerer 2003: 192–5; Roth 1995: 294–6). Very recently, the necessity of combining experimental with field studies has been acknowledged by experimental game theory (Gaechter et al. 2009; List 2009). Studies of communicative behavior in financial chat rooms (Lu and Mizrach 2008: 13; Mizrach and Weerts 2009: 275) have acknowledged that traders seek to influence each other all the time, while communication appears as an intrinsic feature of transactions. This is indicative of several sociologically relevant aspects: social factors such as reputations or ethical considerations play a role in the decisions reached by participants in experiments. At least as important though, from the viewpoint of this chapter, is that whenever interaction and communication are allowed in experimental games, participants happily engage in them, with significant effects. (I am not aware of any reported experimental game where participants were offered interaction and communication but turned them down.)

Interactions and decisions in naturally occurring games This brings me to the last element in the triad mentioned above: naturally occurring games, a subspecies of which are financial transactions. In naturally occurring games, interactions and communication are not bonus features, but intrinsic to the game. Despite their appearances, silent games are suffused with communication, even actionpacked. Economists have focused on studying experimentally recorded deviations from model-based predictions, deviations observed in controlled, artificially created environments, while excluding communication. Sociologists, by contrast, focus on naturally occurring games in existing institutional habitats. Since interactions are intrinsic to these games, I start by specifying their formal properties. Interactions are situational, oriented, bounded, and organized sequentially. Their situational character means that the local resources and the constraints within which they unfold are not mere external props, but definitional features of what is going on. Orientation means that participants’ actions are conditioned by the response presence of their counterparts. Response presence implies the participants’ accessibility to mutual monitoring (Goffman 1964: 135), and is mainly achieved by the temporal coordination of responses and counter-responses. Response presence can include physical copres-

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ence (in face-to-face situations) or not (in synthetic situations—see Knorr Cetina 2009); in both cases, however, the temporal coordination of action and counteraction remains crucial. In financial trading, we encounter both types of situations—face-to-face exchanges, as well as online transactions (dominant nowadays). Response presence also implies that participants in an interaction, more or less regularly, have to make known (or signal, if one wishes) their availability for action. An appropriate illustration here is that of soccer players who, through cries and vocalizations, make known to their teammates their availability for action over some spatial distance (see also Goffman 1978). The bounded character of interactions means that they are structured, finite, and defined. Interactions are structured, in the sense of being made of sequences of distinct steps, and not just of infinite repetitions of the same steps. (Interactions are not mere clockwork-like repetitions of the same routines.) “Finite” means that interactions have a limited duration: the end of an interaction strip, while not foreseeable from the start, can be both indicated and expected by participants at various steps in the response/counterresponse sequence. This means that in the interaction participants will mutually send signals about their anticipation of closure, and adapt their actions accordingly. Thus, finitude is a structural feature of interactions. The defined character of interactions means that they are ascribable to social classes of activity, an ascription achieved within the mutual engagement of participants. This defined character also implies the moral commitment of the participants to the interaction sequence, while at the same time providing them with opportunities for circumventing this commitment. This means that interaction sequences constrain to procedural conformity. In interactions, participants reciprocally send signals of conformity, among other things, as a means of keeping the counterpart in play. In strategic interactions, however, signals of conformity are not necessarily taken by participants as overlapping with intention. One can use expressions of procedural conformity in order to disguise intention. Procedural conformity can induce imitation, without automatically requiring it. There are opportunities for strategically feigning imitation, as well as for contrarian actions. This is important with respect to financial trading, and to the debates about social imitation in finance (e.g., MacKenzie 2005). The sequential organization of interactions means that: (a) they include a flow of distinct steps; (b) this flow includes a diminishing possibility of backward self-repair followed by reconstitution (it is easier to repair an immediately preceding step than steps which are further back); (c) each step in the sequence depends on the choices allowed by the immediately preceding step, and these choices cannot be specified in advance. These formal properties have some significant corollaries: first, interactions are not mere chains of foreseeable routines. Participants make selections across repertoires of routines; while these repertoires may provide a pool of shared expectations for participants, and while at any step in the interaction available choices may be restricted to subrepertoires, a specific selection cannot be foretold. For instance, even in a highly routinized greeting pair like “hello”/“hello” there are choices such as feigning inattention, not returning the answer, and so on. Such choices may violate social conventions, but they nevertheless occur. Second, interaction sequences leave room for innovations:

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that is, for choices which are not part of established repertoires of routines, and which surprise participants. In other words, uncertainties are not mere external constraints placed upon interactions, but an intrinsic feature, and a resource of the latter. Third, the requirements of signaling response presence means that participants use expressive repertoires in order to achieve this, and to convey information about the specific state of their presence, and about the specific modality of their response (Goffman 1969: 9, 1974). (For instance, somebody may be enthusiastic, or unwilling to do something, or joking, etc.) Such repertoires will then necessarily include emotional markers and qualifiers of the state of each participant. These markers and qualifiers (for example, expressions of arousal or of boredom) do not undermine the cognitive processes unfolding in interactions. Quite the contrary: they help structure, orient, and pace cognition. Having specified the formal properties of interactions and their corollaries, we need to narrow the focus on strategic interactions. Broadly speaking, a strategic interaction can be seen as a competitive assessment of a consequential situation (see also Goffman 1969: 85). More specifically, a strategic interaction involves two or more parties and is a “well-structured situation of mutual impingement where each party must make a move and where every possible move carries fateful implications for all the parties” (Goffman 1969: 100–1). “Fateful” here means consequential and uncertain. Moves are fateful with respect to subsequent countermoves, as well as with respect to the final outcome of the interaction strip. We can see games as concatenations of strategic interaction strips, where each strip is consequential with respect to the next one. (An example here is provided by soccer games, in which the end of each interaction strip will determine how the next strip starts.) In strategic interactions, signaling response presence includes conveying not only a participant’s knowledge about the move they are in, but also intentions about the next move, so that counterparts can build expectations about what is going to happen next. This signaling is done through verbal and nonverbal expressive means. Since moves carry fateful implications, and since they require expressing response presence, it follows that the expressions intrinsic to a move will be fateful too—that is, as seen by the counterpart, they will be both consequential and uncertain. In a soccer game, for instance, a pass can be a real one or a mock one; from the perspective of the counterpart, this is consequential, but uncertain at the same time. The keying of a pass (mock or real) should be deciphered from the player’s expressions (verbal and nonverbal). This, however, is uncertain, since expression and intention can be disjointed. In a game, control over expression can become a semi-autonomous subgame, in which participants compete on their “capacity for dissembling expression” (Goffman 1967: 240). For instance, in games participants can compete not only on explicit criteria and values, but also on implicit ones, such as their capacity for cunning, or endurance, or dissimulation. This moral subgame—what Erving Goffman (1967: 240) calls a “character contest”—is played with a view to influencing the overall outcome of the game by hurling uncertainties at the opponent. Hence, in strategic interactions we can distinguish between two kinds of interrelated yet not overlapping moves, which are intrinsic to the game: expression moves and action

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moves. Both types involve repertoires of routines, but cannot be reduced to preset routines (and therefore are not foreseeable). In strategic interactions, at the level of expression as well as of action, participants select across repertoires of routines; most of the time, however, sequence-specific choices are not planned and cannot be foretold. Since interactions are situational, choices are situational too. Fabrications, dissimulations, plantings, and rekeyings are among the basic kinds of expression moves used in strategic interactions (see also Goffman 1969: 58, 74; O’Sullivan 2009; Harrington 2009; Fine 2009; Harrington and Fine 2000), and emotions intervene in all of them. We remember that when experimental economists allowed face-to-face interaction in the lab, lying soon occurred. The types of available expression moves, however, depend primarily on the temporal structure of strategic interaction strips, structure that provides both a constraint and a resource with respect to availability. In other words, expression moves must be adapted to the interaction horizon, and mismatches allow counterparts to detect them. In online financial trading, for instance, strategic interactions have a much shorter span than in mergers and acquisitions of corporations; the range and character of expression moves available in the former will differ from that of the latter, with consequences for decision-making. In strategic interactions, we can distinguish among at least three types of uncertainties: natural, internally strategic, and externally strategic uncertainties. Natural uncertainties are provided by relevant environmental factors seen by participants as beyond their immediate control within the boundaries of the interaction: a sudden change in wind direction which modifies the trajectory of the ball, a power outage shutting down a trading platform, or a typing error in an electronic transaction. Internal strategic uncertainties pertain to the detecting of possible mismatches between expression and action moves, and evaluating their consequences. Internal strategic uncertainties are built-in features of interactions: (a) participants expect them to occur, while not knowing their exact sequence, combination, and timing; (b) they must be dealt with as part of the interaction. In online financial trading, for instance, a basic strategic uncertainty is whether the transactions flashing on the screen come from a human trader or from a trading robot: this is consequential for a trader’s decision-making, and has to be established as it is intrinsic to the interaction. External strategic uncertainties pertain to third-party strategic interactions, the outcome of which is seen as consequential with respect to ongoing actions or to future ones. For instance, in financial transactions, the outcome of regulatory processes, like reducing leverage or increasing disclosure requirements, is seen by traders as consequential with respect to future transactions. Such regulatory processes, however, are themselves strips of strategic interactions. Observers (including here traders) follow them and try to evaluate the consequentiality of possible mismatches between expression and action moves, while preparing moves adapted to possible new constraints. Based on these notions, we can turn now to concretely examining interactions and decision-making in financial trading. I will start here with the link between cognition and emotions, and how cognitive operations impact decision-making in naturally occurring trading games.

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Emotions and cognition in trading interactions To reiterate, the choice is between two arguments: one is that emotions, understood as arousal or excitement, are detrimental to cognitive processes unfolding during trading; the other is that emotions are intrinsic to expression moves, and as such cannot be separated from cognition in trading. Let us look at empirical evidence coming from field studies of naturally occurring financial transactions. We deal here with at least three types of situations, namely (a) face-to-face trading, as experienced on trading floors with varying degrees of technologization; (b) anonymous trading in face-to-face groups, where physically copresent traders transact with unseen partners; (c) online trading, where isolated individual traders transact with unseen partners. In contemporary financial markets, these types of situations coexist. While recent neurophysiological studies undertaken in the field have documented the biological basis of emotions (Lo and Repin 2002; see also Berezin 2005), video recordings of face-to-face trading sequences indicate that excitement and arousal do not seem to impede traders’ cognitive processes. The presence of emotions in face-to-face financial transactions has been noticed for a longer time; due to access limitations, however, very little primary data exists on this (but see Fenton-O’Creevy et al. 2011). In two recent studies, Stefan Laube (2008a, 2008b) examined recordings of a computerized trading floor where traders were copresent but traded with invisible counterparts using computer screens. Traders often used verbal and visual signs of arousal (consisting of cries, imprecations, or hand gestures) to reciprocally draw attention to changes on the trading screens and to preannounce incoming changes. In this respect, signals of emotion (for instance of anger, expressed through cries, imprecations, and expletives) do not appear to impede cognition, but rather to facilitate and coordinate basic cognitive operations, such as observation. What is more, price discovery, understood as judgment upon the appropriate response to price data (buy, sell, or do nothing), appears as a collaborative cognitive effort, not an individual one. While the social character of the traders’ cognitive processes has been highlighted by other ethnographic studies as well (e.g., Beunza and Stark 2005), the data analyzed by Laube (2008b: 39–40) show that traders use imprecations, curses, and insults in the process of decisionmaking. For instance, when prices are falling and traders have to sell financial securities they have held for some time, signals of anger are intrinsic to the decision-making process. The display of emotional signals triggers the decision, but also legitimizes it for other, copresent traders. Similar data come from investigations of online anonymous transactions, where traders act in isolation and do not know their counterparts (Preda 2009: 686, 689). One would expect emotions to be completely absent here, at least in part because there is no counterpart to witness them. The opposite is the case: even when they are alone, traders use emotional signals consisting of vocalizations, cries, imprecations, curses, and the like. This does not appear to impede or slow down trading. By using emotional displays,

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online traders achieve several things: they pace their observation of the screen; when necessary, they keep observation focused on particular transactions; they evaluate the character of a situation they are in; they encourage themselves to take a particular course of action. All in all, field data obtained from different trading environments resonate with previous, broader naturalistic evidence (Katz 1999) and point in the same direction: emotions are expression moves which (a) structure cognitive processes rather than impede them; and (b) are a part of decision-making, especially in situations where existing routines and habits prove themselves dysfunctional.

Interactions, price recognition, and classifications I have argued above that in strategic interactions, expression moves are disjointed from action moves, and that a key issue for players is to evaluate how the expressions of the counterpart relate to incoming actions. In face-to-face trading on classical trading floors, identities were an asset in expression moves designed to obtain information (e.g., Abolafia 1996; Zaloom 2006). In face-to-face transactions on classic trading floors, establishing identity is facilitated by standardized signs and signals, as well as by a process of reciprocal adaptation to the routines of the counterpart. For instance, wearing jackets of a particular color, using standardized hand signs for conducting transactions, or using standardized verbal shortcuts both restricts and channels the use of expression moves in strategic interactions. Similarly, getting used to the routines of one’s counterparts through years of trading together in the same pit makes it easier to detect fabrications or dissimulations. It also makes it easier to sanction repeated fabrications; as Mitchel Abolafia (1996) argues, face-to-face interactions provide participants with the means of detecting and sanctioning recurring opportunistic behavior. This, however, is only the case if interaction arrangements either standardize identities or tag them in an observable manner (colored, numbered jackets in the trading pit or colored and numbered T-shirts for soccer players are examples of tags). Traders use elements usually ascribed to action moves, such as price and volume data, in order to create expression moves that dissimulate their identity, or fabricate a new one. An example is the slicing up of orders and distribution of them to different brokers, so that the identity (and the intentions) of the player is not recognized. What is in fact a larger order, capable of moving the price up or down, will then appear on trading screens as smaller, unrelated orders. Another example comes from online trading platforms, where not only human players, but also algorithms (or “algos”) trade. Algorithms are pieces of software code programmed to buy or sell automatically when the price has reached a certain level, or to slice orders and post slices at specific intervals so that a larger transaction will be unrecognizable. The flashing of price and

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volume data on trading screens is thus not merely an action move, but an expression move as well. It is recognized as such by participants, who have learned how to distinguish the identity of an algo from that of an individual trader, and from that of an institutional trader as well. In the excerpt below, a nonprofessional currency trader indicates how data work as expression moves and how he recognizes identities (algo vs. individual vs. institution) from price and volume data flashed on screen while trading: You see every price and you see all of the orders and the size, so you know for instance at this price there are two thousand contracts that people want to sell, whereas at the prices above and uh . . . under there is only three, four hundred, so you know at that price where there is two thousand contracts, it’s, it’s a significant price and . . . I also have on the, on the charting stuff to add there is time and sales which tells me every trade that comes on as soon as it happens I see it, price and the size, so if it, so if I see in one minute a thousand trades with one contract, like, one after the other, boom boom boom, it’s most definitely an algorithm, which buys at this price, say, 1, 1, 1, 1 lot, 1 lot, if uh . . . sometimes you see . . . really big trades going on with a hundred, uh, a thousand, two thousand contracts that’s more likely to be a big bank offloading a big position for a client or something like that and then in between it’s just different traders, maybe hedge funds, it depends . . . some of the guys there are some of the biggest traders in the world so they have a big size as well and then you see on the ladder again at the best bid on offer, so . . . at the, at the spreads like, you see what happens there, because very often what happens is there are big players, some in hedge funds, some in uh, trading houses that umm they influence the market, so they will put for instance, they will, they will have bought a bit earlier on, uh, maybe it went up a couple of ticks and what they will do then is they will . . . umm . . . add two, three, four thousand contracts on the best bid, so people will see, wow, this guy, some guy is really into buying big size at that price, so it’s going to go up, so they, and then all these guys, small guys, they buy in, push it up and then he just, sells, shorts, versus position, he pulls his bid, so all those small guys and then they are “oh, that wasn’t real, so it’s not actually going up” and it comes crashing down and they do this over and over again so you try and spot these patterns to sort about . . . (Interview, AP, March 2010)

This points to several things: (a) in online trading at least, the search for trading opportunities goes hand in hand with the search for expression moves; (b) data is treated not only as an action signal, but as an expression too, and is used to tag identities, similar to coats and badges on the trading floor; (c) data is not treated in an atomistic way, but aggregated into patterns indicative of action moves and of social categories (including here algos). Trading decisions depend on correctly identifying the classes of participants. Other data I obtained, similar to the above, confirm that traders differentiate between classes of on-screen behavior (algo vs. individual vs. institution) and adapt their decisions accordingly. Overall, while recognizing the uncertainties associated with strategic behavior as intrinsic to the game of online trading, traders use situational resources to counter them cognitively. This can be seen as an adaptive process which,

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while tending toward equilibrium at some moments (i.e., adaptation to surprises by developing new routines), is inherently not routine-like.

Price anticipation and mutual obligations In face-to-face bargaining sequences, price announcements can have multiple features: they can test the counterpart’s willingness to engage in a transaction, maintain the bargaining sequence, provide openings for counteroffers, and signal the anticipation of closure. A study of bargaining in Chinese markets (Orr 2007) found that price offers and counteroffers performed all these functions, and that the price at which the transaction took place often deviated considerably from the opening price. Price variations in such cases can be seen not as due to different calculative procedures, but to the various functions price announcements and counter-announcements perform at different steps of the bargaining sequence. Reaching a deal at a specific price depends in the first place on maintaining the sequence; if the latter is broken too early, no transaction will take place. If the sequence is unduly extended, there will be few transactions. The more skilled a trader is in managing this sequence, without extending it too much, the better the chances are that a deal will take place. A primary feature of marketplace transactions with negotiable prices is the management of bargaining sequences (see also Heath and Luff 2007 and, more generally, on the organization of bidding sequences Heath 2012), keeping them not too short, but not too long either. Price announcements appear as an expression move designed to keep the counterpart in bargaining and to elicit counteroffers. At the same time, in marketplace bargaining price announcements provide slots for making value judgments on the products being offered, as well as on the bargaining parties. In this perspective, they have a normative character, in that they constrain the parties to commit to the sequence. A similar situation, yet with different implications, is investigated by Karin Knorr Cetina and Urs Bruegger (2002: 927–8) in their examination of global currency markets. In interbank currency markets, traders bargain through online instant messaging; deals take only a couple of seconds. Nevertheless, sequence management plays a role here too. While in marketplace transactions participants do not necessarily know each other, in interbank currency trading they do, since, globally speaking, the interbank currency market includes only a few hundred traders. Although considerably shorter than marketplace bargaining, their instant messaging too includes pricing requests which must be answered. An answer (that is, an offer to trade) is seen by traders both as a commitment to the trading sequence and as a professional obligation. Failure to honor such requests can be sanctioned by terminating the business relationship. Strategic interactions include thus a layer of semi-autonomous expression moves, which place upon participants moral constraints not codified by the explicit rules of games nor by their respective institutional frameworks.

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Using models and calculating prices Expression moves, as well as action moves, make use of material tools and instruments. In a game, a material artifact is used not only in performing an action move, but also in expressing something for the opponent (think here of how a soccer player’s use of the ball in a dribbling move expresses something to the opponent and for the public). This means that the use of tools is not neutral with respect to strategic expressions and to observers of the game. With respect to financial trading, this raises the question of how tools are used in action and expression, and what the consequences are for trading decisions. Strategic interactions in finance include using a vast array of tools: mathematical models for calculating securities prices; software codes for visualizing price movements, for signaling entry and exit prices, or for automating trades; visual displays of price and volume movements, to name but a few. Their emergence and adoption by communities of traders has been more recently discussed in the sociological literature under the banner of performativity (e.g., MacKenzie 2005; Mackenzie, Muniesa, and Siu 2007; more generally, see Callon 1998). Historical studies of model emergence and adoption need to be supplemented by contemporary field studies of uses of models in financial transactions, based on naturally occurring data. While the latter are relatively rare and works in progress, the following can be said here. First, as argued above, in strategic interactions participants use expression moves in order to identify categories of players and respond to them in a differentiated manner. This means that material tools used in such moves (here including models) are not employed in an undifferentiated manner, just because they are there, but classified according to social categories of use and of users, and put to work accordingly. Furthermore, selectivity would apply not only to categories of users, but also to categories of providers, depending on social criteria such as authority or personal trust. Second, since material tools are used in expression moves, not only in action moves, they can also be used in fabrications, plantings, or dissimulations (see also Brooke Harrington’s chapter in this volume). Indeed, media reports regularly indicate that this appears to be the case. Bernard Madoff, who ran an investment fund scam over decades, swindling his customers out of billions of dollars, faked elaborate financial statements. This would make social selectivity in the use of models even more important: before deciding whether or not to use a particular tool or model, a trader would have to decide not only whether the source is trustworthy, but whether the tool itself delivers genuine results. This requires judgment along two interrelated dimensions: character and genuineness. One could argue that in organizational settings the need to formulate such judgments is replaced by institutional controls, in the form of proprietary trading models, with restricted intra-institutional access, confidentiality agreements, and so on. However, intra-organizational trading rooms are also characterized by internal competition along expression moves, including dissimulations and fabrications, as recent cases

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have shown (think here of Jérôme Kerviel, the trader who faked trading accounts and conducted unauthorized transactions in order to improve his performance). Ethnographic observations made by myself, as well as by others (Wansleben 2010, this volume) show that traders do indeed use models in their trading decisions in a discriminatory fashion, determined by social criteria, and that decisions about how and where to use models depend on social judgments. Commercially available trading robots, for instance, may be bought but not necessarily used in trading by nonprofessional traders. Programming-savvy traders can buy robots only in order to decompile them and learn about the tricks used by manufacturers in their validation procedures: the decision to buy a robot is more an expression move than an action move. At the same time, savvy traders will develop their own models, and will build small groups of users around them, in which they retain authority over the model: other members of the group can use the model, but have little understanding about the building principles. The decision to let others use a self-developed model can be determined not only by the group members’ skills and know-how (lower than that of the developer), but also by social criteria, such as the members’ life stories or particular situations. On the institutional floors of currency markets, analysts develop their own models of currency movements, models which represent the institution but above all the analyst in her daily dealings with other analysts and with traders. Analysts use models in strategic interactions with their peers, in order to build a distinct identity and gain prestige. Overall, empirical data indicate that tools and models are not indiscriminately used for conducting financial transactions—sometimes, they are not used in financial trades at all. Tools and models are used in a differentiated manner, within and depending upon types of social relationships, among other factors, in order to formulate social judgments about market participants. This indicates that in financial trading, models are not simply developed by a central (academic) authority and then transferred to traders, who take them at face value and apply indiscriminately. Rather than that, the use of models and other trading tools depends on the place they take in strategic interactions, as intrinsic not only to action, but also to expression moves. The latter entails differentiation and autonomization of expertise and authority, as a means of filtering out fabrications and dissimulations; differentiated judgment of model validity according to categories of users and providers; and reputational contests and enlistment of followers.

Conclusion I will now revisit the opening question: How can studying the volatile clay of interactions contribute to a better understanding of financial transactions and decisionmaking? The effort to keep interactions at bay from the economics laboratory has been justified with respect to isolating forms of imperfect individual behavior and contrasting them with a normative model of rationality. The study of financial transactions in

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market habitats, by contrast, has the formal properties of strategic interactions as a starting point. The emphasis here is not so much on comparing experimental results with predictions derived from a model of rational behavior, but on building a heuristic tool that can integrate and explain empirical observations, while guiding investigation. Such a model—which definitely needs further elaboration and consolidation through field studies—allows us to make better sense of a series of empirical phenomena which are difficult to handle or experiment with under laboratory conditions. Three of them have been discussed above: first, the persistence and recurrence of emotions in financial transactions; second, forms of strategic behavior which exploit both the moral features of transactions and the institutional rules constraining them; third, judgment as a prerequisite for decision-making. All these aspects need further investigation: we know very little, for instance, about how emotions intervene in calculating trades, or in their (selective) memorization. We also know very little about what type of social relationships emerge from interactions on online trading platforms, or about the concrete uses of valuation tools in trading. The in situ study of financial transactions—and, more generally, of market transactions as practical, collaborative accomplishments (Heath 2012: 314)—poses conceptual and methodological challenges including, among others, what constitutes relevant and reliable data with respect to particular problems or puzzles; how to systematically collect primary data; what constitutes primary transactional data from a field like electronic anonymous markets. Recently, a variety of approaches in the study of financial transactions have emerged, including, among others, ethnographies based on participant observation, but also studies grounded in ethnomethodology and conversation analysis (see Heath et al. 1995). Their methodological and conceptual premises do not entirely overlap: however, by illuminating transactions from different angles, while sharing a commitment to the study of interactions, they contribute to establishing field studies of financial transactions as a sui generis domain of the sociology of finance.

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——— and Steenbarger, B. N. (2005). “Fear and Greed in Financial Markets: A Clinical Study of Day Traders.” Cognitive Neuroscientific Foundations of Behavior: AEA Papers and Proceedings, 95/2: 352–9. Lu, J. and Mizrach, B. (2008). “Is Talk Cheap Online? Strategic Interaction in a Stock Trading Chat Room.” Rutgers University Working Paper No. 2007–01. MacKenzie, D. (2005). “How a Superportfolio Emerges: Long-Term Capital Management and the Sociology of Arbitrage,” in K. Knorr Cetina and A. Preda (eds.), The Sociology of Financial Markets. Oxford: Oxford University Press, 62–83. ——— Muniesa, F., and Siu, L. (eds.) (2007). Do Economists Make Markets? On the Performativity of Economics. Princeton, NJ: Princeton University Press. Mizrach, B. and Weerts, S. (2009). “Experts Online: An Analysis of Trading Activity in a Public Internet Chat Room.” Journal of Economic Behavior and Organization, 70/1–2: 266–81. Orr, W. W. F. (2007). “The Bargaining Genre: A Study of Retail Encounters in Chinese Local Traditional Markets.” Language in Society, 36: 73–103. O’Sullivan, M. (2009). “Why Most People Parse Palters, Fibs, Lies, Whoppers, and Other Deceptions Poorly,” in B. Harrington (ed.), Deception: From Ancient Empires to Internet Dating. Stanford: Stanford University Press, 74–91. Peterson, R. (2007). “Affect and Financial Decision-making: How Neuroscience Can Inform Market Participants.” The Journal of Behavioral Finance, 8/2: 1–9. Preda, A. (2009). “Brief Encounters: Calculation and the Interaction Order of Anonymous Electronic Markets.” Accounting, Organizations and Society, 34: 675–93. Ricciardi, V. (2008a). “The Psychology of Risk. The Behavioral Finance Perspective,” in F. J. Fabozzi (ed.), Handbook of Finance, Vol. 2: Investment Management and Financial Management. New York: John Wiley & Sons, 86–111. ——— (2008b). “Risk: Traditional Finance Versus Behavioral Finance,” in F. J. Fabozzi (ed.), Handbook of Finance, Vol. 3: Valuation, Financial Modeling, and Quantitative Tools. New York: John Wiley & Sons, 12–38. Roth, A. E. (1995). “Bargaining Experiments,” in J. H. Kagel and A. E. Roth (eds.), The Handbook of Experimental Economics. Princeton NJ: Princeton University Press, 253–348. Smith, C. (1999). Success and Survival on Wall Street: Understanding the Mind of the Market (rev. edn). Lanham, MD: Rowman & Littlefield. Vargha, S. (2011). “From Long-term Savings to Instant Mortgages: Financial Demonstrations and the Role of Interactions in Markets.” Organization 18: 215–36. Wansleben, L. (2010). “Precarious Professionalism: An Ethnography of Analysts on the Foreign Exchange Markets.” PhD thesis, University of Konstanz, Germany. Zaloom, C. (2006). Out of the Pits: Traders and Technology from Chicago to London. Chicago: University of Chicago Press.

chapter 9

tr a ders a n d m a r k et mor a lit y c aitlin z aloom

Studying financial traders is a productive way to understand the distinctive order that emerges in global markets. The world of traders can appear to be separate and exotic, and to hover above the everyday world. Through traders’ work, however, we can see how contemporary practices of exchange create not only monetary, but also cultural values that resonate far beyond dealing rooms floors. One challenge in studying financial traders is that, in recent decades, and particularly since the economic crash of 2008, they have become political, cultural, and economic anti-heroes. Politicians, social critics, and a great many scholars routinely denounce their unjustified earnings and their reckless risk-taking, especially when the economy is sluggish, unemployment is high, and working people are struggling. But for social scientists, it’s useful to move beyond denunciation and to examine these financial players analytically, since doing so allows us to understand the market moralities that have emerged since the rise of global finance in the 1970s. Buying and selling financial instruments, traders reap personal profits from the internal price fluctuations of stocks, bonds, currencies, and derivatives—but their individual fortunes are linked to the wider spheres of economy and politics. The work of traders brings financial markets to life, through practices that politicians and policymakers have vigorously encouraged since the 1970s. Traders are, then, both the product and beneficiaries of economic policies and trends that have driven finance to the center of the global economy and yoked its fortunes to individual and national well-being. Financial markets today represent both the outcome of a decades-old political gamble and the culture that has grown up around it (Krippner 2011). Prosperity is now linked to the vicissitudes of securities and to the rapid transformation of the financial field; its demands press even those far outside the industry’s formal boundaries. As an extreme case of the anxieties and potentials of everyday finance, traders

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can teach lessons about the demands of living in a market-based culture and illuminate the values and dispositions its practices encourage. Sociologists and anthropologists have labored alongside traders, observing their work, conducting copious interviews, and even making deals themselves to understand the global economic order and the contemporary financialized economy. Their works reveals the technological framing of the market arena and the forms of knowledge, time, space, and virtue that appear within to diagnose the cultural power of finance.

Topology of the trading field What unites and divides traders as a group? The banking industry’s professional associations do not keep—or at least make public—demographic statistics about traders. Trading’s gender composition is no mystery, though. The ethnographic and journalistic accounts show that trading rooms are overwhelmingly male and feature few women. Other patterns—their numbers, ages, career paths, and most social demographics— remain obscure, however. The oversight in which other professional associations traffic is considered by traders an evil necessary, which is in place only to please sanctionarmed regulators. Securities and derivatives industry regulators are currently seeking more individuallevel information identifying traders whose speculations can endanger markets. The Securities and Exchange Commission is presently considering a rule that would register “large” traders, dealing in more than 2 million shares of 20 million dollars per day, or ten times as much per month. The Commodity Futures Trading Commission already tracks big traders. Inside financial markets, size already indicates status, offering measurable ability to use financial markets for their highest profitability; in regulatory terms, the same measure works to indicate a potential threat to the system. Each links market personhood to the quantities of contracts, bonds, or stock a trader deals. Identifying demographics is important for the liberal pursuit of inclusion, but market distinctions revolve primarily around the dimensions of potential profit and systemic disruption. The desks where both large and small traders work are located across a range of institutional settings within the field of banking and securities; banks, hedge funds, and proprietary trading operations all employ traders, and exchange trading floors and arcades, and home offices also offer spaces, technologies, and institutional connections for more independent dealers to trade financial instruments. Across institutional settings a focus on the dynamics of financial markets unites traders. An old market adage claims that a good trader can trade anything. The prices of commodities like oil, currencies, copper, bonds, oats, and stocks all fall subject to similar price dynamics in the market’s folk wisdom. Although traders certainly specialize, their skills lie in the analysis of price and the assessment of price-related risk, the likelihood of gain, and the

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exposure to loss. In other words, they are experts on the internal workings of financial markets. And in their hands, these markets, of whatever kind, can deliver vast profits, and deep costs. The question of whom these trades enrich or impoverish divides the field. Proprietary traders (“prop traders” in market argot) deal with the money of the firm for its own profit, whether a bank, fund, or private firm. In the wake of the financial crisis investment banks’ proprietary trading has focused regulators’ attention, as the wagers traders make with the banks’ own money often opposes the interests of their clients. Nonproprietary traders buy and sell securities for those customers. Like demographic statistics, the amount of proprietary versus customer trading remains ambiguous, a blurring that can lower the risk profile of a bank’s books. Perhaps the riskiest business lies in the accounts of independent traders who make deals with their personal funds, placing their own livelihoods directly on the line when they enter an order to buy or sell. The everyday practice of trading draws on a variety of techniques; arbitrage, algorithmic trading, spreading, high-frequency trading, and scalping are just some of the different strategies traders use to pattern their buying and selling. These techniques signal internal distinctions, signaling the expertise of a trader and pointing not only to the different securities in which he deals, but also to the technologies he uses, the ways of both establishing knowledge about the market and using it that he employs, the timescales with which he works, and the uses of urban space in which he engages. Ultimately, these techniques suggest what each trader values, in price and virtue. Together they assemble a market culture from the everyday practices of those who tie their livelihoods to the ups and downs of financial value.

Technology Traders gain access to the online world of financial markets through the technologies that surround them. Just as the assembly line presents workers with car parts to join, screen technologies present the materials—financial prices—which traders must connect. By organizing networks among traders and simultaneously presenting the market to them, trading screens harnesses the worker to the market’s pace and constantly forward-moving character. As on the industrial shop floor, these technologies’ qualities structure practices of knowledge, time, and virtue.1 Each work day, traders walk to their desks and take a seat within a carapace of screens. Information enfolds the trader: prices of multiple markets, in commodities, derivatives, currencies, stocks; financial benchmarks like the yield curve; news wires; and prediction models surround him.2 Work was not always organized this way, though. Computer mediation replaces an older order of shouts and the manic hand gestures of the stock exchange floor.

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For much more than a century, financial markets in futures, options, and stocks operated through bodies and voices fighting for deals on the trading floors of the world’s financial capitals. In the late 1990s, the Internet challenged this multigenerational way of life and labor, promising speed, efficiency, and global connections. For traders both on and off the floor digital technologies also marked a more subtle shift. Some traders, like Forex dealers, laid fiber optic cable alongside their phone wires with little fanfare; their deals already operated at a physical distance. However, online technologies changed ways of working in a more subtle fashion, one experienced both on the floor and in dealing rooms. Even before electronic trading, dealers observed information flowing across screens. Prices, charts, and news blinked on individual monitors and blared on enormous, overhead LED panels. Deals, however, involved talking to or gesturing to another person, the screens and human action working together to complete a trade. With the rise of electronic exchange, traders began working through complete deals on screens—from monitoring market patterns to entering buy and sell orders, receiving confirmation, and registering a gain or loss. Electronic trading then alters the interaction order of financial dealing. Even over-the-phone transactions required grappling with the human presence on the other side of the deal; a voice, a face, or a hand gesture required reckoning with the embodied and human-built qualities of the market. Online trading distills markets into the numbers of prices and patterns, a form that both consolidates the many and varied participants into a single entity that exists beyond any of its individual participants. Screen-based trading, then, raises a unified market that seems to act with its own volition, from the actions of traders dispersed in key cities around the globe. Dispensing with human mediation spurred on many proponents of electronic trading. No wonder, then, that in the securities exchanges where buyers and sellers met through floor brokers, the advent of digital technologies was most jarring. How did these organizations respond to the incursion? Just as organizational environments conditioned the levels of individual opportunism that Abolafia (1996) found in New York’s bond markets, such environments also conditioned traders’ responses to the new technologies. In some settings, online trading looked like a major opportunity, in others only a minor sideshow to the main ring, the trading floor. Attachment to the traditional work techniques and the pull of organizational politics divided those exchanges that adopted online trading swiftly and those that lagged. The Chicago Mercantile Exchange (CME) developed initial trading on its Globex system as early as 1992; its organizational identity as an innovator in the field supported its embrace of new ways of trading. In the 1970s the exchange had spearheaded the shift from physical commodities like cattle to financial ones, like currencies; the membership was primed to see the vast profit potential in innovations. The CME’s voting structure gave strong voice to those members more likely to support experimentation, the traders in the newer index and currency markets. Rival exchanges like the Chicago Board of Trade and the New York Stock Exchange remained indifferent to the novel technologies, convinced that their floor traders would continue to make the surest markets and draw in business. Secure in the lead position in futures and stocks respectively, the members voted to protect their way of working,

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believing that their historical advantages would continue to draw customers. Their position quickly became untenable, however, in the new world of electronic dealing. Digital trading proceeded hand in hand with another organizational change for the exchanges. In the first round of transitions, many exchanges went corporate, abandoning their founding forms as membership organizations and nonprofits, arguing that clear hierarchies would help them move with the speed and flexibility of digital time. Once the trader-members swapped their seats for stock, exchanges began to merge with the promised alacrity, bringing global form to already transnational financial transactions. Both the organizational and technological disruptions generated productive conflicts and debates about the desirable functions and forms of markets. As the form of trading changed, debates about the normative structures of the new social arrangements became topics of intense debate and experimentation (Zaloom 2006: ch. 2). This transition is far from over; in fact the exchanges are laggards in the financial industry where organizational churn has roiled since the 1980s. Global interconnection and organizational elasticity continue today with the merger of the New York Stock Exchange, the preeminent symbol of American capitalism, and Deutsche Börse, firing debates, once again, over the relationship between particular markets and the global economy. The necessity of digital connection is no longer, however, under discussion. Now almost all traders engage the rise and fall of markets from swivel seats facing computer screens. The screens channel prices, news items, and chats to participants, joining the perception and representation of the market, or “appresenting” it (Knorr Cetina and Bruegger 2002b). Screens assemble the material out of which traders build a “streaming” interaction order (Knorr Cetina and Preda 2007: 117) that engages simultaneously the epistemic and economic orders (Knorr Cetina and Bruegger 2002b: 395). Screens insert traders into a set of interactions, information exchanges, calculations, and transactions that define a virtual world on a global scale (Latham and Sassen 2005). Constantly connected, financial markets constitute “virtual societies” that move as the sun moves across the earth with traders rising, logging on, tiring, and departing for home at intervals that periodically repopulate the global trading space (Knorr Cetina and Bruegger 2002a). Fluctuating prices coordinate geographically distant competitors, providing the material for exchanges with counterparts around the globe. The flow of activity joins with the similar labor of other traders, bound together through the signals surging through fiber optic cable. With the screens, coordinated actions of traders establish a “global microstructure” (Knorr Cetina and Bruegger 2002b) and enliven the market as an object greater than the sum of its individual trades. The network, tied to city centers, gives birth to the global market. The screens do more than establish a global microstructure however; they validate the market they create. These “windows” onto the market world present prices and information as legitimate records to be monitored, calculated, and acted upon, lending authority to the world beyond the screen (Preda 2009). So, as traders watch and engage the market they do more than gain profit (or acquire losses) for themselves and their banks; they also justify the market as an independent system, one that displays its own observable trends and rules organized around the price of currencies, securities, and commodities.

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Despite their initial sophistication, these observational systems always appear insufficient to the traders that use them. They seem to fall short of optimally presenting the market, since speed and efficiency drive competition forward and, by definition, propose no endpoint. This aporia thrusts traders into an ongoing search for novel technologies to enable smarter understanding and faster interaction. Facing such an inherently imperfect system, traders and their digital designers constantly manipulate technologies, since they ask a question without firm resolution: What constitutes the market? And what technologies can represent it? It is a query relevant for practical use in trading room, but which engages a more philosophical set of market ideals: individual autonomy, acumen, and competition. Contemporary financial markets have built technologies around an ideal of “informational transparency,” a model that requires market information to be formatted as facts free from the distortions of social information. The designers of electronic dealing systems supply simple economic truths in the shape of financial prices, their histories, and their relationships. These technologies then lay the foundation for traders’ calculations and engagements with the market. With sheer economic facts visible for interpretation, a particular kind of competitive arena can emerge. The virtual society promises that dealers, separated from the contamination of social influences, would subject one another to a purer form of competition and generate an efficient market at the same time as they reeled in profits for themselves and their backers. Only the fittest—the most perceptive and the quickest—will flourish, the logic proceeds (Zaloom 2003). As electronic trading knitted together markets, another set of even faster traders rose to take advantage of the new environment: quantitative traders developed algorithms to draw profit from global price movements. Taking advantage of the lush informational environment, algorithms detect patterns no human could compute alone, and with unique speed. These observational systems do not remain on the sidelines, however; they whip buy and sell orders through exchanges’ matching systems, and even exploit other algorithms, buying or selling ahead of a detected sale (MacKenzie 2011). Sometimes they also move markets in extreme ways. On May 6, 2010, market indexes fell nearly 6 percent in five minutes. And recovered 20 minutes later. The “flash crash” was triggered by a program executing an extensive sell order of stock index futures, instruments tied to actual corporate stocks. Algorithms reacted to plummeting prices by shutting down under these extreme conditions, accelerating the drop. Prices began to move back toward their previous levels only when the Chicago Mercantile Exchange applied an electronic brake, also coded to trip under particular conditions. Human traders then had five seconds to consider their positions and decide to buy or sell outside the constraints of their automated avatars. What were the factors that precipitated the flash crash? The consensus explanation faults the algorithms’ bolt from the market (Easley, Lopez de Prado, and O’Hara 2011). The flash crash raises more fundamental queries too: What is the relationship between human traders and their machines in the electronic world? What vulnerabilities accrue to this new system of observation and market action? And what responsibilities must these systems carry? When citizens’ economic security is ever more tied to finance, this

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is a pressing political question. These novel forms also demand fresh analysis. The meshing of observational tools and profit-taking breeds a form of interconnection where traders react to machines and also to other humans reacting to the market. Close observations of the relationship between human traders and their tools offers a starting point.

Reflexive reason In the enclosed world of the market, observational systems take on a reflexive nature. Traders’ knowledge about the market’s movements rests on its simultaneous existence as the aggregate of participants and an entity apart, a dual character displayed in key predictive tools, like the spread plot and the yield curve. With these devices in hand, traders can assess their own positions relative to the market’s judgment. Because technologies give the market presence, the media of exchange gain particular power in conditioning traders’ strategies and understandings. The construction of traders’ predictive instruments and their uses feeds back into professionals’ calculations and ultimately their buy and sell orders. The interchange between the traders and the market world shapes the tools of observation themselves producing a form of reasoning characterized by its reflexivity. As traders enter into an exchange of information with the market, they create and consult models of its behavior, harvest novel information about it from their monitors, and enter buy and sell orders to profit from it. Their calculative repertoire includes far more than their most obvious numerical tools offer; instead, calculative strategies center on the interdependence of the social and the technical. Traders delineate social groupings at work in the market, and identify affective trends, such as fear or ebullience that might drive prices (Beunza and Stark 2004; Godechot 2000; Zaloom 2006: ch. 4). The relation between social composition, emotion, and reason generates reflection on both the constitution of the market and traders’ own positions among participants—and even their relationship to themselves as market actors. Traders must detect their own patterns of elation and anxiety and, subjecting these reactions to conscious manipulation, either incorporate their signals or abjure them. The social objectification of the market and the objectification of themselves as actors within the market feed into trading acts. Social objectification, especially, raises the issue of the tools traders employ to understand price patterns. The spread plot and the yield curve offer insight into this reflexive relationship between financial knowledge and tools of market appresentation. Corporate mergers can offer traders profit, but the politics of regulation and of corporate combination can derail a deal. The spread plot offers a view of the likelihood of two firms combining as it draws a visual picture. A narrowing gap between the prices of the two companies indicates a greater likelihood as the values converge, whereas a widening rift indicates skepticism as the prices migrate to their original, respective values. Monitoring the spread plot offers the trader a view of the market’s shifting assessment of the merger’s likelihood. Beunza and Muniesa describe this circular process: “Market participants see themselves aggregated and take this picture into

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account for further action—action that translates in a particular performative twist, into the spread plot again” (Beunza and Muniesa 2001: 633). Traders frequently make use of such reflexive loops in their calculations. Rather than take the signals as given, traders often use models to suss out their own oversights, “backing out” from the model rather than directly employing its judgments. Traders “take as a point of departure the fact that financial actors go back and forth between models, their understanding of what is being traded, and their ability to figure out what their competitors are doing,” a process that Beunza and Stark (forthcoming) argue can produce dangerous interdependencies as individual traders act in reaction to the same sets of information. Affect also loops through market reflexivity, engendering an anxious relationship between traders and their tools. As a graphic representation of US bonds’ future value, the Treasury yield curve is a powerful model of the future; it points to the health of America’s economy and therefore reflects global economic stability. The yield curve unifies a field of market action, reflection, and emotion, bringing together the dispersed and disparate actors who make up the credit market. Its varied and particular social content raises questions about the yield curve’s effectiveness as a predictive tool, however. If the participants are rational, then the yield curve’s signals about the future should be valid and traders can pursue their strategies with more composure. Bank traders and hedge fund managers assume their counterparts act as they do: working to gather information about the forces that will shape the course of the economy and then buying or selling accordingly. These individual rational decisions should draw an aggregate picture of economic prospects. However, the market may include participants whose intentions or “irrational” judgments distort the picture. The bond market cannot be assumed to be composed of only judicious experts. Yet participants can never know who exactly does what in the market. Rational prediction can proceed only on the faith in the rationality of the players whose opinions sketch the economic forecast. The techniques and technologies of reflexive finance are shot through with such fissures, pointing to a conflict in the composition of financial understanding and to an intractable problem of contemporary forms of knowledge more generally. Professionals’ engagements with the yield curve proceed through the uncertainties sustained within it—uncertainties about both participants and the ability of the yield curve to provide a convincing portrait of the economic future. The constant changes—of actors and their strategies—that make up the market transform the tool itself, drawing the instrument into cycles of doubt, a process reflected in traders’ forms of reason. The uncertainty of reflexive tools sends traders in search of information to confirm their judgments and establish new associations among ambiguous messages. Combining sets of devices, each with their own formulas of prediction, promises the ability to form enough of a provisional judgment to draw profit from price fluctuations. Constantly adapting their strategies to changing conditions, traders work within a “bazaar of rationality” where profit results from strategies that link calculation and feeling, including assembling different kinds of statistical reports, analyzing traders’ own “feel” for the market, and speculating about the emotions of competitors

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(Godechot 2000). In relating a diverse array of information sources, traders practice a particular, contemporary form of bricolage. That also includes the spatial and social elements of the dealing room, and the specifics of the situations it draws together (Beunza and Stark 2003; Godechot 2000). Physical location routes the paths of formal calculation (Beunza and Stark 2004; MacKenzie 2008: ch. 6). Donald MacKenzie argues that even the mathematicization of options trading works through the “dense, bodily, spatial social structures of trading pits.” The exchanges’ social and spatial structures “affected the ease with which the mathematical relation between put and call prices was maintained,” generating a situation in which a model did or did not make sense in a given moment (MacKenzie 2008: 169–70). Bank trading rooms also draw together spatial and social arrangements with abstract forms of financial calculation in ways that enable profit. As Beunza and Stark point out, the physical organization of dealing rooms enables novel associations that can lead traders to recognize and research evolving patterns. If “diverse principles of valuation” are critical for establishing the cognitive basis for drawing future profits, physical space organizes that heterogeneous order (Beunza and Stark 2003: 373). When traders are displaced, the relationship between market reasoning, space, and technology reveals itself most clearly. After the disaster of September 11, lower Manhattan’s trading rooms bivouacked to nearby sites in the region. New office spaces forced traders to replicate the arrangements that supported their work. To reconstitute their profitability under new conditions, arbitrage traders rebuilt their cognitive environment from spatial, social, and technological materials. Entwined, networks of traders and tools created the ability to make sense, which was especially (and literally) valuable under such conditions of extreme uncertainty (Beunza and Stark 2003). Reconstructing the trading room made productive use out of rapid change and uncertainty, a task also central to traders’ everyday work and to their particular sense of time.

Time Although screens and tools of financial analysis provide entry into a coordinated and stabilized system of global exchange, time within that space moves with velocity and volatility. The interconnection of traders through fiber optic cable enables the financial markets’ particular and peculiar organization of time, one that exaggerates its unfolding character. The pace and timescale of trading generates the conditions in which traders learn to regulate themselves in relation to their work. In traders’ understandings, these processes, when successfully managed, lend profit, and they also develop a sense of market-based virtue. As the prices of financial instruments move up and down, their irregularity, what economists call the “random walk,” forces traders to direct unbroken attention to the screen.3 The demands of continual focus on the immediate future heighten the power of time’s unfolding nature. Knorr Cetina and Preda (2007: 130) have described the quality

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of trading temporality as one of a carpet “where small sections are woven and at the same time rolled out in front,” establishing an “ontological fluidity” that places traders at the always-emerging edge of the future. The market’s continual unfolding frames both calculation and the social form that emerge from it. Continuous changes of prices and opinions direct traders’ improvisational strategies and place the unfolding nature of market time at the center of traders’ calculations. To profit, traders must predict the pattern on the carpet being woven beneath their feet, yet stay flexible in their interpretations and ready to lift their judgments of market direction as conditions, participants, and as the market itself changes. The ability to act within the future’s emergent uncertainties directs the social hierarchies and virtues that emerge in trading rooms. On the trading floor, both status and self hinge on handling fast-paced volatility. Arguments over traders’ “competence” point to triumphs or failures in this area. In both pits and digital dealing floors, traders observe each other and take account of actions and reactions under intense time pressure. Aggressiveness and assertiveness in “fast” markets are understood to reveal a trader’s self-confidence and fight, an attitude that transforms stress into the sinews of success. For traders, such masculine virtues define success and failure at the edge of the future (Levin 2001). Profit-making, then, marries calculative acumen with character. The social demand for masculine competence also raises more internal questions: How do traders create these skills? How do they adapt to work at the edge of the future? Traders cultivate marketplace selves to function under emergence and to exploit their chosen techniques. Each strategy—from scalping to spreading to arbitrage—generates its own internal temporality. Organizing time strategies in varied ways, different techniques produce distinct visions, of both the market and of dealers’ relationship to them. Arbitrage, the technique of drawing profit from price inconsistencies across markets, offers a view into the relationship between the temporality of trading techniques, traders’ self-fashioning, and the global financial order. Arbitrageurs take advantage of discrepancies across markets, based on the assumption that prices will converge; even though there may exist momentary divergence, values among financial products will return to a balanced state. Designing strategies to draw profit from the “propensity of the market toward a future moment of equilibrium” (Miyazaki 2003: 257), arbitrageurs fulfill the prophecy, lending the technique the ability to bend time to its shape. Yet profit is not the only effect of arbitrage’s temporality. The technique’s gap between the divergent present and imminent rebalancing generates a “future orientation” (Miyazaki 2003: 261) based in a particular, quasi-religious, faith: a belief in the market’s inevitable return to price equilibrium. Arbitrageurs knit together practice and conviction by buying and selling securities. Arbitrage also works as a metaphor for understanding temporal relationships beyond the floor. Traders live not only with their financial instruments and trading strategies but also in workplaces set within nations. For Japanese traders in particular, the understanding of arbitrage in which opportunities are “immediately foreclosed” resonates with their understanding of their place in finance. US banking firms set the financial

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pace; Japanese traders must play catch up, closing the gap between the emergent order and their own lag. In both dealing techniques and national comparisons, the sense of a foregone future generates both anxiety and hope (Miyazaki 2003: 256). Financial instruments, then, create a temporal effect that shapes traders’ affects and understandings of self and the global financial order. Techniques of trading exercise influence over traders’ social imaginations, but their influence also goes deeper within. Traders treat the self as a tool, developing techniques to work within the market’s temporal emergence and volatility. Manipulating emotions to create more effective calculation, traders analyze their own departures from an ideal form of market reason, under intense time pressure. For instance, both arbitrage and other trading techniques, such as scalping, or position trading, require sustained attention and consistent calm to attend to swift shifts in prices as their securities gain and lose value sharply. On the dealing room floor, capital circulation produces a particular form of attention that couples with ideals of virtuous market action. Traders organize their self-conduct around the intricate dictates of “discipline.” Discipline is both an idealized state and a concrete set of internal strategies that remove emotion and individuality from judgments, orienting the dealer to the unfolding future. Discipline itself is a set of techniques for manipulating space and time. There are four core elements of discipline; first, traders separate their actions on the trading floor from their lives outside; second, they control the impact of loss; third, traders learn to break down the continuities between past, present, and future trades, by dismantling narratives of success or failure; and, fourth, they create a stance of acute alertness in the present moment. With discipline speculators train themselves to become embodied instruments for reading the market and reacting to its every twitch (Zaloom 2006: ch. 6). Discipline enables the state traders value most: the sense of total absorption, of entering “the zone.” There, conscious thought disappears and an ultimate sense of presence takes over. In the zone they are able to act without explicit thought; their trades flow with the rhythms and sounds of the market. Traders’ dealing techniques and flow experiences can illuminate sites far from the trading room floor. For instance, the video poker players and slot machine gamblers of Las Vegas prize a similar connection between time, technology, and absorption. Just like prices on a trading screen, the fast-paced changes in video poker hands create a structured chaos that helps induce the zone. Like traders at their peak performance, gamblers lose any sense of space, time, and self during play. Completely captivated by the swift shifts in their glowing cards, their sense of their own presence dissolves into the smooth motion of poker hands through time (Schull 2012; Zaloom 2010). Mihaly Csikszentmihalyi identified such absorption as “optimal experience,” and traders’ description of the zone aligns closely with the athletes of Csikszentmihalyi’s formulation (Csikszentmihalyi 1991). Jet pilots, Indy 500 racers, and surgeons also operate in masculine arenas where the idea of optimal experience holds fast. The gamblers, however, tell a different story, one which contains a key for reevaluating the absorption of financial markets. In machine gambling, the convergence of time and technology leads to literal addiction. Financial trading displays similar addictive qualities, and requires

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remedies that address the particular features of technology and money that drive forward destructive habits. For now, though, financial trading still inhabits a special cultural space that identifies profit at the edge with masculine virtue. Traders exemplify adventure capitalism for a world in which time is the new frontier. Dealing on the prices winging into the future, traders operate at a temporal edge. This risky business lends a charisma to speculators as characters who crystallize and celebrate “individual freedom and force” (Weber, quoted in Preda 2009: 233). The marriage of individual cunning and risky profit cuts a figure of daring in a routinized world, and produces a mythical draw. Adventure capitalism, especially in the United States, has long linked heroism to the regeneration of wealth. Once, the frontier accomplished the renewal of fortunes, at least in American fantasies. Today, however, the territory for domestication is temporal. Both traders and popular writers have built a moral relation to markets cast in familiar heroic terms, a contemporary mythology that glorifies the taming of the future. In the years leading up to 2008, dealers in derivatives and other financial instruments became the hero-villains of popular novels and movies frequently adapted from the broadsheets. “Rogue” dealers’ losses ripped holes in the sides of global banks’ (then) seemingly unsinkable pleasure cruisers, generating fodder for fictionalized accounts.4 Other writers chose the new math prodigies recruited to Wall Street from physics departments and backgammon tournaments, penning thrilling tales of financial gambles most corporate workers could only imagine. These new wizards of Wall Street broke the house in The Predictors (Bass 2000), Fortune’s Formula (Poundstone 2006), and The Quants (Patterson 2010) among others. Upon their exit from the industry, another set of authors composed tales confessing the outrageous locker-room behavior married to financial manipulation.5 Even today as such stories assume a distinctively contemptuous color, traders remain alluring symbols of our financialized economy’s excesses as they link us to powerful iconography and the glamor of speculation.6 Traders, inhabiting this paradox, illuminate the necessity, need, and desire of intimate relations with markets, for better and worse. Taking profit draws both traders and everyday citizens into the nexus of gain and goodness. Playing against the unknown future, profit draws the distinction between the virtuous and those the market has deemed lacking. In both these public tales and the stories that traders tell each other, the market creates a moral arena for contests among financial strivers; inside each proves his worth against the others.7 The market also stands apart as a moral force, assuming the qualities of an all-seeing judge, an entity both apart and above. Traders routinely describe the market as the generator of ultimate truth and the judge of human value. Working in currency markets, Karin Knorr Cetina and Urs Bruegger (2002c) show that the market becomes an “object of attachment,” the arbiter of traders’ sense of lack or wholeness. Discipline offers access to the transcendent power’s embrace. One trader described how, with discipline, “you can experience the market and become a part of this living thing, intimately connected to it” (Zaloom 2006: 128).8 As the market delivers a sense of absorption, virtue, and completeness, it also seems to demand allegiance to principles beyond individual profit.

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Service to the market defines the value of traders’ work, particularly to what traders identify as its essential functions. Directing their focus, it also provides justification for their occupation. Market-makers, those traders who continually post bids and offers, express commitment to “liquidity.” Buyers or sellers can view their quotations and, as their title suggests, come to them at any moment to make a deal. The market’s constant forward motion depends upon their presence and willingness to trade at any time. Liquidity also moderates volatility—an object lesson relearned during the flash crash— and facilitates matching exchange partners. When buyers and sellers meet, another feature of the market emerges. Price discovery uncovers what traders consider the “truth” of the market. The cross of supply with demand defines the value for a commodity or security, naming the value of oil, corn, General Motors cars, even the US government, by establishing a price. Each trader plays a tiny fractional role in this ongoing drama of changing values, each moment a revelation that offers a reward over and above the profit that it can also yield. Traders’ moral allegiance is rooted, then, in a commitment to the market as vital source of truth about the material world.

Space The market’s essential verity relies on traders’ continual use of their expertise, a routine configured at once through technology and through urban space. Finance’s urban “command centers,” such as New York and London, amass symbolic analysis that produces both the materials and motion of the virtual space (Sassen 2000). Cities also offer the means for traders, and other financial experts, to display their success in the virtual world—and for those who remain outside, cities offer arenas for claiming inclusion in finance. Urban space both organizes global trading networks and offers a platform for the performance of financial aptitude. Paradoxically, even as online technologies have obliterated the constraints of distance, a few critical sites of finance have emerged, in part to support the luxury lifestyles such workers seek. As high-level computing and online connection have elevated trading, and other banking activities, in economic importance these key cities’ significance has also increased. New York and Dubai, Singapore and London display their own importance as entry points and expressions of the global network. In finance, cities organize agglomerations of experts to answer questions of value. Urban resources become materials for financial market professionals, such as architects, managers, and software designers, to build market infrastructures. In order for traders to answer questions like “How much is the Japanese yen worth right now?” and “How much will a US Treasury note be worth in three months?” designers engage in “practical experiments” to fulfill the ideals of autonomous market competition by combining physical spaces and technologies. Under conditions that can enable “true” prices to emerge, traders act as critical infrastructure in establishing cities as “value loci,” and in virtualizing the urban qualities of centralization, agglomeration, and calculated exchange that establish the market qualities of online exchange (Zaloom 2009).

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Urban propinquity also fosters such expertise, particularly in price and profit-making. For traders, exchanges with financial dealers both within the same firm and in nearby firms help generate the novel associations between sectors and techniques essential for profiting in a constantly changing field. However, concentration in cities also creates vulnerability. The attacks on September 11 took a particularly heavy toll among traders, many of whom worked in the towers for firms like the bond dealer Cantor Fitzgerald. The urban geography of financial markets demands that financial firms balance necessary proximity with desired security (Beunza and Stark 2003). Following the disaster, The New York Times printed pages of faces, names, and occupations that both recorded the tragedy’s personal toll and, at the same time, revealed the particular geography of financial trading, a concentration that launches New York City into the virtual world of global finance and secures its importance in the network. Urban command centers coordinate more than the transactions that make up the daily commerce of finance; city spaces offer finance a particular public stage. Traders highlight the legitimacy of finance by using urban space for displays of success. Cities are critical in generating “the perfect lifestyle” that traders and other bank employees seek out, a balance between such “self-won” urban luxury consumption and stable home lives often based in nearby suburbs (Ho 2009: 52). Market survivors deserve urban luxury: elaborate meals, trendy clubs, fashionable hotels, and clothes of fine design and fabric. Raunchier pursuits offset such domesticated pleasures. Bad behavior in nearby high-end strip clubs and hushed-up sprees in Las Vegas offer offsite opportunities to display the prerogatives of primal, market man. To the rawest, most competitive, and most willing to breach decorum in the search for success, go the spoils. In sum, cities operate as stages for consuming the deserts of market success. Because discourse about market winnings poses these profits as the results of fair contests, urban consumer bacchanalia stages meritocratic deserving. Cities also offer materials—their urban histories and built environments—for claiming social inclusion and a right to employment in the financial field. In London’s early days of currency and derivatives trading in the 1980s, “barrow boys” came to populate the dealing floor of the City of London, Europe’s most powerful financial district. With roots in the working-class East End these traders drew on the hard-bargaining tactics of the street trades and the raucous manners of the London docks that once provided material sustenance for the district’s young men. The East End’s history aligned effectively with the designs of the rising global market trade in financial goods. Moving from physical commodities to more abstract ones, the task, they argued, was the same: to best your opponent for the best price. This was a new version of an old market character, one that fit well with an ideology of market competition. The association of East Enders with market-making created grounds for the barrow boy’s legitimate inclusion in the City, a space long dominated by a clubby set of elites (Zaloom 2006: ch. 3). Women, too, have used urban materials to mount similar arguments. For instance, women who entered Wall Street as behind-the-scenes analysts in the 1960s and 1970s were systematically locked out of the men’s clubs that for many decades organized the social lives of Wall Street’s brokers and traders. Groups organized to advance women’s

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leadership in finance have used New York’s emerging spaces of professional–managerial culture, like art galleries and museums, as stages to launch bids for increasing the female presence in Wall Street firms’ upper tiers. These women’s groups employ “material spaces to work out new discourses and images of gender relations, finance, and women’s status” (Fisher 2010: 265). For instance, events of the Wall Street organization, the Women’s Campaign Forum, dramatize finance as aligned with a meritocratic culture that should be gender-blind according to the logic of the bottom line. In doing so, they use spaces of the city to challenge the exclusively masculine character of finance and elite levels of politics (Fisher 2010). As traders and other bankers use public space to display their winnings and marginal groups dramatize the liberal imperative for their inclusion, cities then also offer the materials to debate the distribution of goods connected to the financial economy. For instance, what does it mean for New York City that the wages average of the securities sector was $347,000 in 2010, binding the livelihoods of service workers to the industry’s welfare (Lowenstein 2011)? Such imbalances in the organization of urban industries raise squarely political questions. Cities, then, operate as stages for the dramas that establish and can also question the social legitimacy of finance.

Conclusion Finance crystallizes contemporary forms that also operate beyond its boundaries: an essentially reflexive knowledge, a heightened sense of time’s unfolding, and a system of virtue defined by service to the market’s truth. Interconnected screens establish the infrastructure for an online world, erecting the arena in which traders improvise strategies that are at once cultural and financial. Most significantly, electronic technologies shape the temporal structure of financial work. The unfolding future defines the emerging contours of the market, the arena of competition in which the individual trader must take decisions and, he hopes, profit. Joining the market’s emergence with temporal unfolding creates a new kind of edge where masculine adventurism takes hold, a threshold where the pursuit of money and moral standing merge. The market, in traders’ work, becomes not only a source of gain or loss but also an essential ethical commitment. Examining traders can illuminate cultural patterns in arenas that draw in far greater numbers than those who deal on trading room floors. The online world of traders offers a contemporary exemplar, one that crystallizes not only the workplace relations of a global knowledge economy, but also the realm of leisure pursuits, as online media become defining features of both work and play. Online communications technologies and their constantly shifting information have come to dominate our technological landscape. As an extreme example of everyday processes, traders show what constant engagement with a volatile information environment looks like. The combination of screens and emergent information heightens awareness of temporal emergence, no matter what their specific content; commonplace technologies, like

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smartphones, create windows onto unfurling and volatile information environments. Mediated through screens on pockets and on desks, social media like Facebook, Twitter, and even email structure similar qualities of attention that traders evince. Unfolding information, and even the simple possibility of novelty, exercises a compelling force. Constant monitoring of the shifts in social information establishes a form of social connection that mimics market linkages and exchanges. This transformation of daily life is not simply a change in transmitting information, but also in the values that accrue to its pursuit. Traders assign moral significance to the ability to operate at the edge of the future; in the wider online world, the constant search for novel information has emerged as its own ethical pursuit. Like online interaction, markets, too, have become an object with which to understand human interconnection. At the same time, and under today’s contemporary political conditions, the market has become a key object that citizens generate collectively—the entity that is simultaneously made up of the interactions of participants and that creates another entity beyond and above them. A valued, governing force, as well as a description of transactions, the market seems to demand fidelity to its principles of operation. Traders’ uses of knowledge, perception of time, and sense of virtue show how market interactions can become moral endeavors. Those cultural qualities may or may not be compatible with other, perhaps more essential, values. Discovering an answer to those questions requires collective reflection available only outside the market’s thrum.

Notes 1. For a classic treatment, see Michael Burawoy’s (1979) Manufacturing Consent: Changes in the Labor Process Under Monopoly Capitalism. 2. The vast majority of traders are male and I will use masculine pronouns to reflect both the social composition, and also the gendered character, of trading rooms. 3. See Burton Malkiel (2011) for a plain language synopsis of this perspective and why economists believe that short-term trading strategies produce profits only for the lucky. 4. Nick Leeson was the first trader to gain fame through his massive, and hidden, speculations gone awry. From the bank’s Singapore trading operation, Leeson built up enough losses to cause Barings, the oldest merchant bank in England, to collapse. See Leeson (1997) for a self-report of the events written from prison. 5. Examples of this genre are Fiasco: The Inside Story of a Wall Street Trader by Frank Partnoy (1999); Monkey Business: Swinging through the Wall Street Jungle by John Rolfe and Peter Troob (2000); and Liar’s Poker: Rising through the Wreckage on Wall Street by Michael Lewis (2010). 6. I agree with Clark, Thrift, and Tickell (2004) that finance has become entertainment, but popular media, on television or online, are never just that. Clark, Thrift, and Tickell argue that the significance of finance as entertainment lies in the seriousness with which financial institutions receive these transmissions. I argue that financial entertainment also serves as broader cultural commentary, delivering moral messages for living with markets.

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7. Like the Balinese cockfight, the market constitutes a “focused gathering,” as Erving Goffman called it, an assembly that draws participants into a common activity that directs their relations with each other. Also like the cockfight, the market is a “combination of emotional explosion, status war, and philosophical drama of central significance” (Geertz 1973: 417). 8. Karin Knorr Cetina and Urs Bruegger show that the market becomes an “object of attachment” where the “uniquely unfolding character of the market-object uniquely matches the structure of wanting by which we can characterize the self ” (Knorr Cetina and Bruegger 2002c: 153).

References Abolafia, M. (1996). Making Markets: Opportunism and Restraint on Wall Street. Cambridge, MA: Harvard University Press. Bass, T. A. (2000). The Predictors: How a Band of Maverick Physicists Used Chaos Theory to Trade Their Way to a Fortune on Wall Street. New York: Holt. Beunza, D. and Muniesa, F. (2001). “Listening to the Spread Plot,” in B. Latour and P. Weibel (eds.), Making Things Public: Atmospheres of Democracy. Cambridge, MA: MIT Press, 628–33. Beunza, D. and Stark, D. (2003). “The Organization of Responsiveness: Innovation and Recovery in the Trading Rooms of Lower Manhattan.” Socio-Economic Review 1/2: 135–64. ——— (2004). “Tools of the Trade: The Socio-technology of Arbitrage in a Wall Street Trading Room.” Industrial and Corporate Change 13/2: 369–400. ——— (forthcoming). “From Dissonance to Resonance: Cognitive Interdependence in Quantitative Finance.” Economy and Society. Burawoy, M. (1979). Manufacturing Consent: Changes in the Labor Process Under Monopoly Capitalism. Chicago: University of Chicago Press. Clark, G., Thrift, N., and Tickell, A. (2004). “Performing Finance: The Industry, the Media and its Image.” Review of International Political Economy, 11/2: 289–310. Csikszentmihalyi, M. (1991). Flow: The Psychology of Optimal Experience. New York: Harper Perennial. Easley, D., Lopez de Prado, M. M., and O’Hara, M. (2011). “The Microstructure of the Flash Crash: Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading.” The Journal of Portfolio Management, 37/2: 118–28. Fisher, M. S. (2010). “Wall Street Women: Engendering Global Finance in the Manhattan Landscape.” City & Society, 22/2: 262–85. Geertz, C. (1973). The Interpretation of Cultures. New York: Basic Books. Godechot, O. (2000). “The Bazaar of Rationality: Towards a Sociology of Concrete Forms of Reasoning.” Politix, 13/52: 17–57. Ho, K. (2009). Liquidated: An Ethnography of Wall Street. Durham, NC: Duke University Press. Knorr Cetina, K. and Bruegger, U. (2002a). “Global Microstructures: The Virtual Societies of Financial Markets.” American Journal of Sociology: 107/4 905–50. ——— (2002b). “Inhabiting Technology: The Global Lifeform of Financial Markets.” Current Sociology 50/3: 389–405. ——— (2002c). “Traders’ Engagement with Markets: A Postsocial Relationship.” Theory, Culture and Society, 19/5–6: 161–85.

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Knorr Cetina, K. and Preda, A. (2007). “The Temporalization of Financial Markets: From Network to Flow.” Theory, Culture and Society 24/7–8: 116–38. Krippner, G. R. (2011). Capitalizing on Crisis: The Political Origins of the Rise of Finance. Cambridge, MA: Harvard University Press. Latham, R. and Sassen, S. (2005) (eds.). Digital Formations: IT and New Architectures in the Global Realm. Princeton, NJ: Princeton University Press. Leeson, N. (1997). Rogue Trader. New York: Warner Books. Levin, P. (2001). “Gendering the Market.” Work and Occupations, 28/1: 112–30. Lévi-Strauss, C. (1968). The Savage Mind. Chicago: University of Chicago Press. Lewis, M. (2010). Liar’s Poker: Rising Through the Wreckage on Wall Street. New York: W. W. Norton & Company. Lowenstein, Ronnie. (2011). “City Gaining Jobs, but at Lower Pay.” Crain’s New York Business, 14 March. (accessed August 12, 2011). MacKenzie, D. (2008). An Engine, Not a Camera: How Financial Models Shape Markets. Cambridge, MA: MIT Press. ——— (2011). “How to Make Money in Microseconds.” London Review of Books, 33/10: 16–18. Malkiel, B. G. (2011). A Random Walk Down Wall Street: The Time-tested Strategy for Successful Investing. New York: W.W. Norton. Miyazaki, H. (2003). “The Temporalities of the Market.” American Anthropologist, 105/2: 255–65. Partnoy, F. (1999). Fiasco: The Inside Story of a Wall Street Trader. New York: Penguin. Patterson, S. (2010). The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It. New York: Crown Publishing Group. Poundstone, W. (2006). Fortune’s Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street. New York: Hill & Wang. Preda, A. (2009). Framing Finance: The Boundaries of Markets and Modern Capitalism. Chicago: University of Chicago Press. Rolfe, J. and Troob, P. (2000). Monkey Business: Swinging Through the Wall Street Jungle. New York: Warner Books. Sassen, S. (2000). The Global City: New York, London, Tokyo (2nd edn). Princeton, NJ: Princeton University Press. Schull, N. (2012). Addiction by Design: Machine Gambling in Las Vegas. Princeton, NJ: Princeton University Press. Slotkin, R. (1973). Regeneration through Violence: The Mythology of the American Frontier, 1600–1860. Norman, OK: University of Oklahoma Press. Zaloom, C. (2003). “Ambiguous Numbers: Trading Technologies and Interpretation in Financial Markets.” American Ethnologist, 30/2: 258–72. ——— (2006). Out of the Pits: Traders and Technology from Chicago to London. Chicago: University of Chicago Press. ——— (2009). “The City as Value Locus: Markets, Technologies and the Problem of Worth,” in I. Farías and T. Bender (eds.), Urban Assemblages: How Actor-network Theory Changes Urban Studies. London: Routledge, 253–67. ——— (2010). “The Derivative World.” The Hedgehog Review, 12/2: 20–7.

chapter 10

the m ater i a l sociol ogy of a r bitr age 1 i ain h ardie and d onald m ackenzie

“Arbitrage” is a term with different meanings, but this chapter follows market practitioners in defining it as trading that aims to make low-risk profits by exploiting discrepancies in the price of the same asset or in the relative prices of similar assets. A classic example historically was gold arbitrage. If the price of gold in Saudi Arabia exceeds its price in New York by more than the cost of transportation, arbitrageurs can profit by buying gold in New York and selling it in Saudi Arabia (or vice versa if gold is cheaper in Saudi Arabia). By buying and selling as close to simultaneously as possible, arbitrageurs avoid the risks of “directional” trading: they profit irrespective of whether the price of gold goes on to rise or to fall. Arbitrage requires technological resources, sustained effort, and expertise beyond the capacity of nearly all lay investors. It is the preserve of market professionals, and is a crucial form of trading. Arbitrage constitutes markets, for example helping to determine their scope and the extent to which they are global; that international gold arbitrage is possible creates a world market in gold with a “world price,” rather than geographically separate markets with different prices. In constituting markets, arbitrage has wider consequences for economies and political systems. For example, in the late 1990s arbitrageurs in hedge funds and investment banks began to perceive growing similarity between the bonds issued by the government of Italy and those issued by other European countries, notably Germany. For a variety of reasons (including distrust of the fiscal efficiency of the Italian state and consequent fears of it defaulting on its bonds), the prices of Italian government bonds had traditionally been low relative to those of countries such as Germany, thus imposing high debt-service charges on Italy. As arbitrageurs began to buy Italian bonds, their relative prices rose and the proportion of Italy’s government expenditure devoted to debt service fell. The process—which was assisted by the liquidity created by the MTS

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electronic bond-trading system, set up by the Italian treasury in 1988—helped Italy meet the Maastricht criteria for the European Economic and Monetary Union (EMU). Arbitrageurs’ beliefs thus had a self-validating aspect—they prompted trading that made the event (Italy’s qualification for EMU) on which the beliefs were predicated more likely—and helped to create a European government bond market, rather than separate national markets, although the Eurozone crisis has now caused those markets once again to diverge radically. The failures of arbitrage can be as consequential as its successes. Such failures were at the heart of three of the most serious crises of the postwar financial system: the 1987 stock market crash, the 1998 turmoil surrounding the hedge fund Long-Term Capital Management (LTCM), and the 2007–8 credit crisis. A crucial aspect of the 1987 crash was the breakdown of the link—normally imposed by arbitrage—between the stock market and a key derivatives market: stock-index futures. In the case of LTCM, the forced unwinding of arbitrage positions caused huge, sudden, highly correlated price movements across the globe in apparently unrelated assets, bringing some markets close to paralysis. Arbitrage was the crucial motivation for the creation of the structured financial instruments at the heart of the credit crisis. There is an enormous disciplinary imbalance in regard to arbitrage. It has received almost no sustained attention in economic sociology, in economic anthropology, in economic geography, or in the strand of political science known as international political economy, even in the subsets of those specialties that deal with financial markets (the limited exceptions include Beunza and Stark 2004; Hardie 2004; MacKenzie 2003; Miyazaki 2003; Robotti n.d.; and Stark 2009). In contrast, the central theoretical mechanism invoked by modern financial economics is “arbitrage proof.” The field posits that the only patterns of prices that can be stable are those that permit no opportunities for arbitrage. Particular patterns of prices are then shown to be necessary by demonstrating that if prices deviate from that pattern arbitrage is possible. Arbitrageurs’ purchases of “underpriced” assets will raise their prices, and their sales of “overpriced” assets will lower the prices of the latter, so returning patterns of prices to that stable condition. The entire modern theory of asset pricing—especially the theory of the pricing of derivatives such as options—relies on “arbitrage proof ” of this kind. The conceptualization of “arbitrage” in mainstream financial economics differs from the arbitrage as market practice that is the focus of this chapter. Orthodox economists define arbitrage as demanding no capital and involving no risk, while in market practice arbitrage seems always to require some capital and involve some risk, even if the risk is only that a counterparty to a transaction will not fulfill its obligations (Hardie 2004). Indeed, a purist would argue that the trading we consider in this chapter should not be considered “arbitrage” but simply “relative value” trading. Purism, however, has its costs—a purist definition of “arbitrage” excludes the realworld counterparts of the classic arbitrages of finance theory (see MacKenzie 2006)— and purism is not the only possible response. Financial economists—especially “behavioral” economists—have begun to investigate the consequences of making the definition of arbitrage more realistic (a crucial article in this respect was by Shleifer and

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Vishny 1997). These economists rightly see the topic as a crucial one. Since, in orthodox views, it is, above all, arbitrage that makes markets efficient, the existence of limits to arbitrage casts into doubt the full validity of the central tenet of modern financial economics: the efficient market hypothesis, according to which prices in mature capital markets fully reflect, effectively instantaneously, all available price-relevant information. We shall suggest below that there are potentially productive linkages between the emerging literature in economics on the limits of arbitrage and the “material sociology” of arbitrage that we advocate. Material sociology pays attention to, among other things, the role played in social relations by technological systems and other physical objects and entities, including human bodies viewed as material entities: see MacKenzie (2009a). Since that role is, of course, pervasive, all sociology should be material sociology, yet social theory frequently abstracts away from physical objects and empirical enquiry often does not focus on them. As we shall argue, a proper understanding of arbitrage requires us to take into account both its “physical” and “social” aspects, and the two are ultimately inseparable: arbitrage is simultaneously a “physical” and a “social” process.

Brazil 14s and 40s We begin with a concrete example of arbitrage. January 5, 2005: the authors are observing trading in a small London hedge fund, when one of its managers notices an oddity in the Brazilian government bond market.2 The minutes of the US Federal Reserve’s Open Market Committee, released the previous evening in London time, have been taken by market participants as indicating that interest rate rises are on the way, and have led to general price falls in the Brazilian bond market. However, the “14s” (an issue of dollar-denominated bonds that mature in 2014) are “trading up”: their price is high relative to other bonds. “Hit the bid” (sell them), the manager suggests to his colleague, the fund’s trader. The trader does not respond immediately, but he goes on to ask his assistant to produce a chart of the prices over the last three months of the “14s” and the “40s” (Brazilian government dollar-denominated bonds that mature in November 2040). As the day proceeds, the trader takes a position in the 14s and the 40s, short selling the former and buying the latter. (To “short sell” an asset is to sell it without owning it, for example in the hope that it can be bought at a lower price when the time comes to deliver it.) He also sends a contact in an investment bank the Excel file containing the price chart produced by his assistant, encouraging his contact to circulate it to others. (Later in this chapter we discuss why he does this.) A bond maturing in 2040 seems very different from one maturing in 2014: much could happen in the quarter century between the two dates. But the bond maturing in 2040 is “callable”: the Brazilian government has the right to recall the bond by repaying the principal early, in 2015. If Brazilian bonds continue to trade at anything like their current prices, it will be in the government’s interest to do this, since it will be able to

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replace the borrowing more cheaply. The “40s” thus in effect mature in 2015 and so, despite appearances, a “14” and a “40” are quite similar. None of this is said explicitly: it is part of what all sophisticated participants in the Brazilian bond market simply “know.” (Hardie was an investment banker before returning to academia, and was involved in the initial sale of the “40s” on behalf of the government of Brazil, so he knows it too, though he needs to whisper an explanation to MacKenzie.) Nevertheless, the chart produced by the trader’s assistant is a material representation that makes visible the reasoning underpinning the trade. Once he has configured the chart according to the trader’s wishes—initially, it shows the prices of the 14s and the prices of the 40s, when the trader wants it to display the difference in prices— the prices of the two bonds can be seen to follow each other closely, as would be expected, but with the 40s almost always slightly more expensive than the 14s. Again, the reason is common knowledge among aficionados. The 40s are the most liquid of Brazilian government bonds, the ones most readily bought and sold, and thus the most attractive to those who wish to create and to exit positions quickly. Someone viewing the chart can see what the trader has seen: in recent days the 14s have become more expensive than the 40s, with the difference increasing sharply the previous day (January 4). The trader knows his market well enough to infer a cause that is confirmed only later in the day in a telephone conversation with the above-mentioned investment bank contact. The sell-off triggered by US Federal Reserve’s minutes has concentrated in Brazil’s liquid 40s. Indeed, as the contact tells the trader, unusually “the real money guys [traders not in hedge funds but in bigger institutions] shorted 40s.” The trader thus confidently assumes—and makes explicit in a telephone conversation with his contact—that the fact that 14s are more expensive than 40s is a price discrepancy that will be temporary. By short selling 14s and buying 40s, he—and indeed others—can perform an arbitrage (in market practitioners’ sense of the term). The discrepancy would be expected to vanish in the normal course of events, but if others choose also to exploit it (perhaps because the investment bank contact circulates the assistant’s chart to them), the process will be hastened, maybe considerably. By early afternoon, the trader has accumulated some $13 million of short sales of 14s and another $13 million of purchases of 40s. By mid-afternoon, he is able to say “it’s moved in my favor”—the discrepancy has started to reduce—“but not enough to unwind”: he keeps the position on, expecting further reductions in the discrepancy. Only at the end of the week does he liquidate his position, earning a healthy profit. Note what the trader is not doing in this trade. Like the gold arbitrageur, he is not taking a “directional” view. He is not attempting to predict the policies of the Brazilian government, to estimate the probability of bond default by Brazil, or to anticipate the future courses of interest rates or inflation: because the 14s and the 40s are so similar, changes in factors such as these will affect the prices of each bond roughly equally, and with the trader’s matched “long” and “short” positions the effects will cancel out. As the trader puts it in a telephone call to his contact in the investment bank, “there is zero market risk” in the trade: its profitability (“there is at least half a point in that trade”) should not be affected by overall rises and falls in the prices of Brazilian government bonds. In fact,

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as he acknowledges to us, the trader’s position is not entirely free from risk—see below— but, in its insulation from the major risk factors in his market, it is low risk. Asked about the rationale of the trade, the trader says (just as a financial economist would) that the fact “that this trade has presented [itself] indicates [an] inefficiency.” Temporarily, prices are reflecting something other than information such as the relative liquidity of the two bonds. Although the trader’s motivation may simply be to earn money for his hedge fund, his actions are helping to eliminate a discrepancy and correct the effects of an “inefficiency.” In that respect, his trading, even if not free of risk, resembles arbitrage as conceived by financial economics.

The materiality of arbitrage A price is a thing. Like all prices, those to which the trader was responding (and circulating in the form of the chart prepared by his assistant) were physical entities—patterns on computer screens and spoken numbers transmitted by telephone. The forms of embodiment of prices are various—the sound waves that constitute speech; pen or pencil marks on paper; the electrical impulses that represent binary digits in a computerized system or encode sound over a telephone line; hand signals in “open-outcry” trading pits that are too noisy for voices to be heard; and so on—but are always material. If a price is to be communicated from one human being to another, or from one computerized trading system to another, it must take a physical form. The materiality of prices matters to arbitrage because their physical embodiment affects the extent and speed of their transmission. Classical forms of arbitrage exploited the differences between prices in different places. The commodities and currency arbitrageur J. Aron & Company, for example, used to keep telephone lines to Saudi Arabia open constantly so it could, as quickly as possible, detect and exploit the emergence of discrepancies in gold or silver prices (Rubin and Weisberg 2003: 90–1). The development of electronic price dissemination systems (such as the “Monitor” system, introduced by Reuters in 1973: see Knorr Cetina and Bruegger 2002) largely undermined the time–space advantages that firms such as Aron had achieved by the use of social networks, the telegraph, and telephone. Electronic price dissemination does not, however, entirely eliminate differences in the speed of transmission of prices, and those differences remain consequential, even if they are now measured in milliseconds or even microseconds. An “arms race” has been underway for some time among arbitrageurs, and also those using automated order-placing systems to optimize their trading in other ways, in respect to transmission delays in computer networks. For example, firms are prepared to pay a premium to have their computer systems physically close to an exchange’s computer system. The end of face-to-face trading on exchange floors has meant that the human bodies participating in such trading need no longer be located in one place, but a recentralization of technological systems is running alongside the decentralization of bodies.

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Arbitrage often involves bodily skills. Concluding a transaction over the telephone with one party to buy gold, a currency, or other asset, while at the same time telling a colleague to sell it to another party at a higher price is unlikely to succeed if one’s conversation with the colleague can be heard. It is thus important in this (and in many other uses of the telephone in financial markets) that one switches off the microphone when talking to colleagues. The telephones used in dealing rooms often have thumb-operated switches behind the earpiece that make it easy to do this, and many people always switch off the microphone when the party at the other end of the line is speaking, even if there is no parallel conversation for them to overhear. That way, it becomes a bodily habit that will not desert one in situations of excitement or stress. Even electronically conducted arbitrage can also involve material, embodied skill. Such trading involves placing “bids” (offers to buy) or “asks” (offers to sell) for the asset in question. This is generally done by using a computer mouse to click on a screen that, at least in the case of electronically traded futures, shows for each price level the numbers of bids (often in blue) and of asks (often in red). At busy times, these numbers and levels change from second to second, with blue and red bars seeming to dance up and down. If an arbitrage opportunity persists only for seconds (as is often the case), constant attention and rapid physical execution are needed. The anthropologist Caitlin Zaloom reports that as trainee futures traders she and her colleagues were made to practice repeatedly with a computerized gold-price arbitrage simulation, so that the disciplined attention and fast, accurate action they would need became bodily habits. As Zaloom says, they were encouraged “to play commercial video games on our own time to increase our reaction speeds and hand-eye coordination.” A particular danger they were trained to avoid was “fat fingering,” in which, for example, instead of leftclicking the mouse to “join the bid” (putting in an offer to buy at a set price) they accidentally right-clicked, inadvertently buying the asset in question at its current market price. The managers’ aim was to “train our bodies to operate as uninterrupted conduits between the dealing room and the on-line world, allowing our fingers to become seamless extensions of our economic intentions” (Zaloom, personal communication; see Zaloom 2006). The bodily aspects of arbitrage were most prominent when it was performed in openoutcry trading “pits”: stepped amphitheaters, which were traditionally octagonal. Dozens or hundreds of traders stood on the rungs of a pit, making deals by voice or by eye contact and an elaborate system of hand signals. In Chicago (the prime site of openoutcry trading), the hand-signal language that was used was called “arb” because its speed was essential to arbitrage. For example, when a trading firm spotted an arbitrage opportunity, classically between the prices of gold futures traded in Chicago and in New York, it was quicker to “arb” (hand-signal) instructions from the firm’s booth to the trading pit than to send a clerk running to the pit with a written order (Lynn 2004: 57–9; see also Zaloom 2006). Where bodies are positioned with respect to each other could be of considerable significance to arbitrage in open-outcry trading. For example, the two main forms of option are calls (options to buy at a set “exercise price”) and puts (options to sell at a set price),

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and discrepancies between call and put prices can be exploited by arbitrages such as “conversion.” (In conversion, a trader sells a call option and simultaneously buys a put option with the same exercise price and expiration plus the stock or other underlying asset in question.) Options arbitrageurs on the American Stock Exchange found it advantageous to stand in between the “specialist” (designated main trader) responsible for calls and the specialist responsible for puts on the same stock. That was the optimum bodily position for detecting and exploiting opportunities for conversion and similar arbitrages.

The sociality of arbitrage A price is a thing, but it is also social. All forms of arbitrage depend for their success on what others will do. Even in the classic forms of arbitrage that exploit differences in the prices of the “same” asset in different places, others must be depended upon to fulfill their obligations: for example, to deliver gold if the arbitrageur has struck a deal to buy it, or to deliver money if the arbitrageur has sold gold. Procedures carried out by others must also be relied upon to ensure that gold in Riyadh is “the same” as gold in Manhattan. Others yet again may be needed to transport gold from one place to another. (When securities were paper certificates, their transportation from place to place and the risk of loss of them during such transportation were issues that arbitrageurs had to consider.) The “sameness” of gold is established by assay procedures “external” to the market that can be treated by market practitioners as a “black box”—a reliable process whose details they do not need to consider—and nowadays “transportation” of securities is also usually treated by traders as a black-box matter. However, many—probably most—current forms of arbitrage exploit discrepancies in the prices not of the “same” asset but of “similar” assets: Brazil 14s and 40s; stocks and stock-index futures; stocks and options on those stocks; Italian and German government bonds; newly issued (“on-the-run”) government bonds and previously issued (“off-the-run”) bonds; government bonds and bonds carrying implicit government guarantees but backed by pools of mortgages; the shares of the two legally distinct but economically integrated corporations that until 2005 made up the Royal Dutch-Shell group; and so on. The similarity of assets such as the Brazil 14s and 40s, or of shares in Royal Dutch and in Shell, depends, at least over the short and medium term, on others within the market treating them as similar, and the arbitrageur can seldom afford to treat this as a black box. The “similarity” of financial assets is always in a sense theory-dependent. Sometimes, the theory in question is a sophisticated mathematical model. At other times, the theory is vernacular and down-to-earth: for example, that the 40s will remain Brazil’s most liquid government bonds, or that the intended Eurozone would converge, making Italian bonds similar to German bonds. To embark upon arbitrage, traders thus have to convince themselves that the theory on which the arbitrage rests is correct, or at least plausible enough to be the basis of practical action. They will often also want to or need to

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convince others. In our observations of the hedge fund (and the observations of an investment-bank arbitrage trading room by Beunza and Stark 2004) there was much discussion of possible trades and of the theories underlying them, both inside the organization and in the form of analyses coming in from outside (and occasionally flowing in the opposite direction). Critical roles in these discussions are often played by material representations of value, such as the chart showing the recent history of the difference in prices between the 40s and the 14s, or a “spread plot,” showing the relative prices of Hewlett Packard and Compaq, which Beunza observed being closely followed in 2001–2 by “risk arbitrageurs” hoping to exploit the probable—but not certain—merger between the two corporations (Beunza and Muniesa 2005). But material representations are often not on their own conclusive: information about what other traders are doing—for instance, about the behavior of “real money” in the Brazilian bond market—can also be important in allowing the plausibility of theories to be judged. The need to convince others does not necessarily cease once a trader takes on an arbitrage position. Often, the price discrepancy that is being exploited will increase further before it decreases, which means that the arbitrageur will incur apparent losses. Sometimes, apparent losses are actual outflows of money or securities (or, at least, the electronic traces thereof), for example as a result of the daily process in which exchange clearing houses adjust the “margin” deposits that participants must maintain in order to be allowed to continue to hold their positions. At other times, there are no actual outflows, but as banks and hedge funds “mark to market” (revalue their trading positions, which is now also normally done at least daily), a position shows a loss. In either case, the losses will be temporary (the outflow will be replaced by an inflow, a “paper” loss will turn into a realizable profit) if the theory underpinning the arbitrage is correct, but others may need to be convinced of this to allow the arbitrageur to continue holding the position. In a large institution such as a bank, the immediately important audience for arbitrage is an arbitrageur’s manager or managers, who will normally be closely attentive to the “P&L” (profit and loss) figures of those they supervise. “There’s a saying in trading circles,” one trader and manager told us: “the white sheet [P&L sheet] doesn’t lie”—losses are real, and should be acted upon as if they are real. The arbitrageur’s problem, however, is that from his or her viewpoint the white sheet does often lie, at least temporarily. A common complaint among arbitrageurs is of being instructed by managers to liquidate loss-bearing positions that they were certain would become profitable. Even “textbook” arbitrages can be subject to this risk: the traders in the Japanese securities firm studied by Miyazaki (2003) reported being forced to abandon arbitrages between stocks and stock-index futures because of the apparent losses incurred when they had to deposit additional futures margin. Such management behavior may seem incomprehensible until one realizes that the boundary between arbitrage and speculation is porous, and it can be hard for managers to be certain that arbitrageurs have not in fact started to speculate on the rise or fall of prices. Two of the most celebrated “rogue traders”—Nick Leeson of Barings Bank and Jérôme Kerviel of Société Général—were arbitrageurs who covertly became very large-scale speculators.

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In hedge funds, the manager/arbitrageur divide is typically much less marked: even in large funds such as LTCM the two roles are not distinct. Investors, however, form a more immediate audience than they do in the case of banks. Hedge funds report changes in net asset values to their investors monthly, while banks report quarterly or less frequently (depending on the jurisdiction in which they are incorporated), and losses in a hedge fund’s trading are not masked by the profitability of other lines of business as they often are in banks. So a large loss by a hedge fund conducting arbitrage—even a “paper” loss—quickly becomes visible. One hedge fund manager (and former investment banker) told us that in a bank “you can justify why you want to hold on to those positions,” while hedge fund investors “don’t care. They just look at the number [change in net asset value].” The threat of investors withdrawing their capital from the fund is thus almost continuous: “there is very small tolerance to losing money. . . . [W]e cannot have a losing month.” The risk of arbitrageurs in a bank having to abandon their positions because of temporary losses is reduced if managers understand and accept the theory underpinning a trade, and thus believe that losses will indeed be temporary. One advantage of investment banks with long experience of arbitrage over newcomers such as the Japanese firm studied by Miyazaki is that this understanding is much more likely. Often, though, the technical details of arbitrage trading are daunting even to those with extensive market experience. In such cases, trust in arbitrage in practice often has to be trust in the arbitrageur or arbitrageurs as particular people, just as in many cases trust in science comes down to trust in the scientist (see Shapin 1994). A hedge fund, a university endowment manager, or an individual trader or trading desk at a bank who or which has built up a good reputation is more likely to be trusted. LTCM’s founder John W. Meriwether had led Wall Street’s premier arbitrage desk (at Salomon Brothers), and his colleagues included other traders with high personal reputations. They were able to have LTCM’s investors accept a three-year “lock-in” in which they were not allowed to withdraw capital, and even after the near bankruptcy in 1998 they successfully recruited investors to a successor fund, JWM Partners. Losses, even temporary, can, in addition, be avoided if other arbitrageurs and professional traders also come to view the price difference that an arbitrageur is exploiting as a discrepancy. In our hedge-fund observations, for example, we were struck by the extent of the circulation among traders in different funds and banks, mainly by electronic mail, of ideas for trading; and in wider interviews with professional traders we have found almost all pay much attention to what others seem to be doing. If that discussion and attention leads others also to seek to exploit a discrepancy, then their purchases and sales will narrow the discrepancy, or at least reduce the risk of it widening. That, for example, was why the trader discussed in this chapter’s second section wanted the chart displaying the 14s/40s anomaly circulated to others. “All I want is people even to talk about it,” the trader told us. If others also took action on the pricing anomaly, they would prevent it widening. Should it widen, the trader explained, he might even come to doubt his belief (the “theory” behind the trade) that the anomaly was a discrepancy that would close. “There might be a reason [for the anomaly]

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I don’t understand. I might have to reconsider the decision [to construct a trading position predicated on it narrowing].” Another way of minimizing the risk of premature capital withdrawal is diversification. If a fund, trading desk, or bank holds a wide variety of arbitrage positions—for example, in different parts of the world and in different asset classes—then, on the face of it, there is little likelihood of enough of those positions losing money simultaneously to create a serious overall loss. (The matched “long” and “short” positions characteristic of arbitrage mean that common factors such as global economic conditions, the levels of interest rates, and the buoyancy of stock markets should have little or no effect.) Diversification of this kind was, for instance, a core aspect of LTCM’s strategy. However, the constant attention of many professional traders to what others are doing may undercut the benefits of diversification. If large numbers of traders are led all to take similar positions, then arbitrages that “ought” to be uncorrelated can suddenly become linked. This, for example, was what caused LTCM’s diversification to fail. LTCM tried hard to keep its positions private: as a very large market participant with a largely locked-in capital base, it was concerned less with the benefits of others preventing discrepancies widening than with their trading causing the opportunities it was exploiting to diminish or vanish. However, others did frequently take on similar positions, either because they were following the same general strategy (in part in emulation of LTCM’s success) or because they learned specifics of LTCM’s trading from those who took the other side of those trades. “I can’t believe how many times I was told to do a trade because the boys at Long-Term deemed it a winner,” says one hedge fund manager (Cramer 2002: 179). The resultant overlapping set of arbitrage positions made it possible for an event to which LTCM itself had only a limited exposure—the Russian government’s default on its rouble-denominated bonds on August 17, 1998—to cause sudden, highly correlated, adverse price movements across the globe and in apparently unrelated asset classes. Arbitrageurs who incurred losses in Russia had to liquidate positions (even in apparently unrelated assets) to meet margin calls, withdrawals by investors, and other demands on their capital. In aggregate, the positions they sought to liquidate overlapped considerably with each other and with LTCM’s portfolio. These liquidations in turn caused more losses, leading to further liquidations, and so on in a disastrous, marketparalysing spiral. The sociality of arbitrage goes beyond relations to particular others such as managers, hedge fund investors, and other arbitrageurs: the conduct of arbitrage is affected deeply by the forms of action in financial markets that are seen as permissible and to be encouraged or as impermissible and to be discouraged. One persistent issue is the difference in this respect between the two standard “legs” of an arbitrage trade. Typically, a price discrepancy is exploited by buying (or in other ways taking a “long” position in) an undervalued asset, and short selling a similar overvalued counterpart. Long positions are almost always regarded as unproblematic, but short positions have historically often been the object of suspicion. Short sellers are frequently

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blamed for falls in price, and the activity is seen as morally reprehensible for other reasons: for instance, in current interpretations, borrowing securities in order to short sell them is contrary to Sharia, creating a problem for those who wish to set up “Islamic” hedge funds. In some markets (for example, Mexican government bonds) only specific, trusted market participants are allowed by regulators to sell short. In other markets short selling by a wide range of participants is permitted but is constrained in other ways. Until 2007, for example, short sales of stock in the US were subject to the “uptick rule” (see, for example, Robotti n.d.)—they were prohibited unless the last price change had been upwards—which could cause substantial delays in short selling if prices are falling consistently. Because the extent of the problems of short selling varies from asset to asset, systematic effects of these problems can be detected. Thus Dow Jones futures and other stock-index futures seem to tend more often to be below the value implied by the level of the underlying index than above it (Shalen n.d.). The trading required to exploit “overpricing” of futures is straightforward: the arbitrageur has to establish a short position in futures (which means simply selling futures, and involves no particular difficulties), while buying the stocks that make up the index (also straightforward). In contrast, exploiting “underpricing” of futures requires the arbitrageur to buy futures (again straightforward), but it also involves short selling the underlying stocks, which is, as noted, often more problematic.

Arbitrage and the Credit Crisis Arbitrage played a central role in the genesis of the credit crisis that erupted in the summer of 2007 and culminated in the near-collapse of the global banking system in autumn 2008. At the core of the crisis were two classes of structured security: asset-backed securities (ABSs) and collateralized debt obligations (CDOs). The constructor of an ABS or CDO sets up a legal vehicle (a trust or special purpose corporation), which buys a pool of mortgages or other forms of consumer debt (in the case of ABSs) or of corporate debt in the case of the original CDOs. (An important category of CDO known as ABS CDOs bought ABSs rather than corporate debts for their pool.) The money needed for this special purpose vehicle to buy the debt for its pool was raised by selling to investors securities that were claims on the cash flow generated by the debt. Those claims were “tranched”: the holders of the topmost tranche (“senior” or sometimes “super-senior”) had the first claim on the cash flows from the pool, which meant that this tranche was the safest. The holders of intermediate tranches (referred to as “mezzanine”) were next to have their claims met. At the bottom of the hierarchy was a tranche (known as the “first-loss piece” in the case of ABSs and “equity” in the case of CDOs), the holders of which were paid only after the claims of all the higher tranches had been met. This tranche was thus the riskiest. If there were defaults on the mortgages or other forms of debt making up the

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pool of an ABS or CDO, the holders of the lowest tranche were the first to suffer the consequent loss. Only if losses mounted to such a level that the lowest tranche was entirely wiped out would the holders of the next-lowest tranche suffer a loss. These different levels of risk were compensated in the form of higher interest payments on lower tranches, with the topmost tranche typically paying out only a small “spread” (that is, only a small increment over a benchmark interest rate such as Libor, or London Interbank Offered Rate). There were various motivations for setting up ABSs and CDOs. ABSs, for example, were initially created mainly as a way of raising capital for mortgage lending, while many of the early CDOs were designed to remove the risks of corporate lending from bank’s balance sheets. However, from the end of the 1990s onward, arbitrage became an increasingly important motivation, first in the case of CDOs (some of which were explicitly called “arbitrage CDOs”) and then for ABSs. The arbitrage was quite simple in conception: investors could be persuaded to buy the tranches of an ABS or CDO in return for payments that were, in aggregate, smaller than the cash flows from the debt in the ABS or CDO pool. If, in such a situation, the constructors of an ABS or a CDO could sell all its tranches to investors, they could capture the difference as risk-free arbitrage profit. What was being arbitraged in this case was directly social in nature: it was the authority of the credit-rating agencies and the way in which their ratings were built in to structures of governance in the financial markets. For example, pension funds in the United States are generally allowed to buy only securities with investment-grade ratings, and money-market funds are often restricted to the highest of those ratings. The capital-adequacy rules governing banking also gave banks themselves increasing incentives to hold securities with the highest ratings. The way in which the rating agencies evaluated ABSs and CDOs made it possible to create large tranches rated AAA out of pools of debt of lower credit quality. (For the details of the modeling procedures involved, and an account of the empirical research being drawn on here, see MacKenzie 2009b.) This may sound like alchemy (or deliberate wrongdoing by the rating agencies), but was in fact initially perfectly justifiable: even if the chances of default on any individual mortgage or corporate loan were far from tiny, combining those mortgages or loans in a pool meant that likely losses were reasonably predictable and could be absorbed by lower tranches and other forms of protection against default, greatly reducing the probability of the highest tranches incurring a loss. However, the very attractiveness of the consequent arbitrage had the effect of undermining the empirical accuracy of the models used to produce these ratings, at least in the case of mortgages. The capacity to package mortgages into ABSs, and then to package those ABSs into CDOs, greatly reduced incentives for caution in lending, and also made it possible for the volume of that lending to expand considerably, thus setting the scene for the crisis in the US mortgage market that started to become apparent in the second half of 2006 and reached disastrous levels from summer 2007 onwards.

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Huge losses for investors in ABSs and CDOs (especially ABS CDOs) were thus created, but perhaps most surprising was the extent to which those losses accumulated within the financial system itself, rather than being passed on to end investors. Especially in the case of ABS CDOs (the category of instrument that did most damage to the financial system), specific features of the arbitrage had the unintended consequence of concentrating rather than distributing losses. Most important were the super-senior tranches of ABS CDOs. As suggested above, those tranches could offer only very modest “spreads” without undermining the profitability of the arbitrage, and the low “spreads” meant that despite their AAA ratings, these tranches were hard to sell to external investors. Accordingly, banks tended to retain them themselves, frequently keeping the trade apparently riskless by “insuring” those tranches with the specialist bond insurers known as “monolines” or the financial products division of the giant insurer AIG. (Because the risk of loss on these super-senior tranches appeared very low indeed, the cost of purchasing this insurance was less than the spread offered by the senior tranches, so leaving a small arbitrage profit.) However, the giant scale on which the arbitrage was conducted meant that when losses did begin to hit even the AAA tranches of ABS CDOs, those who had insured those tranches against loss were often unable to meet their obligations. The US government had to step in and rescue AIG, and banks were often left with no alternative but to accept much lower payouts from monolines than those to which they were legally entitled. As noted, the sociality of arbitrage is here most evident in the role of credit ratings. The materiality of prices is also important in the market for ABSs, CDOs, and the “credit default swaps” that “insured” tranches of these products against loss. These instruments are not traded on an organized exchange such as those in Chicago, but directly negotiated between institutions, and the crucial such institutions were a small number (around a dozen) of major international banks, which, for example, acted as “market-makers” in credit default swaps, constantly quoting the prices at which they would “sell” protection against loss and “buy” such protection. The material form that these prices took was e-mail messages to other market participants such as more minor banks and hedge funds. Those messages were tailored to the particular client: large-scale, valued clients were often offered better prices than smaller ones. Clearly, such practices depended upon keeping control of the circulation of prices, so that less favored clients would not know the better prices being offered to others. However, a specialist firm, CMA, created a system, known as “QuoteVision,” which parsed the incoming e-mail messages received by all its subscribers, extracted the prices from them, and made those prices available to each subscriber. In response, many of the major market-makers started to send out price quotes in the form of e-mail messages that could not be forwarded to the QuoteVision system. However, CMA has been able to circumvent this by developing a system that electronically “scans” incoming e-mails (even if these are not forwardable), and continues to extract prices from them. The materiality of prices is thus at the heart of a subterranean conflict in this area, between the large market-making banks and their frequently smaller, less prominent clients.

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Conclusion Our argument in this chapter has been that arbitrage—how it is practiced, its risks, its uncertainties, its limits, and its capacities to weld markets together into a financial system—can properly be understood only if it is grasped in its full materiality and sociality. That kind of rich, qualitative understanding is, of course, different from the more abstract but quantitatively more precise understanding typically sought by economists, even “behavioral finance” specialists. Nevertheless, there are areas of overlap between a “social studies of finance” perspective and financial economists’ investigation of the consequences of relaxing their discipline’s traditional purist definition of arbitrage. For example, Shleifer and Vishny (1997) model the risk that those who provide arbitrageurs with capital will withdraw it prematurely in the face of temporarily adverse price movements. Brav and Heaton (2002) address what in our terms is the difficulty that arbitrageurs can have convincing themselves and their audiences that a price pattern is indeed a discrepancy that can be the object of arbitrage. In circulating the chart of the price history of the Brazil 14s and 40s, the trader we observed was seeking to solve in practice the problem modeled by Abreu and Brunnermeier (2002): the limit to arbitrage that can arise when “rational traders face uncertainty about when their peers will exploit a common arbitrage opportunity” (2002: 341). Attari, Mello, and Ruckes (2005) model a risk that became very pertinent for LTCM after the fund’s difficulties became known to others at the start of September 1998, but of which all large arbitrageurs need to be wary: that the combination of capital constraints and positions known to other traders can make arbitrageurs’ actions predictable and exploitable. Shleifer and Vishny, Brav and Heaton, Abreu and Brunnermeier, and Attari, Mello, and Ruckes put forward four separate models, each capturing one of the aspects that we posit as intrinsic to arbitrage as market practice. No integrated model has yet emerged from the literature in economics on the limits of arbitrage, but our research suggests that it is in the interaction of arbitrage’s aspects that its crucial limits may reside. Thus the crisis surrounding LTCM arose from the way in which the process of capital withdrawal modeled by Shleifer and Vishny interacted with the consequences of others imitating a single prominent arbitrageur, and LTCM’s crisis was worsened (to a degree that is hard to determine) by other traders “arbitraging the arbitrageur” in the manner modeled by Attari, Mello, and Ruckes. We would therefore be hopeful that the study of arbitrage could be a productive area of collaboration between financial economists and those in the wider social sciences prepared to tackle financial markets in their full materiality and sociality. We are, in addition, certain that arbitrage is a pivotal topic for the sociology of finance. The details of arbitrage may seem to be little things, but they are little things connected to big issues such as the credit crisis. The powers and limits of arbitrage are critical to global financial markets, and the material sociology we advocate is needed to understand them.

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Notes 1. Earlier versions of this chapter appeared as Beunza, Hardie, and MacKenzie (2006) and MacKenzie (2009a: ch. 5). Hardie’s and Mackenzie’s research is supported by the European Research council (grant 291733, EPIFM). We thank Daniel Beunza warmly for his contribution to the original version. 2. Our research on the hedge fund is described in detail in Hardie and MacKenzie (2007).

References Abreu, D. and Brunnermeier, M. D. (2002). “Synchronization Risk and Delayed Arbitrage.” Journal of Financial Economics, 66: 341–60. Attari, M., Mello, A. S., and Ruckes, M. E. (2005). “Arbitraging Arbitrageurs.” Journal of Finance, 60: 2471–511. Beunza, D., I. Hardie, and D. MacKenzie. (2006). “A Price is a Social Thing: Towards a Material Sociology of Arbitrage.” Organization Studies, 27: 721–745. —— and Muniesa, F. (2005). “Listening to the Spread Plot,” in B. Latour and P. Weibel (eds.), Making Things Public: Atmospheres of Democracy. Cambridge, MA: MIT Press, 628–33. —— and Stark, D. (2004). “Tools of the Trade: The Socio-Technology of Arbitrage in a Wall Street Trading Room.” Industrial and Corporate Change, 13: 369–400. Brav, A. and Heaton, J. B. (2002). “Competing Theories of Financial Anomalies.” Review of Financial Studies, 15: 575–606. Cramer, J. J. (2002). Confessions of a Street Addict. New York: Simon & Schuster. Hardie, I. (2004). “ ‘The Sociology of Arbitrage’: A Comment on MacKenzie.” Economy and Society, 33: 239–54. —— and MacKenzie, D. (2007). “Assembling an Economic Actor: The Agencement of a Hedge Fund.” Sociological Review, 55: 57–80. Knorr Cetina, K. and Bruegger, U. (2002). “Inhabiting Technology: The Global Lifeform of Financial Markets.” Current Sociology, 50: 389–405. Lynn, C. (2004). Leg the Spread: A Woman’s Adventures inside the Trillion-Dollar Boys’ Club of Commodities Trading. New York: Broadway. MacKenzie, D. (2003). “Long-Term Capital Management and the Sociology of Arbitrage.” Economy and Society, 32: 349–80. ——(2006). An Engine, not a Camera: How Financial Models Shape Markets. Cambridge, MA: MIT Press. ——(2009a). Material Markets: How Economic Agents are Constructed. Oxford: Clarendon. ——(2009b). “The Credit Crisis as Problem in the Sociology of Knowledge.” http://www.sps. ed.ac.uk/staff/sociology/mackenzie_donald (accessed March 1, 2010). Miyazaki, H. (2003). “The Temporalities of the Market.” American Anthropologist, 105/2: 255–65. Robotti, P. (n.d.). “Arbitrage/Short Selling: A Political Economy Approach.” Unpublished typescript. Rubin, R. E. and Weisberg, J. (2003). In an Uncertain World: Tough Choices from Wall Street to Washington. New York: Random House.

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Shalen, C. (n.d.). “The Nitty-Gritty of CBOTR DJIASM Futures Index Arbitrage.” (accessed July 30, 2005). Shapin, S. (1994). A Social History of Truth: Civility and Science in Seventeenth-Century England. Chicago: University of Chicago Press. Shleifer, A. and Vishny, R. W. (1997). “The Limits of Arbitrage.” Journal of Finance, 52: 35–55. Stark, D. (2009). The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton, NJ: Princeton University Press. Zaloom, C. (2006). Out of the Pits: Trading and Technology from Chicago to London. Chicago: University of Chicago Press.

chapter 11

seei ng through the ey es of others: dissona nce w ithin a n d across tr a di ng rooms d aniel b eunza and d avid s tark

The starting point of our chapter is the long-standing notion that diversity contributes to system performance. As Michael Hannan observes, economic systems with a greater variety of organizational forms are more responsive to environmental change: Organizational diversity . . . constitutes a repository of solutions to the problem of producing certain sets of collective outcomes. These solutions are embedded in organizational structures and strategies. If so, reductions in organizational diversity imply losses of organized information about how to adapt (produce) to changing environments . . . A system with greater organizational diversity has a higher probability of having in hand some solution that is satisfactory under changed environmental conditions. (Hannan 1986: 85)

For organizational ecology, the key unit of analysis is a population of organizations. System performance can be examined at the societal level, as Hannan notes: “A society that retains only a few organizational forms may thrive for a time. But once the environment changes, such a society faces serious problems until existing organizations can be reshaped or new ones created” (Hannan 1986: 85). For the population ecologists, then, adaptability is promoted by the diversity of organizations. Systems with a greater diversity of organizational forms will outperform those with lower diversity. But if diversity matters for a population of organizations, we ask, might it also matter at the level of the firm itself? If system performance is enhanced at the level of a population of firms by greater diversity of organizational forms, we argue that diversity also contributes to system performance at the level of the firm. In this chapter we explore the crucial role of diversity in the context of a financial organization. Financial trading firms have been examined from several contending

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approaches. Neo-institutionalism emphasizes norms, scripts, and routines (Abolafia 1996; Zorn 2004); network analysis focuses on embeddedness and patterns of connectedness (Baker 1984; Mizruchi and Stearns 1994); and science and technology studies (STS) turn attention to the socio-technologies of calculation (Beunza and Stark 2004; Preda 2006). Although we draw on all of these perspectives, we take organizational ecology as our launching point. Ours, however, is not a mechanical application of organizational ecology. First, whereas the ecologists stress diversity of organizations, we turn attention to the organization of diversity. In place of population dynamics, we consider dynamics that involve interactions across diverse evaluative principles. Diversity is a prerequisite but it will not yield performance-enhancing effects unless there is some more or less organized interface through which heterogeneous principles interact. Organizational diversity is most likely to yield its fullest evolutionary potential when different organizational principles coexist in an active rivalry within the firm (Stark 2009). For the population ecologists, change takes place through selection, as some firms die and others are born. Our view also draws on metaphors from evolutionary biology, but here we emphasize mating: change takes place by cross-fertilization, yielding new combinations. Diversity matters not because it preserves already-known solutions at hand. Instead, it contributes to adaptability by preserving a more diverse organizational “gene pool,” increasing the likelihood of possibly fruitful recombinations in times of unpredictable change. Note that this modification considers more radically unexpected environmental change for which there might not be pre-existing solutions. The notion that diversity makes a positive contribution to performance is supported by diverse types of evidence. James March’s (1991) simulation in “Exploitation and Exploration in Organizational Learning” finds that groups composed of uniformly quick learners frequently underperform when compared with groups with a mix of quick and slow learners. Organizations that learn too quickly veer toward exploitation at the expense of exploration, thereby locking themselves in to suboptimal routines and strategies. Santa Fe Institute economist Scott Page (2007) runs similar simulations but modifies some of the parameters. He demonstrates that a pool of problem solvers with less ability but with more diverse perspectives outperforms a pool of more uniformly able problem solvers because the latter quickly find merely local optima. From these simulations and other game-theoretic research, Page concludes: “Diversity trumps ability.” Diversity matters not only in problem solving but also in problem generating, as Lester and Piore show in their study of innovations in the fields of mobile telephones, fashionable blue jeans, and medical equipment. The cell phone, for example, emerged in the space created by the ambiguity about whether the product was a radio or a telephone. These technologies each claim a distinct commercial and engineering tradition and Lester and Piore (2004: 17) emphasize that “the cultural differences between radio and telephone engineering were deep rooted.” In their field research into a new media startup, Girard and Stark (2002) found a positive role for friction among the diverse communities of programmers, designers, business strategists, information architects, and

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merchandising specialists (Stark 2009).1 Like that work, our emphasis here is on cognitive diversity (such as that of the different evaluative principles of diverse disciplines) and not on demographic diversity.2 For these reasons, in place of diversity (the existence of difference) we prefer dissonance. The notion of dissonance captures the idea that diverse principles are not merely copresent but are interacting in ways that are not immediately harmonious (Stark 2009). This is more than simple difference, and it is certainly not indifference. This is difference with an edge. And, precisely because it is discordant, it can be a resource, as we elaborate below. Like infantry officers who instructed drummers to disrupt the cadence of marching soldiers while they were crossing bridges, less the resonance of uniformly marching feet bring calamity, we draw the lesson that dissonance contributes to organizational learning and economic evolution. We also depart from the first generation of population ecology theorizing3 in that we view organizations as cognitive ecologies. Trading rooms, like many organizations, face two major cognitive challenges. The first is the challenge of recognizing opportunities. This can take the form of recognizing that some market configuration corresponds to a pattern that has already been identified (pattern recognition) or it can take the form of identifying some new, previously unrecognized, configuration (practices of re-cognition). Think of the former as exploiting existing knowledge and the latter as innovative exploration for new knowledge. The second cognitive challenge is that of recognizing error. At first glance it might seem that the solutions to the cognitive problem of innovation are quite different from solutions to the cognitive problem of error detection. But although innovation and error detection can be analytically distinguished, in practice the two are not entirely different. In fact, at the extremes, the cognitive challenges are remarkably similar. In terms of recognizing new opportunities, the more radical the innovation, the more it breaks with conventional categories. In terms of error detection, the greatest errors are not those such as entering the wrong number into a database but those in the categorical structure of the database itself. And, in both areas, the greatest challenge is not to be locked in to the cognitive structures produced by one’s successes. Cognitive lock-in impedes innovation, and it can lead to disasters when errors are not detected. It is for these twinned reasons that we make a positive case for dissonance. As the organization of diversity, dissonance counters lock-in. As we shall see, disparate valuation metrics in the trading room provide multiple vantage points to test the market. In place of one overarching principle for assessing value, several are contending. Interaction across these metrics provides opportunities for innovation. We shall also demonstrate that the organization of dissonance provides traders with opportunities to be reflexive about the models they deploy. Dissonant cues—episodic, as we shall see, even in the course of a single morning—can serve as a kind of epistemic rupture, stimulating traders to reassess and recalibrate their models. Over the past decades, the American economy has been reshaped by a resolute growth in the economic clout and significance of its capital markets. Within companies, the change has been charted by a few key studies that documented the rising influence of

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shareholders in American corporations (Davis and Greve 1997; Davis and Mizruchi 1999; Fligstein 1990; Useem 1996). But the “financialization” of the American economy has gone far beyond corporate hierarchies (Blackburn 2005; Krippner 2005). With the rise of so-called quantitative finance, investment has been reshaped in a more radical, abstract, and intricate manner. This chapter has two parts. For each we draw on our ethnographic research among arbitrage traders in a major international investment bank. We first analyze the organization of diversity within the trading room itself. We then turn to examine the role of externally induced dissonance. In section one, we observe that locational proximity of diverse tools and instrumentation within the trading room allows traders to understand the limitations of their valuation practices. To express this with a metaphor: you are wearing colored glasses, but the social interaction with colleagues who wear glasses of a different color reminds you of your own partial view of the world. In the second section, externally induced dissonance allows traders to recognize the limits of their models. All models are built on the basis of the past, and as a consequence they are all liable to miss a future contingency. Using specialized quantitative techniques that extend the cognitive ecology beyond the confines of the trading room, traders are able to use the price mechanism to gain a sense of what their competitor’s models are. They use this information to check whether their models are missing something. In both cases, dissonant diversity allows the traders to grapple with the mismatches between the representations of the environment they created and changes in the environment itself. In the first case, communication takes place in the form of face-to-face conversations across valuation regimes. These require an entire organizational setup of high trust, cohesiveness, flat hierarchy, and shared space. In the second case, communications take place through a number—the “spread”— combined with a model, and without any explicit message. Traders do not need to belong to the same network as their competitors, they do not need to talk to them— and indeed they do not need to have met them or even to know who they are. Communication in such a thin setup is possible because traders operate in the very same valuation regime.

Internal diversity Our argument is based on ethnographic field research we conducted in the Wall Street trading room of a major international investment bank. Pseudonymous International Securities is a global bank with headquarters outside the United States. It has a large office in New York, located in the World Financial Center in Lower Manhattan with about 160 traders, and its arbitrage unit is located within it.

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The challenge of arbitrage Arbitrage, that seemingly gray pursuit of financial mispricings, has recently become the subject of a notorious academic debate within economics. On the one hand, orthodox economists portray arbitrageurs as the ultimate enforcers of market efficiency: whether as medieval Florentine currency dealers or modern derivatives traders, arbitrageurs are attributed with the ability to discipline prices, prick bubbles, and purge the market from irrational investors (Fama 1965; Friedman 1953). On the other hand, scholars in behavioral finance argue that arbitrageurs are severely limited in their disciplining role. Even if the detached, sophisticated, and relentlessly calculative arbitrageurs invoked by orthodox scholars can safely be assumed to exist, the exuberance, biases, and sheer humanity of retail investors limit the effectiveness of arbitrageurs’ imitation (Scharfstein and Stein 1990; Shiller 1984; Shleifer 2000). Like drunken drivers in a congested highway, the wayward moves of nonprofessionals wreak havoc with the neat investment plans of arbitrageurs, discouraging the latter from pursuing opportunities. This debate is a timely examination of a crucial activity that has traditionally been under-studied in economic sociology. Indeed, several notable episodes of our recent financial history suggest that arbitrage might be as destabilizing as efficiency-inducing. Thus, for instance, arbitrage in market indices was blamed for the 1987 stock market crash (MacKenzie 2006). Currency arbitrage was associated with the 1992 expulsion of the British pound from the European Currency Unit (ECU). Fixed income arbitrage appears to have led to the implosion of LTCM fund in 1998. Energy arbitrage was linked to the Californian brownouts induced by Enron traders. Thus, arbitrage has profound political and legal ramifications that need to be explored. The arbitrageurs we studied locate value by making associations among securities. At the sophisticated level of trading at International Securities there is a sharp premium on making novel, unexpected, and innovative associations. Arbitrage is a distinctive form of entrepreneurial activity that exploits not only gaps across markets but also the overlaps among multiple evaluative principles. Arbitrageurs profit not by having developed a superior way of deriving value but by exploiting opportunities exposed when different evaluative devices yield discrepant pricings at myriad points throughout the economy. As with value and momentum investors, arbitrageurs need to find an opportunity, an instance of disagreement with the market’s pricing of a security. They find it by making associations. Instead of claiming a superior ability to process and aggregate information about intrinsic assets (as value investors do) or better information on what other investors are doing (as momentum traders do), the arbitrage trader tests ideas about the correspondence between two securities. Confronted by a stock with a market price, the arbitrageur seeks some other security—or bond, or synthetic security such as an index composed of a group of stocks, and so on—that can be related to it, and values one in terms of the other. The posited relationship can be highly abstract. The two securities have to be similar enough so that their prices change in related ways, but different enough so that other traders have not perceived the correspondence before. The tenuous

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or uncertain strength of the posited similarity or covariation reduces the number of traders that can play a trade, hence increasing its potential profitability. In short, arbitrage hinges on the possibility of interpreting securities in multiple ways. Like a striking literary metaphor, an arbitrage trade reaches out and associates the value of a stock to some other, previously unidentified security. By associating one security to another, the trader highlights different properties (qualities) of the property with which he is dealing. As we studied how the room is organized for this process of discovery, we came to see that the trading room is a kind of laboratory in which traders are engaged in a process of search and experimentation. They use instruments to test the markets. At one level it would seem that their search is straightforward: they are searching for value. And it would seem that the means for this search are similarly obvious: use channels of high-speed connectivity to gather as much timely information as possible and take advantage of sophisticated mathematical formulae to process that information. Among the very elite of the profession, however, these means in themselves do not give advantage. You must have them to be a player, but your competitors are likely to have them as well. That is, the more that timely information is available simultaneously to all market actors, the more advantage shifts from economies of information to processes of interpretation. Moreover, what seems straightforward—value—is exactly what is at issue. The challenge of search and experimentation must thus be re-specified: How do you recognize an opportunity that your competitors have not already identified? At the extreme, therefore, you are searching for something that is not yet named and categorized. The problem confronting our traders, then, is a problem fundamental to innovation in any setting: How do you search—when you do not know what you are looking for but will recognize it when you find it? (Stark 2009). The cognitive challenge facing our arbitrage traders is, thus, the problem of recognition. On one hand, they must be adept at pattern recognition (e.g., matching data to models, etc.). But if they only recognize patterns familiar within their existing categories, they would not be innovative (Brown and Duguid 1998; Clippinger 1999). Innovation requires another cognitive process that we can think of as re-cognition (making unanticipated associations, reconceptualizing the situation, breaking out of lockin). In James March’s (1991) terms, the problem is how to exploit the knowledge they already have while also exploring for new opportunities.

Pattern recognition at the desks The trading room is equipped to meet this twin challenge of exploiting knowledge (pattern recognition) while simultaneously exploring for new knowledge (practices of recognition). Each desk (e.g., merger arbitrage, index arbitrage, etc.) is organized around a distinctive evaluative principle and its corresponding cognitive frames: metrics, “optics,” and other specialized instrumentation for pattern recognition (Hutchins, 1995). That is,

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the trading room is the site of diverse, indeed rivalrous, principles of valuation. And it is the interaction across this heterogeneity that generates innovation. The basic organizational unit of the trading room is a “desk,” and it is here that the organization of diversity in the trading room begins by demarcating specialized functions. The term “desk” not only denotes the actual piece of furniture where traders sit, but also the actual team of traders—as in “Tim from the equity loan desk.” Such identification of the animate with the inanimate is due to the fact that a team is never scattered across different desks. In this localization, the different traders in the room are divided into teams according to the financial instrument they use to create equivalencies in arbitrage. Each desk has developed its own way of looking at the market, based on the principle of equivalence that it uses to calculate value and the financial instrument that enacts its particular style of arbitrage trade. Merger arbitrageurs draw on the “spread plot,” a representation that helps them assess the likelihood that an announced merger between two firms will actually be consummated. Convertible bond arbitrageurs, by contrast, do not obsess about whether the spread between two merging companies is widening or narrowing. Instead, they specialize in information about stocks that would typically interest bondholders, such as their liquidity and likelihood of default. At yet another desk, index arbitrageurs, in their attempt to exploit minuscule and rapidly vanishing misalignments between S&P 500 futures and the underlying securities, specialize in technology to trade in high volume and at a high speed. Thus, within each team there is a marked consistency between its arbitrage strategy, its evaluative principle, its visual displays, its mathematical formulae, and its trading tools. To be opportunistic, you must be attached to a principle.

Re-cognition across principles The desk, in our view, is a unit organized around a dominant evaluative principle and its arrayed financial instruments (devices for measuring, testing, probing, cutting). This principle is its coin—if you like, its specie. But the trading room is composed of multiple species. It is an ecology of evaluative principles. Complex trades take advantage of the interaction among these species. To be able to commit to what counts, to be true to your principle of evaluation, each desk must take into account the principles and tools of other desks. Shaping a trade involves disassociating some qualities in order to give salience to the ones to which your desk is attached. To identify the relevant categories along which exposure will be limited, shaping a trade therefore involves active association among desks. Co-location, the proximity of desks, facilitates the connections needed to do the cutting. To see opportunities, traders use the mathematics and the machines of market instruments. We can think of traders as putting on the financial equivalent of infrared goggles that provide them with the trader’s equivalent of night vision. The traders’ reliance on such specialized instruments, however, entails a serious risk. In bringing some informa-

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tion into sharp attention, the software and the graphic representations on their screens also obscure. In order to be devices that magnify and focus, they are also blinders. The danger is that distributing calculation across their instruments amounts to inscribing their sensors with their own beliefs. As we have seen, in order to recognize opportunities, the trader needs special tools that allow him to see what others cannot. But the fact that the tool has been shaped by his theories means that his sharpened perceptions can sometimes be highly magnified misperceptions, perhaps disastrously so. What the layout of the trading room—with its interactions of different kinds of traders and its juxtaposition of different principles of trading—accomplishes is the continual, almost minute-by-minute, reminder that the trader should never confuse representation for reality. Just as Latour (1987) defined a laboratory as “a place that gathers one or several instruments together,” trading rooms can be understood as places that gather diverse market instruments together. Seen in this light, the move from traditional to modern finance can be considered as an enlargement in the number of instruments in the room, from one to several. The best scientific laboratories maximize cross-fertilization across disciplines and instruments. For example, the Radar Lab at MIT in the 1940s made breakthroughs by bringing together the competing principles of physicists and engineers (Galison 1997). Similarly, the best trading rooms bring together heterogeneous value frameworks for creative recombination. We saw such processes of re-cognition at work in the case of an announced merger between two financial firms. Through close contact with the merger arbitrage desk and the equity loan desk, the traders were able to construct a new arbitrage trade, an “election trade,” that recombined in an innovative way two previously existing strategies, merger arbitrage and equity loan (for details of this interaction, see Beunza and Stark 2004: 386–9). The argument so far makes it clear that diversity in the organization of the trading room was key for preventing lock-in. We now examine whether diversity among trading rooms serves a similar purpose—and, if so, how it does so.

External diversity In the first part of this chapter we analyzed the trading room as an ecology of disparate practices of valuation. To do so, we examined the trading room as an ensemble of desks. We turn now to a single desk—merger arbitrage. But this focus on a particular strategy reveals that the cognitive ecology of the traders at the merger arbitrage desk is not limited to the trading room. Instead, the organization of dissonance extends beyond its confines. If diversity within the trading room is key to preventing lock-in, we shall also see that diversity among trading rooms serves a similar purpose. Let us return to the merger arbitrage desk discussed above. The basic principle of modern arbitrage is to exploit mispricings across markets. These situations arise when two different regimes of value coexist in ambiguity (Beunza and Stark 2004), and merger

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arbitrage is no exception. In the case of mergers, the ambiguity arises from the fact that a company is being bought. The acquiring firm typically buys the target company at a price well above its market capitalization, leading to two possible valuations: if the merger is completed, the price of the company will rise up to its merger value; if it is not, the price will drop back to the level before the merger announcement or lower. Arbitrageurs exploit the ambiguity as to which of the two will apply by speculating on the probability of merger completion. To the arbitrageurs, therefore, profiting from mergers boils down to successfully estimating a probability. How does dissonance help the merger desk? A merger trade entails a two-part operation. Arbitrageurs first develop their own sense of merger probability, and then mobilize external diversity. To illustrate how this happens, we turn to the morning of May 27, 2003. On that date, two companies had announced their intention to merge. (These were two for-profit education firms, Whitman and Career Education.) We first observed how the arbitrageurs accomplished the first of the aforementioned two steps: sizing up the nature of the newly announced merger. They did so by categorizing the merging firms and drawing analogies with other mergers. These associations came from conversations at the desk, from experience with other mergers, and from a database that they carefully maintain. The cognitive associations allowed traders to develop a probability estimate. After two hours of sensemaking, the traders looked at the prices and decided to take a small position, buying a few shares and putting their money where their models were.4 The arbitrageurs had deployed their sophisticated quantitative tools and taken a position. But no matter how sophisticated their tools, arbitrageurs are acutely aware that their models are fallible. Traders confront their own fallibility by distancing themselves from the categories and procedures that guided them to an initial position. This, however, is easier said than done. Mental awareness of the limits of one’s view does not automatically provide a check against these limits. Traders, we found out, gain cognitive distance from their categories by exploiting the fact that other arbitrageurs have also taken positions on this trade. It is to the second moment of a distributed cognition— across a socio-technical network outside the trading room—that we turn. Two hours after taking the position, the traders saw that the “spread,” or difference in prices between the two companies, was the same as in the early morning. This worried them. “Are we missing something?” they asked. And they started searching for missing information. Why did the spread worry the traders? The arbitrageurs, we found out, consider the spread to be a measure of the confidence that “the market” has in the successful completion of the merger. If the merger goes through, the two companies will have the same price, and the spread will be zero. If, on the other hand, the merger is cancelled, the prices of the two companies will revert to their original difference, and the spread will widen. Traders thus use the spread to see the probability that other traders assign to the merger. The spread has a magic element to it: it tells you what your competitors think, without any need for explicit communication. Using the spread plot involves semiotic sophistication. In this complex system of signs (Muniesa 2007; Peirce 1998), the spread plot provides each trader with an indirect sign

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of the likelihood of the merger, achieved by signaling the aggregate of his or her rivals’ assessment of that likelihood. The arbitrage trader, however, is not interested in the spread plot as a sign of what others are doing in the market. They read the spread as a sign of an event that will or will not happen in the world—the merger. The promising aspect of this sign is that it is quasi-independent of a trader’s own estimates of the probability of merger. The arbitrage trader is not a technical trader who, like the fashionista who monitors others to anticipate the hottest clubs, seeks to profit by anticipating market trends. Instead, arbitrageurs use the movements of their rivals as a check on their own independent opinion, rather than a substitute for it. The developments described above suggest that the traders’ caution unfolds as the confrontation between two related magnitudes. A trader’s ability to mobilize prices for greater precaution hinges on the encounter between the probability of the merger (estimated at the desk) and implied probability (derived from the spread plot). This comparison provides an invaluable advantage: it signals to traders the extent of their deviation from the market, warns against missing information, motivates additional search, prompts them to activate their business contacts, and provides the necessary confidence to expand their positions. This distinctive interplay of internal and external estimates points to a novel use of economic models, which we refer to as reflexive modeling. The expression denotes the process whereby dispersed market actors employ economic models to confront their own estimates. This confrontation pits a trader’s estimates against those of his or her rivals, thereby introducing dissonance in his or her calculations. This dissonance is attained through the construction of implied probability. This variable is a representation of an economic object that does not have a price, is otherwise not observable, and is coproduced by the positioning of actors who use it to confront their interpretations and re-evaluate their positions. Collectively produced, the implied probability is a device for dissonance. Reflexive modeling thus denotes a heightened awareness on the part of the arbitrageurs about the limits of their own representations of the economy. This reflexivity is not a mental process or a solipsistic practice. In its simplest form, reflexivity rests on the contraposition of two material artifacts—the arbitrageur’s screens. The first, an Excel spreadsheet, summarizes how the traders think about the merger. The so-called Trading Summary builds on a web of associations, including categories and analogies, leading up to the key issue facing the deal. The second screen, the spread plot, is shared by all arbitrage funds and captures how competitors think about the merger by showing the difference in the prices between the merging companies. Reflexivity is made possible by the dissonance between the two screens. Dissonance offers cues that the arbitrageurs might be missing a relevant obstacle to the merger. The premise of the system is that whenever an arbitrageur misses a relevant merger obstacle, rival arbitrageurs with a different view will prompt a dissonant chord (a spike in the spread plot), leading to additional search and correction. Thus, the dual-screen system lets arbitrageurs look at their own associations against those of their rivals. Arbitrageurs compare the two representations and exploit the difference for reflexive purposes.

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Instead of substituting search with imitation, as in mimetic isomorphism, arbitrageurs use social cues to complement their search. As a practice of using a model to gain cognitive distance, reflexive modeling is thus a cognitive process. But it is not taking place in the heads of the traders, as if cognition could be turned back onto itself. Just as the cognitive process of deriving their own probability estimates is socially distributed across the tools and instruments at the arbitrage desk, so reflexive cognition (Stark 2009) is a socio-technical process of distributed cognition triggered by the spread plot—a device for dissonance that is itself a socio-technically constructed object. The traders we observed were not engaging in some heroic mental feat, splitting and twisting their minds back on themselves like some intellectual variant of a flexible contortionist. Instead, as we saw numerous times in a single morning at a single trading desk, the taken-for-granted elements of their models were cognitively disrupted by devices for dissonance. Despite the above, there is a dark side to reflexive modeling, which illustrates the problems that arise in situations that lack diversity. We only discovered this dark side by analyzing the history of crises in merger arbitrage. Consider the failed merger between General Electric (GE) and Honeywell in 2001. This is an example of what economists call “arbitrage disasters.” An arbitrage disaster takes place when two companies unexpectedly cancel their promised merger, inflicting widespread losses on the arbitrageurs betting on its success. In June 2001, European commissioner Mario Monti decided to block the GE–Honeywell merger because of antitrust concerns. To the merger arbitrage desks in hedge funds and investment banks, the decision was unexpected, for it had already been approved in United States (and, after all, the two companies were American). The Europeans were expected to defer. The cancellation led to collective losses estimated at $2.8 billion—large enough to push most merger desks into the red for the year. Our analysis of the disaster suggests it was caused by a failure of reflexive modeling. Admittedly, we were not in the trading room on that day. But the very same traders we visited in 2003 had been active on GE–Honeywell in 2001, and we interviewed them. The traders’ comments support our view. “Max traded it,” said the manager of the trading room, confirming that his senior merger trader was active in the deal. And the trader had not anticipated Monti’s move: “everyone’s database lacked a field, and the field was ‘European regulatory denial,’” the manager added. But a disaster takes more than missing a risk factor. The initial lapse was made worse by the very tool that arbitrageurs used to stay safe—reflexive modeling. This is clear from the second step described by the manager of the derivatives trading room. “I encouraged him [Max] to increase his size,” he said. “You have confidence, all of your fields are fine.” In other words, the traders escalated their bet. And the decision to do so was not simply based on their model, but also on the comparison with others in the market. This comparison, however, was indirect rather than direct, as it took place through the spread. A more systematic analysis confirms the role of reflexive modeling in the GE–Honeywell disaster (see Beunza and Stark 2012). Arbitrageurs initially assigned a very large implied probability to the completion of the merger. Reports from the financial

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press confirm this point. Furthermore, the banks and funds which were active on the deal decided to ignore the danger of Monti’s threats. This can be deduced from a comparison between the spread and the media responses to the Commission’s actions (see Beunza and Stark 2012). We counted the number of weekly articles published in the major business press that included in their text the words “Honeywell” and “Monti.” A spike in the number of articles on February 27, 2001, suggests that the media had genuine concern about European opposition. But even as the media voiced these concerns, the narrow spread between the merging companies barely moved. In short, unlike the media, the traders’ models did not pick up the danger of European regulatory opposition. Our takeaway from this event is that there are limits to the uses that traders can make of dissonance. The same reliance on dissonance put in place by the traders to avoid their own mistakes can also lead to their own undoing. For even though reflexive modeling improves trading on the basis of dissonance, it can lead to financial disaster in the presence of resonance. Such resonance takes place when the combined use of models and stock prices gives traders misplaced confidence in an event. Our analysis provides a contrasting narrative to the behavioral theories of herding and the Black Swan. Our account of the GE–Honeywell incident differs from herding and its associated imagery of traders as lemmings, willing to abandon their views for the sake of conforming to the masses. What we saw, however, is that the traders were reinforced in their own view—wrongly reinforced, unfortunately—by the use of the spread. They were cheered, not repressed. Resonance also differs from Black Swans. According to the Black Swan theory, the combination of financial models and unforeseen contingencies leads to crises. But our findings suggest otherwise. First, the possibility of European regulatory opposition was not a surprise—the traders knew about it. Every mainstream business publication we consulted had some reference to this contingency. It is only reasonable to expect that the professional traders read the newspapers, and in fact the traders that we followed assumed that everyone in the bank read the cover of The Wall Street Journal every day. In sum, neither herding nor the Black Swan can explain the disaster of GE–Honeywell. The crisis was the outcome of a procedure—reflexive modeling—that failed to accomplish its goal. And, crucially, one would only know about it by being in the trading room. These considerations point to the benefits of adopting a sociological perspective in the study of finance. Implicit in the behavioral account of crises is the psychological view that trouble happens because of essential flaws in the character of individuals, with investors portrayed as either mindless lemmings or reckless users of models. Our analysis offers a very different view. It shows that the cause of the disaster was a malfunctioning of the reflexive mechanism described above. Reflexive modeling works by providing traders with dissonance whenever their estimates are different from those of the majority—and, therefore, possibly mistaken. Conversely, traders take the absence of dissonance as a source of reassurance: as proof that the estimate they have developed is correct. The widespread diffusion of this typically safe modus operandi gives rise to

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the possibility of widespread failure. When a trader’s position becomes everyone else’s green flag, cognitive interdependence is created. If enough traders miss a key variable, their mistake will reverberate to the others through the implied probability. As resonance develops in the system, traders will develop a false confidence that their views are correct, locking them into their positions and leading them to accumulate losses in the event of merger cancellation. Our analysis shows that such resonance was the cause behind the GE–Honeywell arbitrage disaster. Our analyses of the trading room and the spread plot point to a consistent message. In dealing with the uncertain, cognitive diversity conveys opportunity and limits failure. But in the absence of diversity, the use of the same techniques leads to disaster. Our analysis thus calls for a sociologically richer conception of systemic risk. What makes risk systemic rather than individual is the presence of interdependence across financial actors. But this interdependence is currently understood only in terms of liquidity constraints. Our study provides an additional mechanism to account for such system-level effects: reflexive modeling resides in leveraging the cognitive independence among dispersed, anonymous actors. But as we saw in the case of arbitrage disasters, it can also give rise to cognitive interdependence. Just as reflexive modeling can be a source of correction, it can also lead to the amplification of error. In the following sections we consider the implications of this insight at two different levels. First, how can traders further incorporate diversity in their trading strategies? Second, what does an appreciation of diversity imply for the task of regulating markets?

Implications for trading strategy The lesson we drew from our analysis of the spread plot is that attending to the social context (“the market”) is only helpful in situations where that market context contains enough diversity. If not enough rivals hold a certain risk to be relevant, a trader that relies on a combination of his or her own model and “the market” will dismiss press reports on it. This weakness in reflexive modeling makes for a trading opportunity. A trader can actively look for situations in which there is a great measure of agreement among market participants, and consider whether the agreement is due to a failure of reflexive modeling. If it is, a trader might hypothesize that most rivals are wrong, and profit from it. For an example of this, return to the case of GE–Honeywell and consider how an entrepreneurial trader found a way to exploit disasters in merger arbitrage. According to press reports, the renowned New York hedge fund Atticus Global developed a strategy to exploit arbitrage disasters such as the GE–Honeywell deal, before they happen. Atticus proceeded by betting on the reverse of the outcome that its rivals were anticipating. As we saw above, merger arbitrageurs bet on merger success and the subsequent convergence in the prices of GE and Honeywell. By contrast, Atticus bet on merger cancelation and a

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subsequent divergence in the prices of the two stocks. As a journalist described, “Most risk arbitrage managers followed their usual strategy of going long the target, Honeywell, and short the buyer, GE. Atticus shorted Honeywell and bought GE, making a 10 percent return on its investment” (Clow 2001: 25). By assembling a trade that was the negative image of what its competitors did, Atticus managed to profit from their losses. Because the original trade is known as a convergence trade, Atticus’s strategy is known as a divergence trade. In general, “divergence trading” is a form of being contrarian. Divergence trades such as those performed by Atticus are unconventional and rare. While betting on convergence allows traders to rely on their rivals for reassurance, betting on divergence does not allow for that possibility. Divergence trades are therefore riskier and rarely put into practice—they are not even considered to be an integral part of merger arbitrage. However, Atticus understood that there is one instance in which divergence trades might be profitable enough to be worth the risk: when the merger is unlikely to happen and everyone else thinks it will. The more traders bet on convergence between two stocks, the narrower the spread, and the greater the returns from betting that this spread would widen. In short, understanding the role that diversity plays in the market provides the basis for a trading strategy. Traders exploit cognitive diversity among their rivals. When this diversity is missing, those same traders will be misleadingly reassured and potentially very wrong. This can be exploited with a divergence trade—that is, by betting that the misled will lose out.

Regulatory implications Following three decades of rapid expansion in a low-regulation environment, quantitative finance now faces the likely prospects of regulatory reform. Our analysis informs this regulatory debate. Since the late 1980s, financial institutions have replaced administrative controls with model-based risk management techniques, leading to a situation of self-regulation by modeling. The persistence of arbitrage disasters points to the limits of this setup. The arbitrageurs at International Securities, for instance, were not able to avoid arbitrage disasters by simply trading off less risk for higher returns. As the GE–Honeywell merger shows, disasters strike precisely when arbitrageurs mistakenly believe they are playing it safe. Beyond self-regulation, our analysis suggests a theoretical framework for thinking about quantitative finance. First and foremost, our findings should not be read as a denunciation of financial models. Certainly, the models used to back out implied probabilities are necessary to produce reflexive disasters. But, by allowing arbitrageurs to be reflexive, these models are averting other difficulties. Recognizing the fallibility of financial models underscores the importance of diversity of perspectives. Reflexive modeling requires a requisite variety of views among the arbitrage community. Policies that favor participation in arbitrage trading add to this diversity, while policies that restrict participation will reduce this diversity.

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Our analysis also provides a way to think about the relative advantages of regulatory disclosure and oversight of arbitrage. As with other innovations, reflexive modeling poses dangers because of its success. In the presence of widespread diffusion, reflexive modeling gives rise to positive feedback, leading to aggregate consequences that are different from its more obvious individual effects. Recognizing this wedge calls for the creation of a government agency that, as the Food and Drug Administration does with new compounds, examines possible unintended consequences of new financial innovations (see Lo 2009 for a related proposal). By obtaining access to the positions of all arbitrageurs, such an agency could conceivably spot disasters as they brew up. At the same time, our framework makes clear that such a move would not be without costs. By entangling banks and their regulators, government intervention can eliminate the possibility of calculative action. It could alter market engagement from scopic back to embedded: a return to lobbying, dinners with government officials, and guessing games about future public policy. Indeed, an embedded regime could mark a return to the 1970s, when the Federal Reserve Bank of New York regularly met with the “money center”—the ten largest New York banks—and exerted monetary policy through informal suasion. Paradoxically, the regulatory solution to the risks posed by models necessarily involves greater use of models. Given the breadth and complexity of the current financial system, it is inconceivable that regulators could reform the system and prevent future systemic failures without the help of modeling techniques such as stress testing and network analysis. As this reform takes place, further research in economic sociology will be required to understand the interplay between models used for the purpose of profit-seeking, risk management, and regulatory objectives.

Conclusion Dissonance disrupts. This chapter has elaborated a positive role for the disruptive effects of dissonance in financial organizations. In so doing, we hope to be a bit disruptive in the field of economic sociology. That disruption was signaled at the beginning of this chapter when we endorsed the organizational ecologists’ emphasis on diversity, but then departed from them by applying the notion of diversity not to a population of organizations but as a property of the organization itself. In closing, we indicate similar points of departures from the institutionalist framework and from the paradigm of embeddedness. One of the great strengths of research within the neo-institutionalist paradigm was its focus on cognition. In their bold statement outlining the program of neo-institutionalism, DiMaggio and Powell (1991: 24) issued a call to “re-establish the centrality of cognition.” Cognition in that article, as in much of the institutionalist work that followed, was conceived as “taken-for-granted scripts, rules, and classifications” (DiMaggio and Powell 1991: 15), succinctly expressed by DiMaggio and Powell as “unreflective activity.” Scripts, routines, and classifications of cultural taken-for-granteds worked as analytic tools because they worked as the operative recipes for behavior in the relatively stabilized

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institutional environments of the mid to latter part of the last century. They might still be operative in many sectors today. But much of the economy has changed in the decades since the period when the new institutionalists developed concepts acutely attuned to their times. Whereas the new institutionalists emphasize unreflective activity and the taken-for-granted,5 our research documents actors who are acutely aware that if they take their knowledge for granted they can lose their shirts. These actors, in a sense, take seriously the sociologists’ insight that institutional scripts and organizational routines tend to lock in to unreflective activity. “You’re right,” they seem to be saying, “my organization is filled with routinized scripts.” But, rather than accepting this as their sociological fate, they go on to look for practices to help unlock the grip of habit. Within and across trading rooms, the organization of dissonance is a means to move from unreflective activity to reflective cognition. These material practices, moreover, are not by recourse to networks of embedded personal ties (Granovetter 1985). As we saw, reflexive modeling does not involve interactions with known and trusted others; instead, it involves a form of interaction that is impersonal and anonymous. Yet it is emphatically social. The calculative practices of arbitrage are not embedded in social relations. Instead, calculation itself is social. Its social character occurs in two aspects: the (material) relation between traders and their artifacts (instrumentation, databases, and formulae), and the (model-based) relation between traders and their rivals. The arbitrageurs we studied used the second for critical input to realize the first. When we say that calculation is “socially distributed” we do not refer only to knowledge that is distributed among human agents. Our notion of “the social” includes not only such human agents but also the relationships between these human agents and their instrumentation, formulae, algorithms, and other artifacts that populate sociotechnical networks as well the anonymous and impersonal interactions via the mechanisms of reflexive modeling. In sum, grappling with modern crises calls for an understanding of the novel forms of engagement introduced by financial models. Models have given rise to a new mode of sociability, disembedded yet entangled, impersonal but nevertheless social.

Notes 1. Using quantitative methods, Uzzi and Spiro (2005) demonstrate that the success of Broadway musicals (in which innovation is the ability to produce a “hit”) is a function of enough cohesion (the continuity in the composition of the musical “team” from one musical to the next) and connectivity (diversity in composition from one musical to the next). Similarly, in their longitudinal study of Hungarian business groups Vedres and Stark (2010) found that a distinctive network pattern that involves familiarity and diversity is a strong predictor of market performance. 2. Evidence on demographic diversity is mixed. In his study of entrepreneurial groups, Reuf (2010) found adverse effects of demographic diversity, most marked in survival rates. By

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contrast, Harrington (2008) found that demographic diversity was a strong predictor of higher performance among amateur investment clubs. 3. New work in organizational ecology (e.g., Hannan, Polos, and Carroll 2007) does examine problems of cognition. 4. It should be noted that merger arbitrage entails actual risk-taking: the traders face the real possibility of incurring losses. Certainly, merger arbitrage trade entails hedging—not simply buying the target company in the merger, but also shorting the acquiring company to reduce the arbitrageur’s exposure. But the reduction in exposure does not include exposure to a failed merger. It is precisely for this reason that a merger arbitrage trade can be read as a (risky) bet that the merger will take place. 5. The phrase is striking in its ubiquity, occurring no less than nine times in DiMaggio and Powell’s text.

References Abolafia, M. (1996). Making Markets: Opportunism and Restraint on Wall Street. Cambridge, MA: Harvard University Press. Baker, W. (1984). “The Social Structure of a National Securities Market.” American Journal of Sociology, 89: 775–811. Brown, J. S. and Duguid, P. (1998). “Organizing Knowledge.” California Management Review, 40/1: 90–111. Clippinger, J. H. (1999). “Tags: The Power of Labels in Shaping Markets and Organizations,” in J. Clippinger (ed.), The Biology of Business: Decoding the Natural Laws of Enterprise. San Francisco: Jossey-Bass, 67–88. Clow, R. (2001). “Atticus Global finds its Strategy Paying Off.” Financial Times, August, 30: 25. Davis, G. and Greve, H. (1997). “Corporate Elite Networks and Governance Changes in the 1980s.” American Journal of Sociology, 103/1: 1–37. —— — and Mizruchi, M. (1999). “The Money Center Cannot Hold: Commercial Banks in the US System of Corporate Governance.” Administrative Science Quarterly, 44/2: 215–39. Fama, E. (1965). “The Behavior of Stock Market Prices.” Journal of Business, 38: 34–105. Fligstein, N. (1990). The Transformation of Corporate Control. Cambridge, MA: Harvard University Press. Friedman, M. (1953). Essays in Positive Economics. Chicago: University of Chicago Press. Galison, P. L. (1997). Image and Logic: A Material Culture of Microphysics. Chicago: University of Chicago Press. Girard, M. and D. Stark. (2002). “Distributing Intelligence and Organizing Diversity in New Media Projects.” Environment and Planning A, 34(11): 1927–1949. Granovetter, M. S. (1985). “Economic Action and Social Structure: The Problem of Embeddedness.” American Journal of Sociology, 19: 481–510. Hannan, M. T., (1986). “Uncertainty, Diversity, and Organizational Change,” in N. J. Smelser and D. R. Gerstein (eds.), Behavioral and Social Science: Fifty Years of Discovery. Washington DC: National Academy Press, 73–94. —— —, Polos, L., and Carroll, G. R. (2007). Logics of Organization Theory: Audiences, Code, and Ecologies. Princeton, NJ: Princeton University Press.

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Harrington, B. (2008). Pop Finance: Investment Clubs and the New Investor Populism. Princeton, NJ: Princeton University Press. Hutchins, E. (1995). Cognition in the Wild. Cambridge, MA: MIT Press. Knorr Cetina, K. and Bruegger, U. (2002). “Global Microstructures: The Virtual Societies of Financial Markets.” American Journal of Sociology, 107/4: 905–50. Krippner, G. (2005). “The Financialization of the American Economy.” Socio-Economic Review, 3: 173–208. Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers through Society. Cambridge, MA: Harvard University Press. Lester, R. K. and Piore, M. J. (2004). Innovation: The Missing Dimension. Cambridge, MA: Harvard University Press. Lo, A. (2009). “Regulatory Reform in the Wake of the Financial Crisis of 2007–2008,” Journal of Financial Economic Policy 1: 4–43. MacKenzie, D. (2006). An Engine, Not a Camera: How Financial Models Shape Markets. Cambridge, MA: MIT Press. March, J. G. (1991). “Exploration and Exploitation in Organizational Learning.” Organization Science, 2/1: 71–87. Mizruchi, M. S. and Stearns, L. B. (1994). “A Longitudinal Study of Borrowing by Large American Corporations.” Administrative Science Quarterly, 39/March: 118–40. Muniesa, F. (2007). “Market Technologies and the Pragmatics of Prices.” Economy and Society, 36/3: 377–95. Page, S. (2007). The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. Princeton, NJ: Princeton University Press. Peirce, C. S. (1998). The Essential Peirce: Selected Philosophical Writings, Volume 2 (1893–1913). Bloomington, IN: Indiana University Press. Preda, A. (2006). “Socio-Technical Agency in Coming Financial Markets: The Case of the Stock Ticker.” Social Studies of Science, 36: 753–82. Reuf, M. (2010). The Entrepreneurial Group: Social Identities, Relations, and Collective Action. Princeton, NJ: Princeton University Press. Scharfstein, D. S. and Stein, J. C. (1990). “Herd Behavior and Investment.” American Economic Review, 80: 465–79. Shiller, R. J. (1984). “Stock Prices and Social Dynamics.” Brookings Papers on Economic Activity, 2: 457–98. Shleifer, A. (2000). Inefficient Markets: An Introduction to Behavioral Finance. New York: Oxford University Press. Stark, D. (2009). The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton, NJ: Princeton University Press. Useem, M. (1996). Investor Capitalism: How Money Managers Are Changing the Face of Corporate America. New York: Basic Books. Uzzi, B. and Spiro, J. (2005). “Collaboration and Creativity: The Small World Problem.” American Journal of Sociology, 111/2: 447–504. Vedres, B. and Stark, D. (2010). “Structural Folds: Generative Disruption in Overlapping Groups.” American Journal of Sociology, 115/4: 1150–90. Zorn, D. (2004). “Here a Chief, There a Chief: The Rise of the CFO in the American Firm.” American Sociological Review 69: 345–64.

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chapter 12

m a r k et efficiency: a sociol ogica l perspecti v e 1 e zra w. z uckerman

Introduction The primary purpose of this chapter is to sketch a sociological approach to the question of market efficiency—that is, whether financial market prices accurately reflect the “intrinsic” or “fundamental” value of financial assets. The approach advanced here, which is based on my prior work (principally, Zuckerman 1997: ch. 4, 2004, 2008a, 2008b, 2010; Zuckerman and Rao 2004), and builds on certain heterodox strains in finance research (see especially, Dreman 1977; Graham and Dodd [1934] 1940; Keynes [1936] 1960; Miller 1977; Shiller [1990] 1993, 2005; Thaler 1993), integrates three perspectives on social valuation generally and financial market pricing in particular: (a) the “pure realist” perspective, represented by the efficient market hypothesis (EMH), which holds that financial markets are both allocatively and informationally efficient due to the processes of arbitrage and learning that swiftly eliminate any mispricings; 2 (b) the “pure constructionist” perspective, captured most famously by Keynes’ ([1936] 1960) image of a speculation-driven market as a beauty contest, whereby prices bear no relation to intrinsic value; and (c) the “contrarian” perspective, which is best represented by value investors (Buffett 1984; Graham [1949] 1973; Graham and Dodd [1934] 1940; Williams [1938] 1956) who direct investors to opportunities that can be exploited by discerning short-term gaps between price and value. I argue that each of these perspectives is based on sound principles, but that each has important weaknesses. I sketch an integrative approach that carries three main lessons: (a) asset prices are governed by theories of value that translate economic indicators into price; (b) specific institutional conditions are required for weak theories to be replaced by stronger theories, thereby leading to a more (but never fully) efficient market; and (c) an understanding of these institutional conditions—in particular, the need for a vehicle for effectively communicating the full

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range of opinion and reaction to material information—is critical to guide policy on how financial markets should be constituted and regulated. But before sketching this approach, it is important first to clarify why sociologists should even care about the question of financial market efficiency. Indeed, while recent years, and especially the last decade, have seen sociologists and sociologically inclined scholars direct significant attention to financial markets, few have directly engaged with the question of market efficiency.3 This avoidance reflects one of two implicit stances toward the EMH. The first stance seems prevalent among those economic sociologists who came to economic sociology from the sociology of organizations, and who have generally adopted an oppositional attitude toward the discipline of economics.4 This set of scholars regards the EMH as rooted in a broader ideology of free markets and a commitment to rational action, one that does clear violence to reality. The second stance seems common among those who arrived at the sociology of finance from science and technology studies (STS) and political economy (see, e.g., MacKenzie, Muniesa, and Siu 2007). For such scholars, the very question of market efficiency is problematic because they tend to favor a pure or strong version of social constructionism, one that is at best uncomfortable with the notion that there are objective constraints on the reality that human beings construct for themselves.5 Thus, whereas the first set of scholars dismisses the question of market efficiency because the answer seems obviously “no,” the second orientation is loath to admit it as an appropriate question for sociological inquiry. Instead, such scholars prefer to focus on the question of whether economic theories such as the EMH have self-fulfilling or “performative” properties, such that its widespread adoption makes it more accurate (see Mackenzie 2006: ch. 9). The net result is the same: with the exception of myself, sociologists have had little to say about the extent to which financial markets are efficient and the conditions that make them more or less efficient. And yet, there are five interlocking reasons why sociologists should care about the question of market efficiency. The first is straightforward. Just as political sociologists should be informed by, and engaged with, work by political scientists, and historical sociologists should be informed by, and engaged with, research by historians, sociologists of finance should be fully informed by, and engaged with, financial economics— that is, the primary field of inquiry that attempts to understand financial markets. And the question of market efficiency is the axis around which research in financial economics revolves (see Fox 2009; Jovanovic, this volume). Indeed, while financial economics had long been stultified by near-universal fealty to the EMH, the field has recently become much more interesting, as debates between orthodox and heterodox opponents rage. Research in the sociology of finance is necessarily impoverished if it is not informed by such debates, and especially if it caricatures the literature out of ignorance of current work. The second reason for sociologists to care about the question of market efficiency is that an inquiry into this question affords a more productive way to understand the conditions under which economic theories may be “self-fulfilling” or “performative” (terms I will henceforth use interchangeably), and when they are not. A social theory may be

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said to performative when: (a) its predictions do not depend on actors’ awareness and endorsement of the theory; (b) its predictions turn out to be accurate—that is, the theory is predictive; and (c) the theory is predictive not due to the assumptions and logic that constitute the theory, but because the actors in fact became aware of the theory and endorsed it in action. It has long been known that both lay and professional social theories can have self-fulfilling qualities (for classic statements, see Merton [1948] 1968; Merton 1995). However, two challenges have hampered progress in understanding the conditions under which theories are performative: (i) to distinguish those predictive theories that are in fact performative from those predictive theories that are not performative because they fail either criterion (a) or (c) above; and (ii) to understand why many theories that are widely adopted fail to be performative. In light of these challenges, an investigation into the fate of the EMH appears quite promising. It is useful to compare the EMH with the most widely cited example of a performative theory—that is, the Black-Scholes-Merton (BSM) theorem for pricing options (see Mackenzie 2006; Mackenzie and Millo 2003). The BSM is in fact not a good test case for performativity due its failure to satisfy both criteria (a) and (c). The BSM fails criterion (a) because it was in fact not written as a prediction of how markets would look absent the adoption of the theory.6 And the BSM fails criterion (c) because it is impossible to rule out the possibility that it eventually came to predict option prices due principally to the soundness of the assumptions and logic upon which it was originally based (see Mackenzie 2006: 20). By contrast, the EMH satisfies criterion (a) since it was stated as a prediction of reality when it was first articulated (see especially Fama 1965a). Moreover, the EMH went on to have significant influence on finance practice—most notably, in the widespread adoption of indexing and in the training of hundreds of thousands of MBAs. And yet there is significant doubt as to whether it was predictive, and no evidence whatsoever that the widespread endorsement of its tenets and tools had any effect on its accuracy. As such, it is an excellent negative case for helping us to understand why even prominent economic theories often fail to fulfill themselves. The third reason why we should care whether, and under what conditions, markets are efficient is that this is the key question that necessarily animates policy debates on the governance of financial markets. Especially given the havoc they often wreak, we as a society could choose not to have financial markets. The primary reason for continuing to support such markets is the belief that capital-allocation decisions are more efficiently made via the price mechanism than by a more managed process. The basis for such a belief is surely some version of the EMH—that is, the expectation that capital will seek out the projects that promise the highest returns, and will run from the projects that promise the lowest returns. And it seems plain that anyone who invests her personal portfolio in financial assets and securities is driven by similar expectations. Who among us would put their money in securities (or vehicles such as mutual and pension funds that invest in such securities) if we thought that securities prices were just as likely to be high (low) on projects that promised low (high) returns as vice versa? Of course, financial market prices sometimes do seem to be unjustifiable, and this may lead investors to take their money out of the market. But even if we might sometimes endorse such a

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withdrawal by individual investors, it is highly problematic to advocate for mattresses as the place where society as a whole should put its cash. Capital that is taken out of circulation means lower economic growth, and fewer jobs. And insofar as society as a whole has a need for capital markets, such markets should surely be the most efficient possible, such that capital flows to the most productive activities.7 And this then makes salient the question of which conditions promote and limit market efficiency. The recognition that public support for securities markets depends on at least a measured belief in market efficiency leads to the fourth reason why sociologists should engage with the question of market efficiency: the core logic underlying the EMH is so clear and compelling that it needs to be incorporated into any account of how financial markets work. Accordingly, I next turn to laying out the logic of the efficient market hypothesis. And yet while this logic is compelling, it is limited. I thus turn next to laying out the opposing logic, which holds that financial markets are constructed in “selfrecursive” fashion, such that prices can become quite distant from intrinsic values. But we will see that this logic is limited as well and that, ironically, such constructionism shares key weaknesses with the realism of the EMH. To advance a more robust account, I then draw on principles of value investing, which are quite useful for clarifying where value and price meet but need to be augmented with elements of the first two perspectives to explain why they often do not meet. We will then arrive at an account of financial markets, the efficiency of which depends on particular institutional and social conditions. And this account will be useful in fulfilling the fifth and primary reason that sociologists should care about market efficiency. In particular, while framed in terms of a setting that has not been the subject of sustained sociological inquiry, the question of market efficiency cuts to the core of a general sociological problem: What are the limits and possibilities for the social constructive projects to which human beings devote themselves? To what extent are our myths and institutions “castles in the air” or are they firmly anchored in “objective reality”? Financial markets are an excellent setting for addressing these questions because, at least after the fact, it is possible to compare projects with the reality they purport to represent (see Zuckerman 2012; Zuckerman and Rao 2004: 208–9).

The efficient market hypothesis: logic and difficulties Logic of the EHM To summarize the logic of the EMH (see especially Brav and Heaton 2002; cf., Fama 1965a, 1970, 1976, 1990; Malkiel 1985, 2003; Sheffrin 1996), it is useful to focus on the case of the stock market, and specifically the case of common (as opposed to

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preferred) stock. But the same logic will apply, mutatis mutandis, to other securities markets. To begin, let us first recall that, as in any market, price reflects a balance of supply and demand; in particular, the price for an undifferentiated commodity or asset is determined by the marginal demander (the least interested among current buyers who thus requires a low price to buy the good) coming to terms with the marginal supplier (the least efficient among current suppliers who thus requires a relatively high price to serve the market). However, securities markets are distinct in that (at least theoretically) investors can switch roles between buying and selling at any time. Indeed, the institution of “short selling” or “shorting” allows any investor to sell stock even when he does not own it (by borrowing from current owners at the current price, and returning it later, hopefully after having bought it back at a lower price). As such, we may say that prices are determined by the actions of “marginal investors”—that is, that class of investor for whom a price higher than the current (ask) price is too high for him to invest, and a price lower than the current (bid) price is too low for him to sell. There may, of course, be investors who think that the price is already too high at the current price, and those who think the price is too low, but the selling of the first group and the buying activity of the second group will balance each other out, such that the marginal investors tip the balance. In fact, one of the implications of the EMH is that there is no meaningful disagreement among investors as to the value of securities, and, as a result, all investors are marginal investors. This is a troubling implication (see Miller 1977; Shleifer 1986), since it is quite evident that there is substantial disagreement among investors (see Kandel and Pearson 1995; Kandel and Zilberfarb 1999; Zuckerman 2004). But let us continue by laying out the logic of the EMH and why it generates this and related implications. First, consider how (marginal) investors decide whether they want to buy or sell stock. Since there is little or no use or consumption value from owning them, rational investors will buy and sell shares based on expected returns. And the EMH assumes that, in the first instance, such returns are determined by the earnings that accrue to the owners of the stock, where such earnings are discounted by time (earnings received in the near term are worth more than those received in the distant future) and risk (more certain earnings are worth more than those that are subject to some doubt). This focus on the income stream is logical because shares in a corporation legally entitle the owner to a proportionate share in the income that it generates, as well as a proportionate vote on such corporate decisions as how much of the income should be reinvested in the firm’s operations and how much should be disbursed to shareholders as income. All things being equal, investors should be willing to pay more for shares that can be expected to earn their owners more income. Note, however, that the fact that investors are willing to pay more for more expected income does not mean that investors should invest in high-income rather than lowincome stocks. This will depend on their relative prices. It is in fact possible for investors in high-income stock to earn lower returns than do investors in low-income stock if the relative prices of the stock are such that the former investors are effectively paying more, per dollar of expected income, than the latter. At any point in time, there is an effective going rate in the market for a dollar of expected income, and a rational investor should

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be unwilling to pay above this rate to acquire an asset (and he should be unwilling to sell an asset for below this rate). Of course, such an investor should be thrilled to pay below this (sell above this) rate. That is, if an investor believes that the price per dollar of expected income is low for a given stock, he should go ahead and invest in the stock. Conversely, if she believes that the price is high relative to expected income, she should (short) sell it. In either of these cases, the investor should be able to profit from the difference between price and “intrinsic” or “fundamental” value. But the EMH argues that such profit opportunities effectively do not exist—or if they do, they are extremely fleeting, such that prices at any given moment can be assumed to be the best estimates of intrinsic value. The key reason is that insofar as these profit opportunities are substantial, they produce a powerful incentive to find and take advantage of these opportunities, by buying or selling the asset to the point that the gap between price and value, and the corresponding profit opportunity, is eliminated or “arbitraged away.” Indeed, since the EMH assumes no capital constraints, the actions of just a small minority of “smart-money” arbitrageurs are sufficient to make markets efficient.8 Moreover, this arbitrage process also stimulates a learning effect, in that the type of underpricing that the arbitrageur recognized becomes less common (see especially Brav and Heaton 2002). The main reason for this is that we can expect other investors to observe the arbitrageur’s success, and to infer that they should adopt his approach to interpreting information about the security. Moreover, if some investors stubbornly cling to inferior methods of valuing the security, we can expect these dullards to suffer from capital erosion, such that they are effectively weeded out of the market, and only the smart money remains. Finally, the EMH takes this logic to its ultimate conclusion and predicts that the great returns available to potential arbitrageurs have the effect of eliminating them from the get-go. That is, given the incentives for correctly valuing securities, we can expect the arbitrage and learning effects to operate in rapid fashion, such that all investors are marginal investors and all marginal investors are smart-money investors who drive the current price to be the best estimate of the stock’s value, given available information. Accordingly, while an investor may be able to profitably invest on the basis of private information, it is folly to invest on the basis of public information. This would imply that the investor denies the arbitrage and learning effects, and, by inference, that he thinks that investors are not interested in the profit opportunities that come from exercising arbitrage. In colloquial terms, such an investor is assuming that there is free money lying around and that despite the fact that millions of other investors are in exactly the same position to see and profit from picking up this money, they refrain from doing so. The EMH thus counsels investors to assume that they are wrong and the market is right, and to resign themselves to passive investment strategies, such as buying market indexes.

Difficulties with the EMH In 1978, Michael Jensen famously asserted that financial market efficiency was the best established empirical fact of economics (Jensen 1978: 1). The development of modern

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portfolio theory (Markowitz 1952; cf., Roy 1952), and the capital asset pricing model (CAPM; Black 1972; Lintner 1965; Sharpe 1964; Treynor 1965), each of which relied on market efficiency to guide investment decisions, had a powerful impact on the practice of investing as well. Hundreds of thousands of MBAs have been trained in the methods and wider doctrine of the EMH, and the wider public absorption of the EMH’s lessons may be seen in the proliferation of passively managed index funds, which concede the futility of stock picking, and merely try to mimic broad indexes such as the S&P 500 (Bernstein 1992). And yet, by 1990, Eugene Fama conceded that “capital markets are almost surely inefficient” (Fama 1990: 1). Telling blows to the EMH have come from many quarters, and have included a series of demonstrations claiming that the CAPM is an ineffective valuation tool (see Fama and French 2004); various empirical “anomalies” whereby stock returns are predictable for particular periods of time (see Keim 1988; Jovanovic, this volume, for review); substantial evidence that the stock market is excessively volatile (see Shiller 1990); and evidence that there is substantial difference of opinion among investors (Kandel and Pearson 1995; Kandel and Zilberfarb 1999), thus increasing trade and volatility (Zuckerman 2004). And perhaps the most awkward issue for the EMH has been the recurrence of asset bubbles (and subsequent crashes), during which it is demonstrable that prices substantially exceed intrinsic value (see e.g., Ofek and Richardson 2002; Shiller 2005). Note as well that two prominent defenses of the EMH by long-term adherents can be quickly dismissed. One such defense is Fama and French’s (2004) attempt to save the EMH from embarrassing empirical results, whereby the CAPM’s measure of “beta” (the covariance of an individual security with the market index) failed to predict returns (see also Jovanovic, this volume) while simple measures of size and underpricing (marketto-book; see below) succeeded. Fama and French interpret these results as indicating that the latter measures are better measures of risk than the CAPM’s.9 The problem is that this is bald assertion: there is no evidence that investors who buy smaller stocks or undervalued stocks face greater risks. Rather, these results are reasonably interpreted as consistent with the value-investing perspective to be discussed below. The second prominent defense in some sense contradicts the first because it asserts that the EMH is validated by the fact that markets exhibit so few arbitrage opportunities, such that even professional investors are hard-pressed to make money from stock picking. This is a serious mistake in logic because accepting the EMH is not required for one to believe that it is difficult to beat the market. Indeed, this will be true even if one believes that prices are completely random. Moreover, for the EMH to be valid, it is crucial that if and when a mispricing does somehow emerge, it will be quickly exploited, and thereby eliminated. But consider Malkiel’s (2003) review of the state of the EMH, which was written in the aftermath of the Internet bubble. Malkiel, who was one of the great popularizers of the EMH (Malkiel 1985), concedes that “the stock market may well have temporarily failed in its role as an efficient allocator of equity capital” and that “an argument can be maintained that the asset prices did remain ‘incorrect’ for a period of time.” Yet he regards it as a point in the EMH’s favor that “there were certainly no arbitrage opportunities available to rational investors

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before the bubble popped” (Malkiel 2003: 75–6). In fact, this cuts to the core of the problem for the EHM: a scenario where investors have taken collective leave of their senses is precisely when the EMH expects arbitrageurs to act. It is the absence of arbitrage in such cases as the Internet stock bubble and the recent housing bubble that represents the most vexing challenge for the EMH. Why indeed do arbitrageurs not emerge to eliminate such gaps between price and value? And if they do not emerge, how can we expect markets to be efficient?

Implications for performativity Before addressing this question and thereby building a more robust account of market efficiency, it is useful to return to the issue raised earlier—that is, the implications of the EMH’s failure for performativity theory. One obvious implication is that even when a theory is expounded by prominent economists and then widely adopted, it may not be performative. Past work on the performativity of economic theories does not venture an explanation for why a widely adopted theory may be performative in one case but not others (see especially Mackenzie 2006: 248–58). In the present case, the issue may be that whereas performativity theorists seem to assume that the widespread adoption of a theory necessarily makes it more predictive, theories such as the EMH actually require limited adoption to be predictive.10 This point is related to Grossman and Stiglitz’s (1976, 1980) famous observation that if prices reflect all available information, there are no incentives to collect information; they argue that as a result, information collection stops short of the point where full information is gathered and, as a result, markets are less than fully efficient. My point here is a slightly different one, and pertains to the counterfactual situation where all investors would come to believe in the EMH. Regardless of whether prices are in fact the best estimates of intrinsic value, they are assumed as such by all investors in this counterfactual world. As a result, it is irrational for them to engage in arbitrage. And if no one is engaging in arbitrage, prices have no anchor in intrinsic values. At that point, there should be great arbitrage profits to be made, but such profits are available only to those investors who do not believe in the EMH.11 So if all investors believe in the EMH, the market cannot be efficient. The general lesson for research on the self-fulfilling properties of social theories is that the wide adoption of a theory will undermine its predictive power insofar as the internal logic of the theory implies that actors who are aware of it and endorse it will act counter to the theory’s assumptions about their behavior. And as far as the EMH is concerned, it is perhaps a small comfort to its proponents that their failure to convert everyone (including themselves)12 helps to make it more valid! But, more importantly, the recognition that the EHM is a self-defeating theory helps to reinforce our question. Insofar as such arbitrage opportunities as those presented by the Internet stock or housing bubbles do present themselves, why do investors not exploit them and thereby make markets more efficient?

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The self-recursive market hypothesis and the limits of value–price arbitrage Logic of the SRMH I now present the most prominent answer to this question and then show that it too suffers from an important weakness. This answer may be summarized by the famous quote attributed to Keynes:13 “The market can stay irrational longer than you can stay solvent.” Put more concretely, Keynes’ point is that “it is not sensible to pay 25 for an investment of which you believe the prospective yield to justify a value of 30 if you also believe that the market will value it at 20 three months hence” ([1936] 1960: 157). Keynes argues that the investor who buys on the basis of income or yield—that is, the smart-money arbitrageur upon whom the EMH depends—is essentially an anachronistic throwback to the period before shares in corporations were securitized. Once equity is securitized and it trades on large, liquid exchanges, the marginal investor necessarily becomes a speculator who must focus first and foremost on changes in the “conventional valuation” (and therefore, price) over his speculative horizon. This logic leads to Keynes’ famous metaphor of the stock market as a “beauty contest.” In particular, he likens speculative markets to: . . . those newspaper competitions in which the competitors have to pick out the six prettiest faces from a hundred photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole; so that each competitor has to pick, not the faces that he himself finds prettiest, but those he thinks likeliest to catch the fancy of the other competitors, each of whom is looking at the problem from the same point of view . . . We have reached the third degree where we devote our intelligence to anticipating what average opinion expects the average opinion to be . . . ([1936] 1960: 156)

Two points are worth stressing. First, this “self-recursive” logic (see Zuckerman 2004) critically undermines the logic of the EMH.14 As discussed above, the logic of the EMH relies on the incentives inherent in the profit opportunities that emerge when prices deviate from intrinsic value. But Keynes (and more recent observers who recognize the limits to arbitrage; see DeLong et al. [1990] 1993; Shleifer and Vishny 1997) points out that this is not the case. If you think the price is wrong but the marginal speculator does not come around to your opinion within your time horizon, you will not in fact earn profits even if in some objective sense you were right. To return to the example of the Internet bubble, short sellers lost a great deal of money at that time because the very nature of short selling, which requires interest payments and the posting of more collateral when prices increase, meant that they could not sustain their position long enough to benefit from the eventual downturn. Indeed, several famous investors were forced

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from the market because they stubbornly clung to the value-based methods that were objectively right, but were wrong for all practical purposes. Second, it is important to recognize that what might be called the “self-recursive market” hypothesis (SRMH) is not based on irrational behavior.15 Rather, “it is an inevitable result of an investment market described along the lines described” (Keynes [1936] 1960: 157). Insofar as the proximate determinant of price movements is changed in the marginal speculator’s valuation, it is at least as sensible to speculate on the basis of trends in speculator opinion as on calculations of expected income. As Keynes notes, “He who attempts . . . investment based on genuine long-term expectation . . . must surely run greater risks than he who tries to guess better than the crowd how the crowd is going to behave; and given equal intelligence, he may make more disastrous mistakes” ([1936] 1960: 157). Moreover, the case for focusing on one’s fellow speculator is often stronger for institutional investors—that is, the smart money assumed by the EMH to act as arbitrageurs. In particular, insofar as institutional investors such as mutual fund or hedge fund managers are agents who compete for investment, it is not enough that they have the fortitude to bet against the market; they must also convince their investors to believe in their contrarian ideas, and to keep the faith when the market turns against them. As Keynes put it, “Worldly wisdom teaches that it is better for reputation to fail conventionally than succeed unconventionally” ([1936] 1960: 158; cf., Scharfstein and Stein 1990). Surely this is too strong: after all, the unconventional success is often celebrated. The problem though is that the unconventionality comes before the success, and one often has to answer for it well before success can be validated.

Difficulties with the SRMH Yet while the logic of the SRMH successfully undercuts that of the EMH, it too suffers from significant limitations such that on its own it is an even weaker guide to the question of efficient markets. Note first that the fact that value–price arbitrage (or more generally, “valuation opportunism”; see Zuckerman 2012) is difficult does not mean that it is easy to engage in the kind of speculative arbitrage described by Keynes. While the EMH may be wrong to think that the mechanism of arbitrage eliminates all gaps between price and value, there is every reason to think that it operates quite well when it comes to gaps between current and future price. Keynes suggests that it is good strategy to speculate on the basis of trends in the conventional valuation. But insofar as there are great returns available to any speculator who correctly anticipates such trends, it is reasonable to expect great efforts to be made in this direction, such that any gaps between current price and anything that is foreseeable in such trends will be arbitraged away! This reinforces the point that one need not endorse the EMH in order to think that arbitrage opportunities are scarce. The problem then is that both the EMH and the SRMH are recipes for inaction on the part of investors/speculators. The EMH insists that opportunities to arbitrage between price and value are mirages because they are eliminated instantaneously. The SRMH undercuts this argument by showing that how risky it is to try to

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speculate on the basis of intrinsic value. But insofar as we assume rational behavior, the SRMH is equally problematic due to the fact that speculating on the basis of conventional opinion cannot work on average.16 This recognition leads to an even deeper and more problematic commonality among these hypotheses, and the larger perspectives on social valuation that they represent. The EHM is an example of a pure realist perspective, in that it contends that social valuations accurately reflect objective values. Like performativity theory, the SRMH is an example of a pure constructionist theory, in that it insists that social valuations have no effective anchor in objective values (see, e.g., Westphal and Zajac 2004, and see also Zuckerman 2004b, 2004c). Realism and constructionism are typically thought to be opposing perspectives (see, e.g., Abbott 2001). But as I have recently argued (Zuckerman 2010), they have exactly the same implications as guides for action generally, and for public policy in particular. Consider recent financial asset bubbles. Federal Reserve Chairman Alan Greenspan was rightly criticized for letting his belief in efficient markets prevent the Fed from acting against asset bubbles. But pure constructionism provides no more basis for intervention in such circumstances than pure realism: The pure realist regards dominant interpretations as the best possible, thereby renouncing responsibility for challenging them or proposing alternative mechanisms for arriving at such interpretations. By contrast, the pure constructionist has no particular affection for dominant interpretations. But neither does she have a basis for challenging them or suggesting alternative arrangements since she believes all interpretations to be equally (in)valid. Were the pure constructionist to prefer an alternative to the dominant interpretation, how might she argue for it? How might a performativity theorist diagnose a bubble? (Zuckerman 2010: 364)

The differences and similarities between pure realism (represented by the EMH) and pure constructionism (SRMH), as well as their point of intersection, are summarized in Figure 12.1. While the former sees prices as governed by intrinsic values, the latter emphasizes collective beliefs. But they share the implication that markets do not exhibit meaningful gaps between price and value. For the EMH, the reason is that such mispricings are arbitraged away. For the SRMH, the reason is that intrinsic value is a fiction or at best a theoretical construct with no bearing on price. Yet it is worth stressing the third reason I gave regarding why sociologists should care about market efficiency. In particular, while our response to the EMH has often been to label its adherents as naïve realists who do not appreciate that the market is socially constructed, this response begs two questions: (a) Does that mean that prices bear no relationship to intrinsic value? (b) And if not, what is the basis for public support for securities markets? This basis would appear to derive from the belief that prices will be reasonably accurate signals to guide capital allocation. But this will not be so insofar as prices are pure constructions with no anchor in intrinsic values. And this in turn makes the first question more urgent. Let us rephrase it as follows: Given that arbitrage between price and value is severely limited by the selfrecursive nature of speculation and the understandable reluctance of institutional investors to buck convention, how and to what extent do prices relate to intrinsic values—and what can we do to tighten that link?

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Contrarian (Value-Investor)

Principle 1: Prevailing valuations can be judged against, and are shaped by, objective conditions

Pure Realist (EMH)

Principle 2: Prevailing valuations are shaped by subjective factors

Principle 3: No actionable difference between prevailing valuations and objective value

Pure Constructionist (Keynes’s Beauty Contest; Pure Performativity)

figure 12.1 Three Perspectives and Three Principles on Social Valuation and Financial Market Pricing Each vertex in this three-dimensional plot (see Coleman 1961; Martin 2009) is a perspective that embraces each of the principles described on the adjacent edges. For instance, a pure realist perspective holds both that objective values ultimately govern prices and that there is no difference between price and value. The edges drawn from one vertex to an opposing side indicate that the perspective on the vertex rejects that particular principle. Thus, the pure realist position rejects the principle that subjective factors shape prices.

The attractions and challenges of contrarianism The logic of value investing We begin to formulate our answer to this question by turning to a contrarian perspective which, as depicted in Figure 12.1, combines the EMH’s emphasis on value–price arbitrage with the SRMH’s recognition that market dynamics are driven by speculative behavior disconnected from intrinsic value. This essence of this “value-investment” approach of Graham and Dodd ([1934] 1940; cf., Graham [1949] 1973; cf., Fisher 1996; Williams [1938] 1956) is captured by the following parable:

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Imagine that in some private business you own a small share that cost you $1,000. One of your partners, named Mr. Market, is very obliging indeed. Every day he tells you what he thinks your interest is worth and furthermore offers either to buy you out or to sell you an additional interest on that basis. Sometimes his idea of value seems plausible and justified by business developments. Often, on the other hand, Mr. Market lets his enthusiasm or his fears run away with him, and the value he proposes seems to you a little short of silly. If you are a prudent investor or a sensible businessman, will you let Mr. Market’s daily communication determine your view of the value of a $1,000 interest in the enterprise? Only in case you agree with him, or in case you want to trade with him. You may be happy to sell out to him when he quotes you a ridiculously high price, and equally happy to buy from him when his price is low. But the rest of the time you will be wiser to form your own ideas of the value of your holdings, based on full reports from the company about its operations and financial position. (Graham [1949] 1973: 108)

Note that Graham and Keynes both make sharp distinctions between speculation and investment, and they agree that prices are driven by the marginal speculator (“Mr. Market”) whose valuations often appear disconnected from intrinsic value. However, Graham draws very different conclusion from this. In particular, whereas Keynes counsels against engaging in value–price arbitrage (but see note 16), this is exactly what Graham advocates. He insists that the “true investor” should make up his own mind about the value of a security and act when he disagrees with the marginal speculator, and that he will do “better if he forgets about the stock market and pays attention to his dividend returns and to the operating results of his companies” ([1949] 1973: 109). And there is good evidence to suggest that when practiced in a disciplined way, value investing can be quite profitable as an investment strategy (e.g., Buffett 1984; cf., Fama and French 2004). Note finally that a compelling reason for sociologists to take this perspective seriously is that, despite the appeal of constructionism to many economic sociologists, they in fact adopt a contrarian posture whenever they argue for the value of sociology relative to economics (of their own work relative to someone else’s). Such a stance suggests that objective values do indeed exist but that social valuations are often wrong, such that we would be wise to keep our own counsel.

Difficulties with value investing Yet while this ad hominem framing of the matter may make us root for contrarianism, it also underscores the difficult questions it faces. Consider first how the doubts SRMH raises regarding value–price arbitrage generally also apply to the value investor: if Mr. Market is so silly, why is the value investor so sure that Mr. Market will ever correct himself, so that the value investor earns a profit (rather than loss)? Graham and his followers do not provide a clear answer to this question. Graham has often been quoted as saying that “In the short run the market is a voting machine. In the long run it’s a weighing machine,”17 but he provides very little guidance as to the mechanisms

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that make Mr. Market reflect foolish popular fads in the near term but wise trends in the long term. Graham ([1949] 1973: 108) provides five reasons for this “adjustment process” but they are all essentially assertions that Mr. Market figures things out eventually rather than explanations for why this is the case. Moreover, if it is unclear why value investing escapes the critique from the SRMH, it is also unclear how it escapes the EMH’s argument that the incentives from the profit opportunities identified by value-investment strategies should lead (via the arbitrage and learning effects) to their swift elimination. The value-investment approach thus faces a double bind, as illustrated in Figure 12.1 by how it shares key principles with each of the other perspectives. On the one hand, it enjoins the investor to engage in arbitrage, the profits of which are realized because the market eventually learns the intrinsic value of the security; but on the other hand, the arbitrage opportunities it identifies can exist only if arbitrage and learning are limited. We are thus back to our question as formulated above.

Toward a sociological answer to the question of market efficiency In the remainder of this chapter, I sketch an answer to this question. I begin by recognizing the wisdom embedded in the practice of value investing and the contrarian orientation in general, if not in the (relatively undeveloped) theory of markets espoused by value investors. An appreciation for this practice helps to: (a) clarify how value–price arbitrage is possible, thus limiting self-recursive processes and providing an objective foundation for prices; (b) indicate the limits to value–price arbitrage, and thus how prices may deviate from intrinsic values; and (c) suggest significant limitations to the market as a learning environment (and thus its capacity for “weighing” correctly in the short term), with such limitations being very severe under certain institutional conditions (when trading is over-the-counter).

Value–price arbitrage sets an objective price floor The main lesson from the practice of value investing is that securities prices are not pure social constructions, but are constructed within specific objective constraints.18 In particular, prices face a hard lower bound or “floor” below which they do not go. To see this, one must only consider the main strategy recommended by value investing, which is search for stocks that are so low priced that they are trading at a market value that is considerably less (with a “margin of safety”; Graham and Dodd [1934] 1940) than the expected income or, what is even better, a market value that is less than the value of the firm’s assets. In particular, let us consider a counterfactual scenario, whereby the shares of General Electric (GE) common stock at the opening of trading on September 13, 2010,

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were being offered for $1 per share. Since there were 16.9 billion shares of GE common stock outstanding, this would entail a market value of $16.9 billion. This may sound like a large number, but it in fact would represent a 90.1 percent decline from the closing price of $15.98/share (implied market value of $171 billion) on the prior day of trading, which was September 10, 2010. And yet, according to the pure constructionist logic of the SRMH, there is no reason to think that the $1 price is wrong and no reason to think that speculators are more apt to keep prices near $16 rather than push them down to $1. But in fact, there is very good reason to think that the $16 price is a more accurate estimate of GE’s intrinsic value, and that speculators will realize this and incorporate it into their trading activity, thus keeping price much closer to $16 than to $1. To support this assertion, I first use two classic value-investing methods to establish that the $1/share is too low: (a) dividend yield (see especially Burr Williams [1938] 1956)—that is, the income that an investor can expect to receive from owning GE stock; and (b) liquidation value—that is, the income that an investor would obtain via a “fire sale” (i.e., as immediate as possible) of its assets. To be sure, many public corporations do not disburse dividends and none are required to do so. However, these concerns are largely irrelevant for the exercise of determining the intrinsic value of GE. In particular, while the size of the GE dividend has varied over the years, it had (as of September 10, 2010) a decades-long unbroken streak of disbursing quarterly dividends. And despite a recent cut in the dividend, GE had kept its dividend payout ratio constant at about 45 percent of earnings, which suggests that it had the capacity to fulfill its commitment.19 The value of this commitment may be calculated by noting that the quarterly dividend to be disbursed on October 25 to all those who own their shares on September 16, 2010 (the “ex-dividend date”), was $0.12. This means that for a counterfactual investor who purchased a share for $1, GE stock would yield a quarterly return of 12 percent and a yearly return (assuming no compounding) of 48 percent.20 This is, of course, an extremely attractive rate of return. Even at $10/share, the quarterly dividend of $0.12 represents an annual yield of 4.8 percent that compared very favorably with the 2.8 percent yield on ten-year US Treasury bills. By contrast, at the going price of $16/share, the yield to the GE investor was just a bit higher than the investor of the ten-year Treasurybill—3 percent. These calculations strongly suggest that GE’s intrinsic value was much closer to $16/share than to $1/share.21 This conclusion is greatly reinforced when we consider GE’s liquidation value (see especially Graham and Dodd [1934] 1940). The liquidation value of a stock is relevant due to the following logic: should an investor acquire a controlling interest in the company, this is the minimum return that she can expect to obtain from her investment. In reality, such an investor is likely to expect a much higher return insofar as the assets are worth more as part of the business than they would be in a “fire sale.” Thus, an investor valuing GE for its takeover value is also likely to arrive at a price considerably higher than $1.22 One basic and very conservative approach to calculating liquidation value, based on GE’s June 2010 balance sheet, subtracts its total liabilities from its total assets minus intangible assets, and also takes a 25 percent discount to receivables (i.e., assumes that 25 percent of what is owed to GE will not be collected) and a 50 percent discount to

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inventories (i.e., assumes that in a fire sale, its products would be marked off by an average of 50 percent). This calculation results in an estimate for GE’s intrinsic value of $5.33/ share. A still more conservative method would remove the estimated value of GE’s goodwill. Even this method, which effectively assumes that GE’s brand name has no value, generates a liquidation value of $1.60/share or $27 billion, which is 60 percent higher than GE’s price under our counterfactual scenario.23 The foregoing calculations strongly suggest that while GE’s intrinsic value may not be as high as $16/share, it is much higher than $1/share. And there is also good reason to think that these calculations of intrinsic value shape the price of GE’s shares. Let us be very precise about what we mean when we say that intrinsic value “shapes price,” especially since the two perspectives that share this principle (see Figure 12.1)—the “pure realism” represented by the EMH and the “contrarianism” represented by value investing—differ quite radically on whether mispricings occur in the short term. What unites these perspectives is the idea that there is a very conservative calculation of intrinsic value that establishes a floor below which prices are extremely unlikely to fall. Concretely, and if we assume that there is no material information about GE or the political and economic condition that affects its income-generating capacity over the weekend of September 11–12, 2010, this implies that the chance of GE’s shares being offered for a price as low as $1/share is equivalent to the chance that someone will dump a billion dollars onto Times Square that same morning, and that this cash will still be there a few hours later. Such a scenario is physically possible, but socially impossible. Indeed, we routinely organize our lives by assuming away scenarios that are much more socially possible (e.g., that we will be attacked by a mugger as we walk down the street) than this one. You, dear reader, would not wager anything that has value to you on the chance that it might occur. It may be difficult for some sociologists (especially those who tend toward pure constructionism) to accept that there is an infinitesimal chance of GE shares trading as low as $1/share, such that the price of $16/share is a more correct price. But two considerations should defuse such skepticism, and also provide a foundation for grasping how such calculations shape price. First, my rendering of the principle that intrinsic value shapes prices pertains only to the prediction that prices will not decline below the most conservative calculations of intrinsic value. That is, my claim is not that prices equal value, but that as prices decline further and further, there is some very low calculation of intrinsic value below which they will not fall. Second, this value-based price floor operates even if many—even the vast majority of—investors do not endorse my calculations. All that is required for a calculation of intrinsic value to establish a price floor is that those who endorse this calculation have sufficient capital to purchase the shares from those who are willing to sell at this price. If even one investor has sufficient capital, it is rational for him to buy the asset because, by his own estimation, he will earn an attractive return from ownership of the asset regardless of whether he is the only person in the world who thinks this24—and it is rational for him to continue to invest until the point that either the price of the asset rises to equal his calculation of intrinsic value or he runs out of capital to invest. Thus the prediction that there is essentially no chance that GE shares will trade as low as $1/share on September 13, 2010, is essentially a prediction that

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there exists at least a minority of investors who have, or can raise, sufficient capital to buy all shares that are offered at such a price.25

Theories of value shape construction The foregoing discussion suggests how we can recast Keynes’ insights in such a way that the self-recursive nature of speculation is still anchored—if often loosely—in intrinsic value. To see this, consider a speculator who is trying to anticipate trends in the “conventional valuation” and thus anticipate GE prices. At $16/share, this is a very difficult challenge. But it is not very difficult in our counterfactual scenario. Indeed, the foregoing discussion placed us in this very scenario, which is essentially the second “degree” cited by Keynes. That is, at $1/share, it seems very easy to anticipate that someone will step in and buy GE shares due to their recognition that they can make a very good income by owning them. As such, if I can buy some shares at $1 before those investors can snap them up, I stand to enjoy great returns as demand from such investors pushes up the price. Thus, the closer prices are to conservative estimates of intrinsic value, the more speculators’ judgments of conventional valuation are shaped by calculations of expected income. It is at this low point that the two rational imperatives—(a) to invest by comparing price to expected income; and (b) to speculate based on trends in conventional valuation—come together because it is clear how calculations of income enter the conventional valuation. And if a speculator persists in foolishly ignoring the fact that prices are too low, the mechanisms of arbitrage and learning ensure that he will either be eliminated from the market as he loses his money to value investors, or that he will learn from value investors that he must do calculations of expected income if he wants to anticipate price trends—at least when prices are very low. And this same logic, by which estimates of income shape judgments of conventional valuation, also applies when prices are higher than conservative estimates of intrinsic value. Let us recall why a long-term investor who cares only about income—that is, as opposed to a speculator—might ever be willing to pay a price for shares in a venture that is much greater than conservative estimates of its intrinsic value (e.g., based on its current income or the value of its assets). Clearly, such investors often lose their money from making such bets. However, they are sometimes rewarded quite handsomely insofar as the venture has a strategy for creating value and capturing it, thereby accumulating substantial profits. That is, such an investor acts on the basis of a “theory” that relates indicators about the firm and its environment to produce a judgment about the value of a share in such a venture (see Shiller [1990] 1993; Zuckerman 1997, 1999). And the recognition that such theories inform investment should again shape our thinking—as well as that of the speculator who is trying to anticipate conventional valuations. That is, insofar as we think that a great deal of capital believes in a theory that values a venture at price p, it will make sense for us to consider buying shares if for some reason the price declines below p. And to return to our GE example, we may very well decide to buy GE shares at $13/share if we feel strongly enough that the dominant theory in the market implies that

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GE should be worth $20/share. Such speculative strategies were frowned upon by Graham because they rely on successfully anticipating short-term trends in prices (by contrast, Buffett has often invested on this basis; see Lowenstein 1996). But the key point for our perspective is that this logic sheds light on how estimates of intrinsic value enter even into speculative behavior. Again, the speculator who tries to ignore fundamental value is in for a rude awakening when he discovers that the trend that he anticipated runs counter to what most speculators believe that most believe . . . about the theory of value that governs the asset in question.

Theories and prices are relatively unconstrained at the top To this point, there is much about the EMH that I have endorsed. In particular, I have argued that the mechanisms of arbitrage and learning discipline speculators, such that they cannot push prices too far from prevailing theories of value as applied to available information, and these theories are in turn attempts to estimate future income streams. This suggests that prices should be good estimates of these income streams, and thus efficient guides for the allocation of capital. But the rub is that while the mechanisms of arbitrage and learning operate to ensure that the theories of value that govern pricing are reasonable (i.e., based on estimates of future income) and that they improve with time, such theories are often quite wrong in the short term. For instance, the Internet bubble should not be seen as a spate of irrationality or speculation on the basis of sheer momentum. Rather, Internet-stock price movements suggest that they were governed by a theory of value that was reasonable, but turned out to be wildly optimistic (see Zuckerman and Rao 2004; cf., Demers and Lev 2001). There are two interlocking reasons why incorrect theories can govern prices for a time, and these reasons derive from fundamental limitations to arbitrage and learning. With respect to arbitrage, the problem is that while value–price arbitrage becomes easier and easier as prices drop in value, it becomes effectively impossible as prices rise. When prices are very low, the value investor can exercise arbitrage by buying the corporation outright. Others may have a theory that values the shares at this very low price, but their opinion no longer matters: the value investor makes his return directly from the firm’s income stream, not from anticipating the conventional valuation. By contrast, there is no comparable way to execute a contrarian strategy when prices are very high. To return to the example of the Internet bubble, the only option available to them was to short sell Internet stocks. But even when short selling is possible (and it generally was not possible because so few Internet shares were available to borrow; see Ofek and Richardson 2002), the short seller is at the mercy of conventional valuations—that is, of the prevailing theory of value—and to paraphrase the paraphrase of Keynes, “the market can cling to an incorrect theory longer than you can stay solvent.” Accordingly, Graham and Dodd ([1934] 1940) urge value investors to avoid short selling except in the rare circumstance where they can hold their position indefinitely. And the relative absence of value–price arbitrage at high prices has the indirect effect of loosening the upper bounds on price.

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Once speculators believe (that speculators believe…) in a particular theory of value, and this theory implies a much higher price, there is relatively little that a value investor can do to profit from their folly, and thereby bring prices down to a reasonable level.26 I now turn to my final point, which concerns the weakness of the market as a learning environment. To motivate this issue, it is first worth noting that the weakness of value–price arbitrage at high prices does not necessarily mean that prevailing theories will always be wrong. In particular, insofar as wrong theories are eventually debunked (once sufficient time passes, and estimates of income turn out to have been too high), bad theories are replaced with good theories. And given enough observations, only good theories remain. The problem with this, of course, is that there are never enough observations. History never repeats itself in exactly the same way, and this provides the impetus for new theories to emerge for interpreting these new developments. Further, there is always someone (something of a “valuation entrepreneur”; see Zuckerman 2012; cf. Becker 1963) who has an interest in promoting the theory that the new developments will be extraordinarily lucrative. Usually such theories are not taken up by others, but sometimes they are, and the rising number of adherents can generate great momentum. At that point, skeptics may try to counteract the speculative fever by suggesting that the theory is silly and/or that the historical record provides reason to doubt it. But the theory will often seem reasonable enough to enough speculators (who reinforce one another’s sense that it is reasonable) and the historical record will be sufficiently ambiguous (see Reinhart and Rogoff 2009), such that massive amounts of capital may be wasted on relatively low-income projects before the new theory is debunked. Note finally how the weakness of value–price arbitrage both enables and exacerbates such speculative excesses. It enables such bullish speculation because those with the correct theory of value can do nothing (apart from short selling in the hope that they will time the crash well) to counteract it. And second, their very absence from the market means that speculators will derive incorrect lessons from short-term market movements (see Gorton 2008). For example, consider a situation where news arrives that has ambiguous implications according to a dominant but incorrect bullish theory of value, but has negative implications according to the correct bearish theory of value. Such news may lead to a short-term spike in trading and volatility as speculators attempt to judge the conventional valuation of such news (cf., Zuckerman 2004). But since the bears have little or nothing to do to act on their views, speculators will reasonably judge that the news was not particularly negative. Moreover, if the bears express their views in the public media but there is no corresponding effect on prices, speculators will reasonably conclude that the market has judged them to be wrong. In sum, the weakness of the market’s capacity for supporting value–price arbitrage has the side effect of distorting the market’s capacity to effectively communicate the distribution of opinion. And the net result is that insofar as such limits on arbitrage apply, securities markets will be limited in their allocative efficiency (i.e., prices will not be the best estimates of future income) and even in their informational efficiency (i.e., they do not incorporate the full range of opinion about available information; cf., Sethi 2010; Zuckerman 2004a).

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Conclusion I have tried in the foregoing to sketch a sociological account of market efficiency that navigates between the extreme realism, as represented by the EMH, and the extreme constructionism that is represented alternatively by performativity theory and the SRMH. In short, the perspective advanced here is an elaboration on Graham’s mantra that the market is a “voting machine” in the short run, but a “weighing machine” in the long run. This elaboration has suggested how and why intrinsic values constrain prices, but also how and why those constraints are weak. I hope that this perspective provides a stronger foundation for the efforts by sociologists and others who seek to understand how it is that markets can often be such marvelous ways for a mass of individuals to make wiser decisions than they would make on their own, but sometimes foster colossal errors of judgment. And future efforts should be motivated by the desire to minimize the latter episodes and maximize the former. This can be accomplished only when we realize that prices are neither pure constructions nor exactly right, but are the outcome of collective processes of profit-seeking (arbitrage) and communication (learning) that depend on well-working institutions to make sure they work reasonably well, if never as well as one might hope. I conclude by noting two implications for the appropriate stance we should take toward market efficiency. First, a recognition of the limits of market efficiency directs us to how they can be “rationalized” to become more efficient (Zuckerman 2010). In particular, regulators must work to ensure that: (a) there are mechanisms for the full range of investor opinion to be expressed; and (b) in the event that a securities market lacks such mechanisms, they should regard the market as structurally inefficient and intervene to address its problems before they produce negative repercussions for the financial system, and even the economy. However, even while we attempt to make markets more efficient, market efficiency will always be limited. The reason is that there is no escaping the fundamental asymmetry, whereby bulls can invest on the basis of the asset’s expected income and without regard to market risk (thus producing a hard price floor), whereas bears are always at the mercy of market risk (thus rendering a ceiling of straw). Indeed, it is arguable that the main error made by adherents of the EMH was that they failed to appreciate (or waved away as a simplifying assumption; see Fama and French 2004: 29–30) the fact that their theory only pertains under institutional conditions where there are no limits to value– price arbitrage. More specifically, for the EMH to hold, it must be the case that short selling (during bull markets) is as easy as investing (during bear markets).27 But it is questionable whether this assumption ever holds. Insofar as short selling is a speculative maneuver, it necessarily involves “market risk”—that is, the risk that prices will not fall. By contrast the returns of an investor who invests for income, especially if she buys the asset outright, involves no market risk. This fundamental asymmetry means that the limits on market efficiency cannot be eliminated. As such, the final implication of this analysis is

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to impart to us all a sense of humility in what we can ask of securities markets, and to regard securities prices with the kind of skepticism that is at the heart of value investing. It is crucial that we always bear in mind that there is a difference between price and value (see Zuckerman 2010).

Notes 1. Thanks to Alex Preda and Karin Knorr-Cetina for inviting me to contribute to this volume. And thanks to Catherine Turco for her invaluable feedback. The usual disclaimers apply. 2. The EMH has been discussed in somewhat different ways, though all such statements claim that the market achieves a high level of informational efficiency, whereby prices quickly incorporate material information (the “semi-strong” version of the hypothesis pertains to all public information, whereas the “strong” version pertains even to private information (see Fama 1976; Jensen 1978)); this informational efficiency is a necessary but insufficient condition for “allocative efficiency” (see Sethi 2010), whereby securities prices are the best estimate of the value of the future income stream from such securities, and therefore securities markets are allocating capital to their most productive uses. 3. One indicator of this trend is the rate of citations of the first article in a flagship sociological journal on financial markets, Baker’s (1984) network analysis of an options market. While the mean citation rate during the 1980s was 3.6/yr, it increased to 5.7/yr during the 1990s, and nearly doubled to 10.9/yr during the 2000s. (Source: Web of Science.) 4. These scholars are well represented in the volumes on the financial crisis edited by Lounsbury and Hirsch (2010). See especially the chapters by Fligstein and Goldstein (2010) and Pozner, Stimmler, and Hirsch (2010). 5. On the distinction between pure vs. “moderate” or “contextual” versions of constructionism, see especially Best (2008); Bromberg and Fine (2002); Goode (1994); and cf., Abbott (2001). 6. There was essentially no options market at the time BSM was conceived. This means that the only way BSM could become accurate would be if investors came to adopt it or some version of it. Put differently, while Mackenzie and Millo argue (2003; MacKenzie 2006) that the BSM was intended to be a “camera” or description of reality but ironically became an “engine” that created the reality it purported to describe, this is inaccurate. BSM was in fact intended to be an “engine” (a tool of financial engineering) from the outset. 7. This does not mean that the profitability of projects should be the sole determinant of capital allocation. For instance, we may want to steer investment away from projects that harm the environment or which trample on workers’ rights. The point is that insofar as at least a subset of capital is to be allocated according to its profitability (perhaps incorporating taxes and incentives that reflect social welfare), capital-market prices should accurately reflect the profitability of one project over another. 8. The definition of arbitrage in this chapter involves exploiting the difference between an asset’s price and its intrinsic value. This is a different definition of arbitrage from that is frequently used by traders, and applied in Hardie and Mackenzie’s contribution to this volume, which involves finding and exploiting the difference between an asset’s price in one market and its price in another market. But even when the price for an asset is the same in all markets, it is unclear whether this price will be a good measure of the asset’s value. It is the former, “value-price” type of arbitrage that is necessary for this to happen. And so,

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ezra w. zuckerman the ultimate question for the claim that a market is allocatively efficient is whether valueprice arbitrage is a highly effective mechanism. As Fox (2009) discusses, there have long been doubts as to whether beta is itself a good measure of systematic risk. Apart from measurement issues, there is a significant conceptual gap between the probability that one’s capital will be wiped out (i.e., the traditional understanding of risk, which underlies the higher yields on the debt of entities of questionable solvency) and the covariance of a stock with a market index. Of course, performativity theorists are notoriously hard to pin down, both on which theories they expect to be performative and on the mechanisms that are responsible for performative effects. Rather, widely adopted predictive theories tend to be labeled performative, while widely adopted, nonpredictive theories tend to be labeled “counterperformative” (see, e.g., MacKenzie 2008: 244–59). My point here is to highlight why the inner logic of the EMH was such that it could never induce the market that it imagines. That this point was not recognized by the proponents of the EMH may be seen in Fama’s famous prediction that securities analysts would disappear because they “establish a market in which fundamental analysis is a fairly useless procedure both for the average analyst and the average investor” (Fama 1965b: 58). The logical flaw in this prediction is that unless someone engages in fundamental analysis, the market cannot be efficient. So while it may be true that the average analyst and investor cannot gain from beating the market, market efficiency requires that such efforts (by EMH skeptics) do take place. One of the most striking aspects of the EMH movement has been the tendency for the most passionate advocates of the EMH to become very rich through engaging in arbitrage strategies that assume market inefficiency (see Fox 2009). I have not been able to find the source of this quote. My guess is that Keynes did not say it, but it was uttered by someone who was (aptly) summarizing Keynes’ perspective. By contrast, a recognition that investors sometimes act irrationally is not a major source of awkwardness for the EMH. The presence of irrational or “noisy” market participants (Black 1986) is indeed awkward for the EMH, but only if they can be shown that their actions cause significant mispricings. Otherwise, irrational investors can be regarded as suckers who stubbornly refuse to learn the lesson that they cannot beat the market and thereby augment the returns of the arbitrageurs who pounce on their mistakes and quickly drive price back to its correct level. Accordingly, and as stressed by Brav and Heaton (2002) and others (e.g., Sheffrin 1996; Shleifer and Vishny 1997), the only effective critiques of the EMH are those that show that there are significant limits on arbitrage, such that those who know the difference between price and value cannot act upon such knowledge. Unfortunately, this point is often obscured by Keynes’ comments on “animal spirits” as animating market behavior ([1936] 1960: 161–4). In fact, he distinguishes “the instability due to speculation” from the “instability due the characteristic of human nature” (161), but accounts of Keynes’ perspective seem to elide this distinction. Accordingly, Fox (2009: 34, 338) discusses how Keynes did not in fact speculate on this basis in his role as portfolio manager for Cambridge University. Rather, he adopted a value-investing approach that is quite close to that of Graham, as described below. I cannot find a source for this quote. The closest citation is: “the market is not a weighing machine, on which the value of each issue is recorded by an exact and impersonal mechanism . . . Rather we should say that the market is a voting machine, whereupon countless individuals register choices that are partly the result of reason and partly of emotion” (Graham and Dodd [1934] 1940: 27). Yet while this quote seems to deny the market’s

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long-run “weighing” capacity, Graham does indeed seem to assume such a capacity, as discussed below. I mean “objective” in the sense of Abbott (1988: 35–40), of a set of conditions that confront all members of the relevant public in common ways that are subject to independent verification and which change more slowly than attempts at interpretation and adaptation. Thus, even though the economy is a collective construction, it confronts us in terms of a set of objective conditions. The past 15 years of General Electric’s dividend history may be found at . Such a record suggests that the management knows that it would face a significant reputational penalty should it stop paying dividends and especially if it reneged on a specific commitment to pay the upcoming quarterly dividend. In theory, our lucky investor could sell the shares immediately after the ex-dividend date, thus earning an astronomical weekly return of 12 percent, which corresponds to an annual return of 624 percent without compounding. In reality, this kind of return is unavailable because prices rise in the run-up to a dividend disbursement to a degree proportional with the size of the dividend. That is, prices efficiently incorporate the timing of the expected dividend. Note that in practice, the investor must also consider his needs for liquidity. That is, our calculations of yearly return assume that GE’s price will stay the same. If the investor may need his capital in the next year, he must necessarily worry about the possibility that GE’s share price will decline, thus crimping the return he receives from dividend income. Moreover, a large investor must be mindful that liquidation of a large position could itself lower the price, and thus his return. Note, however, that concerns about price declines apply to bonds as well, and the very large volume of GE shares means that it is highly liquid. Therefore, we are basically comparing apples to apples. And in fact, acquisition prices are typically a premium over current stock prices, suggesting that GE would sell for a much higher price than $16/share. In practice, one must consider the likelihood and price of liquidation. If there is reason to think that, for example, current management has legal or political means to prevent liquidation, a discount should be taken to the liquidation value. It is worth underlining the point that the return he realizes from the intrinsic value of the stock, whether via dividend yield or liquidation of assets, has nothing to do with other investors’ beliefs. When the price of a stock declines to a point at which a given investor is confident she can earn an attractive income from ownership of the security, it is rational for her to purchase the stock even if she thinks that the price may continue to decline (whereupon more purchases are warranted). Of course, it may require a very low price to give an investor such confidence. Our point is that every asset has such a price, even if it is negative (e.g., current owners may have to pay future owners to take the asset if it is encumbered with liabilities that exceed its assets and estimated earnings capacity). If the majority of current shareholders are so foolish as to sell at $1/share then our lucky investor can take control of GE and directly access its income stream, which he values as worth much more than $1/share. If only some owners are this foolish then our lucky investor buys as many shares as he can at $1, and the price will necessarily rise since the new set of shareholders will now offer shares at a price higher than $1. Related points are made in the recent finance literature. In particular, it has become widely recognized that there is a basic asymmetry between bull and bear markets (with the key

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implication that markets crash down but not up; see Miller 1977 for the foundational piece in this literature; see Rubenstein 2004 for an historical overview of the idea; and see Chen, Hong, and Stein 2002 and Ofek and Richardson 2002 for recent statements and empirical evidence), which derives from constraints on short selling. My approach is broadly consistent with this idea, but the key point of difference is that I am arguing that there is an asymmetry between bull and bear markets regardless of the availability of constraints on short selling. The reason is that whereas value–price arbitrage on undervalued assets is a nonspeculative maneuver that involves no market risk, short selling on overvalued assets is a speculative maneuver involving significant market risk of the kind captured in the paraphrase of Keynes. In this respect, the perspective advanced here is closest to the approach of Brunnermeier and colleagues, which sees short selling as highly limited even in the absence of short-selling constraints due to the need for a critical mass to bring prices down (see especially, Abreu and Brunnermeier 2003; Brunnermeier and Nagel 2004). However, Brunnermeier does not explicitly contrast such limits on short selling (given the misleading general label of “limits to arbitrage”; cf., Shleifer and Vishny 1997) with the absence of comparable limits in the case of arbitrageurs who seek to profit from undervalued assets. 27. And the EMH does not even apply when—as in the recent real estate bubble—it is impossible to engage in short selling (see G. Zuckerman 2009). Note, however, that even while the EMH relies on the possibility of short selling, it also implies that short selling should be very limited; in particular, we should not observe situations where short sellers hold their positions for extended periods of time. The reason is that insofar as market prices result from a process where correct valuations drive out incorrect ones to arrive at a price that is the best estimate of future income given available information, and insofar as a short position reflects dissent or skepticism that the current price is right (specifically, it suggests that the current price is too high), all but the most fleeting short positions present a contradiction in terms. Thus the paradox is that: (a) on the one hand, constraints against short selling make markets inefficient; (b) but, on the other hand, the very prevalence of shorting is a sign that markets are inefficient because it means that the full range of opinion is not incorporated into price.

References Abbott, A. D. (1988). The System of Professions: An Essay on the Division of Expert Labor. Chicago: University of Chicago Press. ——– (2001). The Chaos of Disciplines. Chicago: University of Chicago Press. Abreu, D. and Brunnermeier, M. K. (2003). “Bubbles and Crashes.” Econometrica, 71: 173–204. Baker, W. T. (1984). “The Social Structure of a National Securities Market.” American Journal of Sociology, 89: 775–833. Becker, H. (1963). Outsiders: Studies in the Sociology of Deviance. New York: The Free Press of Glencoe. Bernstein, P. L. (1992). Capital Ideas: The Improbable Origins of Modern Wall Street. New York: Free Press. Best, J. (2008). “Historical Development and Defining Issues in Constructionist Inquiry,” in J. A. Holstein and J. F. Gubrium (eds.), Handbook of Constructionist Research. New York: Guilford Press, 41–66.

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Black, F. (1972). “Capital Market Equilibrium with Restricted Borrowing.” Journal of Business, 45: 444–55. ——– (1986). “Noise.” The Journal of Finance, 41: 529–43. Brav, A. and Heaton, J. B. (2002). “Competing Theories of Financial Anomalies.” Review of Financial Studies, 15: 575–606. Bromberg, M. and Fine, G. A. (2002). “Resurrecting the Red: Pete Seeger and the Purification of Difficult Reputations.” Social Forces, 80: 1135–55. Brunnermeier, M. K. and Nagel, S. (2004). “Hedge Funds and the Technology Bubble.” The Journal of Finance, 59: 2013–40. Buffett, W. E. (1984). “The Superinvestors of Graham-and-Doddsville.” Hermes, Fall: 4–15. Chen, J., Hong, H., and Stein, J. (2002). “Breadth of Ownership and Stock Returns.” Journal of Financial Economics, 66: 171–205. Coleman, J. S. (1961). The Adolescent Society: The Social Life of the Teenager and its Impact on Education. Glencoe, IL: Free Press. DeLong, J. B., Shleifer, A., Summers, L. H., and Waldman, R. J. ([1990] 1993). “Noise Trader Risk in Financial Markets,” in R. H. Thaler (ed.), Advances in Behavioral Finance. New York: Sage, 23–58. Demers, E. and Lev, B. (2001). “A Rude Awakening: Internet Shakeout in 2000.” Review of Accounting Studies, 6: 331–59. Dreman, D. N. (1977). Psychology and the Stock Market: Investment Strategy Beyond Random Walk. New York: Amacom. Fama, E. F. (1965a). “The Behavior of Stock Market Prices.” Journal of Business, 38: 34–105. ——– (1965b). “Random Walks in Security Prices.” Financial Analysts Journal, September– October: 55–9. ——– (1970). “Efficient Capital Markets; A Review of Theory and Empirical Work.” The Journal of Finance 25: 383–417. ——– (1976). Foundations of Finance: Portfolio Decisions and Securities Prices. New York: Basic Books. ——–(1990). “Efficient Capital Markets: II.” University of Chicago, Center for Research in Security Prices Working Paper No. 303. ——– and French, K. R. (2004). “The Capital Asset Pricing Model: Theory and Evidence.” Journal of Economic Perspectives, 18: 25–46. Fisher, P. A. (1996). Common Stocks and Uncommon Profits and Other Writings by Philip Fisher. New York: Wiley. Fligstein, N. and Goldstein, A. (2010). “The Anatomy of the Mortgage Securitization Crisis,” in M. Lounsbury and P. M. Hirsch (eds.), Markets on Trial: The Economic Sociology of the U.S. Financial Crisis: Part A. Bingley, UK: Emerald, 29–70. Fox, J. (2009). Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street. New York: Harper Business. Goode, E. (1994). “Round up the Usual Suspects: Crime, Deviance, and the Limits of Constructionism.” American Sociologist, Winter: 90–104. Gorton, G. (2008). “The Subprime Panic.” Yale International Center for Finance Working Paper. Graham, B. ([1949] 1973). The Intelligent Investor: A Book of Practical Counsel (4th rev. edn). New York: Harper & Row. ——– and Dodd, D. ([1934] 1940). Security Analysis: Principles and Technique (2nd edn). New York: McGraw-Hill.

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Grossman, S. J. and Stiglitz, J. E. (1976). “Information and Competitive Price Systems.” American Economic Review, 66: 246–53. ——– (1980). “On the Impossibility of Informationally Efficient Markets.” American Economic Review, 70: 393–408. Jensen, M. C. (1978). “Some Anomalous Findings Regarding Market Inefficiency.” Journal of Financial Economics, 6: 95–101. Kandel, E. and Pearson, N. D. (1995). “Differential Interpretation of Public Signals and Trade in Speculative Markets.” Journal of Political Economy, 103: 831–72. Kandel, E. and Zilberfarb, B.-Z. (1999). “Differential Interpretation of Information in Inflation Forecasts.” Review of Economics and Statistics, 81: 217–26. Keim, D. B. (1988). “Stock Market Regularities: A Synthesis of the Evidence and Explanations,” in E. Dimson (ed.), Stock Market Anomalies. Cambridge: Cambridge University Press, 16–42. Keynes, J. M. ([1936] 1960). The General Theory of Employment Interest and Money. New York: St. Martin’s Press. Lintner, J. (1965). “The Valuation of Risky Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets.” Review of Economics and Statistics, 47: 13–37. Lounsbury, M. and Hirsch, P. M. (eds.) (2010). Markets on Trial: The Economic Sociology of the U.S. Financial Crisis: Part A. Bingley, UK: Emerald. Lowenstein, R. (1996). Buffett: The Making of an American Capitalist. New York: Doubleday. MacKenzie, D. A. (2006). An Engine, Not a Camera: How Financial Models Shape Markets. Cambridge, MA: MIT Press. ——– and Millo, Y. (2003). “Constructing a Market, Performing Theory: The Historical Sociology of a Financial Derivatives Exchange.” American Journal of Sociology, 109: 107–45. ——–, Muniesa, F., and Siu, L. (eds.) (2007). Do Economists Make Markets? On the Performativity of Economics. Princeton, NJ: Princeton University Press. Malkiel, B. G. (1985). A Random Walk Down Wall Street (4th edn). New York: Norton. ——– (2003). “The Efficient Market Hypothesis and Its Critics.” Journal of Economic Perspectives, 17: 59–82. ——– (1952). “Portfolio Selection.” The Journal of Finance, 7: 77–91. Martin, J. L. (2009). Social Structures. Princeton, NJ: Princeton University Press. Merton, R. K. ([1948] 1968). “The Self-Fulfilling Prophecy,” In Social Theory and Social Structure, 1968 Enlarged Edition. New York: Free Press, 475–90. ——– (1995). “The Thomas Theorem and the Matthew Effect.” Social Forces, 74: 379–422. Miller, E. M. (1977). “Uncertainty, and Divergence of Opinion.” The Journal of Finance, 32: 1151–68. Ofek, E. and Richardson, M. (2002). “The Valuation and Market Rationality of Internet Stock Prices.” Oxford Review of Economic Policy, 18: 265–87. Pozner, J.-E., Stimmler, M. K., and Hirsch, P. (2010). “Terminal Isomorphism and the SelfDestructive Potential of Success: Lessons from Sub-Prime Mortgage Origination and Securitization,” in M. Lounsbury and P. M. Hirsch (eds.), Markets on Trial: The Economic Sociology of the U.S. Financial Crisis: Part A. Bingley, UK: Emerald, 183–218. Reinhart, C. M. and Rogoff, K. S. (2009). This Time is Different: Eight Centuries of Financial Folly. Princeton, NJ: Princeton University Press. Roy, A. D. (1952). “Safety First and the Holding of Assets.” Econometrica, 20: 431–9. Rubenstein, M. (2004). “Great Moments in Financial Economics III: Short-sales and Stock Prices.” Journal of Investment Management, 2: 16–31.

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Scharfstein, D. S. and Stein, J. C. (1990). “Herd Behavior and Investment.” American Economic Review, 80: 465–79. Sethi, R. (2010). “The Invincible Markets Hypothesis.” Rajiv Sethi Thoughts on Economics, Finance, Crime, and Identity, February 10. (accessed October 27, 2011). Sharpe, W. F. (1964). “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk.” The Journal of Finance, 19: 425–42. Sheffrin, S. M. (1996). Rational Expectations (2nd edn). New York: Cambridge University Press. Shiller, R. J. (1990). “Market Volatility and Investor Behavior.” American Economic Review, 80/2: 58–62. ——– ([1990] 1993). “Speculative Prices and Popular Models,” in R. H. Thaler (ed.), Advances in Behavioral Finance. New York: Sage, 493–506. ——– (2005). Irrational Exuberance. Princeton, NJ: Princeton University Press. Shleifer, A. (1986). “Do Demand Curves for Stocks Slope Down?” The Journal of Finance, 41: 579–90. ——– and Vishny, R. W. (1997). “The Limits of Arbitrage.” The Journal of Finance, 52: 35–55. Thaler, R. H. (ed.) (1993). Advances in Behavioral Finance. New York: Sage. Treynor, J. L. (1965). “How to Rate Management of Investment Funds.” Harvard Business Review, 43/January–February: 63–75. Westphal, J. D. and Zajac, E. J. (2004). “The Social Construction of Market Value: Institutionalization and Learning Perspectives on Stock Market Reactions.” American Sociological Review 69: 433–57. Williams, J. B. ([1938] 1956). The Theory of Investment Value. Amsterdam: North-Holland Publishing Co. Zuckerman, E. W. (1997). “Mediating the Corporate Product: Securities Analysts and the Scope of the Firm.” PhD thesis, University of Chicago, Chicago, IL. ——– (2004a). “Structural Incoherence and Stock Market Activity.” American Sociological Review, 69: 405–32. ——– (2004b). “Towards the Social Reconstruction of an Interdisciplinary Turf War: Comment on Zajac and Westphal, ASR, June 2004.” American Sociological Review 69: 458–465. ——– (2008a). “Realists, Constructionists, and Lemmings, Oh My! [Part 1].” orgtheory.net, October 26. (accessed October 27, 2011). ——– (2008b). “Realists, Constructionists, and Lemmings, Oh My! [Part 2].” orgtheory.net, October 31. (accessed October 27, 2011). ——– (2010). “What if We Had Been in Charge? The Sociologist as Builder of Rational Institutions,” in M. Lounsbury and P. M. Hirsch (eds.), Markets on Trial: The Economic Sociology of the U.S. Financial Crisis: Part B. Bingley, UK: Emerald, 359–78. ——– (2012). “Construction, Concentration, and (Dis)Continuities in Social Valuations.” Annual Review of Sociology, vol. 38. ——– and Rao, H. (2004). “Shrewd, Crude, or Simply Deluded? Comovement and the Internet Stock Phenomenon.” Industrial and Corporate Change, 13: 171–213. Zuckerman, G. (2009). The Greatest Trade Ever: The Behind-the-Scenes Story of How John Paulson Defied Wall Street and Made Financial History. New York: Broadway Books.

chapter 13

fi na nci a l a na lysts 1 l eon wansleben

Introduction Financial analysts “guide investors and asset managers in their investment choices and are central to investment banking, providing expertise on initial public offerings, mergers and acquisitions; they assess and manage financial risks in a variety of settings, and they help create new investment instruments” (Knorr Cetina 2011: 405). Thus, instead of investing or speculating on financial markets themselves, “financial analysts are individuals compensated for providing investment research information, recommendations, advice, or market decisions” (Bauman 1988: 1,809).2 Within financial institutions (investment banks, insurance companies, mutual, pension, and hedge funds, securities firms, and so forth), analysts specialize in different markets (such as equities, fixedincome, foreign exchange, and commodities), particular objects traded on these markets (such as companies, industries, currencies), specific methods (e.g. fundamental analysis and chart analysis), and specific types of “advice” business, that is, sell side (advice as a service to a brokerage’s clients) or buy side (advice for proprietary or mandatory investment). In 2008, 250,600 financial analysts (including fund and portfolio managers) were working in the United States, of which 47 percent were employed in the finance or insurance business (BLS 2010).3 In the same year, 115,000 candidates from 150 countries registered for the Chartered Financial Analyst (CFA) exam program, the most established certification for analysts. The CFA designation is currently held by 86,700 financial professionals, of which approximately 20 percent work as financial analysts. Increasingly, analysts from non-US regions pass the CFA exam; while the share of Asian charter-holders is still only 15 percent, Asians now account for 40 percent of CFA candidates. More than 70 percent of candidates in 2008 were younger than 30 years of age (CFA 2010). This chapter is based on a review of the sociological and economic literature as well as my own research on analysts in foreign exchange markets (Wansleben forthcoming). The sociological research can be organized according to two important traditions. One

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conceptualizes analysts as institutional and organizational agents. “Institutionalists” show that analysts maintain hegemonic categories for valuating financial entities (shareholder value), that they imitate other analysts’ judgments, and that they often act as intermediaries divided by conflicts of interest. A second tradition studies analysts’ knowledge practices and uncovers the omnipresence of choice and interpretation. Here, analysts are portrayed as selectively drawing on quantitative and qualitative information as well as constructing calculative frames and stories; analysts’ knowledge is characterized as distinct from scientific knowledge. Financial economics mainly studies analysts when testing market forecasts. Alfred Cowles already administered such tests in 1933 but they have become increasingly relevant in the context of the efficient market hypothesis (EMH). Behavioral finance studies analysts in order to explore deviations from rationality and efficiency (such as herd behavior or overreaction to news); financial economists are also interested in “conflicts of interests.” The most severe limitation of these various research strands, as reflected in the present chapter, is the predominant focus on analysts within the context of US–American equities markets. In the following sections, I will discuss the existing literature by focusing on the questions of, first, analysts’ historical emergence, practices, and professionalism, and then on the role of analysts in financial market capitalism.

Historical perspectives The following account distinguishes two separate histories of financial analysis—that of “chart analysis,” also known as “technical analysis,” and “fundamental analysis”. Historical literature on analysts is generally scarce but the history of fundamental analysis can be reconstructed from practitioner accounts. Financial analysis emerged as a twentieth-century profession. In the eighteenth and much of the nineteenth century, finance in general was not yet associated with professional status or knowledge. In contrast, many writers and intellectuals at that time regarded finance as a sphere of immorality and antiscience, associating it with “dark powers,” “dishonorable skills,” “illusion and folly,” or the “Devil’s Mechanick” (Preda 2009: 85). This view, as Geoffrey Poitras (2005: 87) points out, applied to stock markets in particular. However, during their subsequent institutionalization and professionalization, market practitioners began to develop authoritative accounts of finance, using media such as “how-to” brochures and para-scientific treatments.4 These texts made two contributions: they created an early rationalization of financial behavior, based on rules and information, and they drew analogies between finance and established scientific enterprises, especially physics and biology. According to Alex Preda (2007, 2009), the introduction of the stock ticker in 1867 (Preda 2006) triggered the rise of a first paraprofessional group of analysts—the “chartists.” This group, located on the east coast of the US, was formed even “before fundamental analysis emerged as a form of financial expertise in the 1930s and before the main principles of financial economics

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were systematically elaborated in the 1950s and the 1960s” (Preda 2009: 170). Preda’s argument is that while financial markets became institutionalized and technologized through the price-recordings of the ticker, a certain group formed around techniques and strategies of “privileged witnessing” of ticker information, primarily by visually charting, interpreting, and forecasting price variations. This formation was a contingent sociocultural process, based on networks among market insiders, support by academics, creation of charismatic leadership, and the development of an idiosyncratic language of “double bottoms,” “head-and-shoulders,” and so on. Existing relationships with (potential) customers were also key, but still more important was chart analysts’ success in reconfiguring their role as the “[l]egitimated Other” (Meyer and Jepperson 2000). Fundamental analysis emerged from a different tradition, and its forerunners were the “statisticians” and “ingenious accountants” within banks (Jacobson 1997: 19–20) rather than chart analysts.5 Before 1929, however, these statisticians and accountants faced a serious obstacle to their analyses: neither corporations nor financial insiders shared information on corporate earnings and book values (among others) with the general public (Knorr Cetina 2011). This became increasingly problematic as more “outsiders” gradually invested in the financial markets, especially during the bond boom of the 1920s. Accordingly, key events in the emergence of fundamental analysis were the Great Crash and New Deal’s regulatory responses to it. New Deal legislators were convinced that one of the key causes for the 1929 crash was that “investors [had been] misled by exaggerated claims and inadequate disclosure of the true financial position of corporations” (Simon 1989: 296). They thus introduced several reforms, the most important of which are the Securities Exchange Acts of 1933 and 1934. While the 1933 Act primarily established laws for new issues, including registration and disclosure requirements, the 1934 Act focused on annual, biennial, and event-related reporting requirements for traded securities (Benston 1973: 133), attributing supervisory functions to the newly founded Securities and Exchange Commission, or SEC. Jacobson regards these Acts as “founding legislation” (1997: 25) of fundamental analysis. How could a “profession” be “founded” on the basis not of the scarcity of information, but of its abundance? Jacobson identifies two factors: first, analysts had developed practices of interpreting companies’ earnings power as well as the “value” of securities before 1933. As a result, they had the organizational position in order to claim this interpretation/valuation as their jurisdiction. One major figure, Benjamin Graham,6 along with David Dodd, synthesized a methodology in Security Analysis, first published in 1934. At the very beginning of the 1962 edition of the book, they maintain: The objectives of security analysis are twofold: First, it seeks to present the important facts regarding a publicly held corporate stock or bond issue in a manner most informing and useful to an actual or potential owner. Second it seeks to reach dependable conclusions, based upon the facts and applicable standards, as to the safety and attractiveness of a given security at the current market price or at some assumed price. (Graham, Dodd, and Cottle [1934] 1962: 1)

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Hence, as a response to the Great Crash and the new regulatory situation (Poitras 2005: 110), Graham and Dodd redefined the financial analyst as follows: first, he or she was supposed to research, collect, organize, and summarize information provided by companies. While information was in principle public, it was still necessary to “dig for facts” (Graham, Dodd, and Cottle [1934] 1962: 1), to select important aspects, and to “make various kinds of adjustment to the material in order to bring out the true operating results in the period covered and particularly in order to place the data of a number of companies in a fairly comparable plane” (25). Second, the analyst was supposed to act as “financial statesman,” critically assessing the soundness of companies’ accounting methods, information, and compliance with the rules (34–5). Third, the task of the analyst was valuation, judgment, and, as the final outcome, advice. This objective could be fulfilled, according to Graham and Dodd, when the analyst properly valuated securities, based on “indicated average future earning power” (28, emphasis in original), comparing these valuations with the current market prices. Cases of over- or undervaluation—a frequent instance according to the authors—provided investment opportunities. To some extent, then, Graham and Dodd developed a profile of financial analysis that they likened to professions such as law and medicine (24): “Results could not be guaranteed, but the integrity of the process itself could be of some comfort” (Jacobson 1997: 56). The critical feature was the definition of tasks that could be, to some extent, standardized, that is, based on abstract knowledge likened to a “science” (Graham [1952] 1995). It must be considered, however, that many people, especially academics, challenged the possibility of codifying financial knowledge and that even Graham emphasized the importance of judgment (Graham [1952] 1995: 30). A second factor, though, was equally important for the rise of financial analysis in the post-1929 context: the ongoing financialization of the US economy and public. Jacobson (1997: 46) provides the following description: “Through the agency of pension funds (many started up during the war), mutual funds and insurance companies, an everwider slice of the general public was introduced to the experience and advantages of stock ownership.”7 Share ownership doubled in the 1950s (Jacobson 1997: 109). This expansion created not only demand for investment advice but also, on the basis of New Deal legislation, public legitimacy for analysts as advocates of the growing number of lay investors in need of information. Jacobson avers that “once generally ignored, or worse, by their subjects, the analysts had been acquiring legitimacy in recent years. They spoke of a building-up process that by the early 1950s had reached a point where when analysts asked, executives answered” (Jacobson 1997: 7). Analysts developed professional organizations. Growing local societies in numerous American cities became advocacy and training institutions, representing what was now known as financial analysis. From 1945 onwards, the New York society had its own journal, The Analysts Journal (later Financial Analysts Journal); in 1947, local societies were integrated into a National Federation of Financial Analysts (NFAA), later known as the Financial Analysts Federation (FAF). Professionalism and the codification of analysts’ knowledge became central projects of the Federation. The NFAA thus founded the

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Institute of Certified Financial Analysts (ICFA) in order to prepare, administer, and evaluate a professional certificate for analysts: the CFA. The institute operated from 1959 onward and administered the first tests in 1963. Another development was critical, as researched by Donald MacKenzie. In his book An Engine, Not a Camera, he describes how “in the 1960s and 1970s the new financial economics gradually became a recognized, reasonably high-status, enduring part of the academic landscape, one that could, and did, successfully reproduce itself and grow” (MacKenzie 2008: 72). The outstanding elements of the new financial economics was modern portfolio theory (MPT), developed by Harry Markowitz and William Sharpe, Eugene Fama’s EMH, the capital asset pricing model (CAPM), and the Black-Scholes-Merton formula. While the emergence and content of these “theories of finance” have been analyzed elsewhere, one aspect is key for financial analysis: they all stand in sharp contradiction with the codified knowledge of financial analysts, especially Graham and Dodd’s approach, as well as in contradiction with the hitherto assumed function of financial analysis. All these theories argue against the valuation of stocks on the basis of fundamental versus market value. They focus instead on risk as the relationship between an individual security’s performance and the market. MPT, especially, can be understood as a severe attack on the analyst profession since it regards individual stock picking, known among analysts as the practice of “selection,” as an inefficient investment strategy: “By shifting focus onto the portfolio diversification problem, modern Finance argued for the elimination of the firm specific risk that was the stock in trade of the Old Finance adherents” (Poitras 2005: 123). Indeed, analysts first reacted to the rise of new finance theory with “hostility” (MacKenzie 2008: 75). For instance, it is documented that these theories did not find their way into the Financial Analysts Journal until some time in the 1980s—long after their establishment in academia (Bernstein 1992). Even once recognized, however, analysts did not wholly adopt or subscribe to the theories. Rather, while academic approaches and the entire subject of fund management were subsequently included in the CFA tests, they still coexist with analyst-specific practices of valuation and advicegiving. Generally speaking, the development of financial economics indicates, however, that theoretical knowledge has become gradually more important. The ICFA was and is the institution ready to profit from this development. As a quasi-academic institution situated at the University of Virginia, it can incorporate new academic ideas into the CFA test curriculum. Accordingly, the ICFA has gained significance in relation to the FAF and the local analyst societies (Jacobson 1997: 124). Another critical development has been the globalization of financial professions, largely consisting of an (idiosyncratic) adoption of North American standards of professional designations and methods (including accounting standards). Societies on other continents, the European Federation of Financial Analysts’ Societies (EFFAS) and the Asian Securities Analysts Federation (ASAF), were founded much later than FAF (in 1962 and 1995, respectively) and in cooperation with the US–Canadian Federation. National as well as continental federations today form the International Society of

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Financial Analysts (ISFA). The CFA, once invented as a certification within the context of US–Canadian “professionalization”, is today “best described as a self-study, distancelearning program that takes a generalist approach to investment analysis, valuation, and portfolio management, and emphasizes the highest ethical and professional standards” (Johnson et al. 2008). Tests are taken at different locations around the globe. However, due to the US bias of the CFA program, other regions have (collaboratively) developed alternative, less recognized certifications (e.g., the “Certified International Investment Analyst” designation). In addition, analysts’ objects of study are globalizing: every serious global bank needs to cover “emerging markets,” hence each needs research divisions focusing on (and sometimes being located in) Asia, Latin America, and what is referred to as EMEA (Eastern Europe, Middle East, and Africa).

Analyst practices Practices are largely a sociological concern because practices only come into focus once we are interested in how institutional contexts, organizational cultures, technologies, commitments to different approaches,8 and changes in “prevalent theories of valuation” (Zuckerman 2000: 614) are enacted by micro-choices during the actual “doing” of financial analysis. Such analyses contribute to the explanation of both isomorphism and differentiation in valuations largely ignored in orthodox financial economics (Zuckerman 2004). Most research has focused on sell-side fundamental equity analysts. A prevalent interest is how this analyst group “frames” companies and their stocks within an economy and industry. In most cases, special economists employed by banks conduct macroeconomic analyses (forecasts of cyclical and long-term growth, inflation, interest rates, exchange rates) and equity analysts are supposed to use these “inputs”—not least because this makes a bank’s research “consistent.” In reality, however, many analysts resist this “top-down procedure” (CFA 2008: 118) because they distrust economists’ forecasts. Either they have their own “big picture” or they simply do not regard macroeconomic forecasts as relevant (Mars 1998: 36–44, 58–72). More important are framings of companies according to industries9 because “industry boundaries reflect divisions among stock market product categories as well as the professional specialties of securities analysts. Divisions among industry specialties are reinforced by public rankings which evaluate analysts within industries” (Zuckerman 1999: 1,408). The textbooks emphasize that analysts should analyze how industries are differently affected by the growth cycle, demographic developments, changes in trade conditions, technological developments, politics, and regulation. Further, they should use quantitative and qualitative means to discern the value chains and competition structure of an industry. Mars (1998) shows that such industry analyses are far from straightforward: analysts face considerable data problems, cope with the unpredictability of industry “trends,” and realize

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Blodget

Category

Abelson

Internet company

Analogy

Dell

Category Internet book retailer

Key metric

Revenue

Analogy Barnes & Noble

Key metric

Profits

figure 13.1 Two “Calculative Frames” for Amazon.com Constructed by the Analysts Henri Blodget and Jonathan Cohen (Beunza & Garud 2007: 27). By using different industry classifications (“Category”), analogies to other companies and metrics, the two analysts arrive at a target value of the Amazon.com stock of $400 (Blodget) and $50 (Cohen).

that many companies within an industry are indeed not comparable. Zuckerman (2004) analyzes the problem of framing and classification in terms of the “structural incoherence” and ambiguous identity of some stocks, resulting in heterogeneous valuations and, in consequence, price volatility as well as excessive trading. Beunza and Garud (2007: 26) suggest that analysts exploit these ambiguities: they do not passively adopt but actively construct “calculative frames,” consisting of “internally consistent networks of associations, including (among others) categories, metrics and analogies.” Beunza and Garud further show the efficacy of creativity in “calculative framing”: during a period from 1998 to 2000, divergent framings of Amazon.com as an Internet company and as a bookseller generated very different valuations and sparked “framing controversies” among prominent analysts (see Figure 13.1). Besides economic and industry frames, “overflowings” (such as terrorist attacks and bank crashes) and alterations (such as new tools and new models) of these frames, analysts are primarily concerned with company information (Barker 1998: 10). Indeed, the profession of fundamental analysis only emerged once companies were required to “disclose” their financial situation. Analysts’ main sources are the annual and quarterly result announcements and financial statements, unexpected company press releases, and other related news (see Table 13.1). However, companies must not be understood as neutral information providers but as interested self-promoters, engaged in various practices of “creative accounting,” “window dressing,” and outright “cooking of the books”. The challenge for analysts therefore is to act as a “financial statesman” (Graham, Dodd, and Cottle [1934] 1963: 34–5) or financial detective, looking for clues of inconsistencies in company reports (Mars 1998: 96). But checking the official reports would not suffice: a good analyst would need to be “out on the streets,” going to companies’ analyst conferences, maintaining intense contact with investor relations officers, visiting headquarters

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Table 13.1 Sources of information ranked according to their importance for analysts, surveyed by Barker 1998 Ranking of analysts’ prioritized sources of information general

direct from the company

Direct contact with the company Analyst meetings Results announcements Annual report and accounts Industry contacts Interim reports and accounts In-house economics Industry information services Clients Sales desk AGM Market news In-house technical analysis Companies house Newspapers Reports of other brokers

Personal contact—by phone, writing, or individual contact Results announcements and analyst meetings Reports and accounts Organized site visits and other presentations for groups of analysts

and production sites (Mars 1998: 86–111). Knorr Cetina coins such company visits “proxy ethnographies” because they aim to fill the gaps left by disclosed information, following an “impressionist” logic (Knorr Cetina 2010: 34–7; see also Mars 1998: 103 and Faust, Bahnmüller, and Fisecker 2010: 53). Summarizing the specific nature of analyst knowledge, Knorr Cetina (2011) argues that analysts’ entire “epistemic profile” is conditioned upon the temporal (decaying) and proxy ontology of their ground data. How do analysts come from this informational reality to their “product,” namely advice and recommendations based on valuations? In fact, analysts do valuate but their final statements of what a company is worth might be less relevant than commonly thought. Many authors, for example Winroth, Blomberg, and Kjellberg (2010: 10–11), argue that customers, especially the more sophisticated financial clients, are more interested in facts, underlying assumptions, arguments, and stories than in recommendations; Hägglund (2000) posits that analysts’ choice of valuation models is more influenced by facilitating client conversations about the “quasi-company” rather than by their functionality in calculating objective value. Principally, two valuation methods can be distinguished: intrinsic and relative. Intrinsic valuation is based on the notion of net present value of actual future cash flows from the company to the investor. Models that calculate intrinsic value accordingly include the dividend discount model (DDM), operating cash flow model, and free cash flow to equity model (CFA 2008: 174). While the

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notion of value here is quite clear, these models face the problem of inputs based on estimates. Relative valuations circumvent some of these problems by looking at current prevailing market valuations. Ratios used are price/earnings (P/E), price/cash flow (P/CF), price/book ratio (P/BV), and price/sales ratio (P/S). These ratios, however, also entail problems: according to the CFA handbook, the prevailing market valuation might be inflated by a bubble, comparisons of different ratios of different industries as well as among different companies might be misleading, and, again, estimates of earnings, book value, and so forth can be wrong. Frank Mars (1998) studies the actual use of these valuation methods. His first observation is the centrality, not of the models, but of the tools: analysts maintain spreadsheets for all “their” companies with numerous columns covering absolute and key figures (such as equity to asset ratios, profit margins, and return on equity). Key figures should make companies commensurable but such commensurability often fails (Chambost 2010: 7–8). Mars further notes that not one of the analysts I studied analyzed the “intrinsic value” of a company. The main reason for not following the textbook method is the complexity of the procedure. The formula requires you to predict three factors and in all three cases you can be wrong. (1998: 139)10

Instead, analysts estimate earnings directly (using gut feelings, tinkering with figures, and so forth) and then use these estimates as inputs to P/E. Moreover, they cope with the contingencies of this method by starting not with the calculation but rather with the story they aim to tell about a company. Numbers are then adjusted until they fit the plot. Stories are at the center of analyst practices because they absorb heterogeneous information, connect past and future, and rely on well-established (commonsense) plots. Moreover, stories, usually communicated via reports, facilitate analysts’ conversations with clients (Hägglund 2000: 329), motivate trading (Knorr Cetina 2010: 28–9), and fuel status differentiation within the analyst community (Wansleben forthcoming). The logic of fundamental valuation in equity analysis is to estimate some value indicator for the concerned company and relate this indicator to the market price. The outcome should then be an analyst’s assessment of whether a company is over- or undervalued (Hooke 2010). What is known as market analysis, by contrast, aims at analyzing and/or predicting the (valuation) dynamics of markets in their own right. These dynamics have long been recognized and recently discussed under the heading of “reflexivity” (Black 1986; Keynes [1936] 1973; Soros 1994). Hardly any analyst, not even a dedicated “fundamentalist,” can ignore this phenomenon.11 One simple reason might be that market prices deviate from “fundamental valuations” considerably and over extended periods of time. The other reason might be that analysts are acutely aware of how “market movers” (high-status traders and analysts) push prices and spread rumors, and how reciprocal observation drives price movements. Consequently, a central feature of financial analysis is that analysts observe each other. For that purpose, they primarily use a specific technology of “market expectations,” namely analyst consensuses. First developed in 1971 by a US brokerage firm, analyst consensuses today are published by specialized information providers, including Reuters and Bloomberg. Analyst

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consensuses differ in detail but mainly consist of means and medians of analyst forecasts as well as listings of the individual forecasts of the contributing institutions for numerous economic variables, indexes, exchange rates, and company earnings (among others). Chambost (2010) discusses the homogenizing effect of analyst consensuses on both the companies covered and the analysts12 covering them, but she also stresses how analysts “play with” and differentiate on the basis of the consensus. More specifically, analysts use the consensus in three ways: they use it as a “simplification mechanism” or “anchor” when making their own forecasts; they take it as a reference point in order to consciously position themselves in relation to their competitors and the market as a whole; and they use the consensus in order to predict market surprises which occur when actual numbers deviate from the majority scenario. Developing surprise scenarios is a “fast and frugal heuristic” (Gigerenzer 2008) for predicting market movements without knowing the precise value of fundamentals (Svetlova 2010). The deployment of such tactics suggests that the dynamics of markets and analysts’ daily coping strategies often conflict with the ideal of fundamental analysis, as set forth by Benjamin Graham and his followers. A tension thus arises between fundamental analysts’ normative expectations regarding “fair” financial value and cognitive expectations about what actually drives market prices. Schmidt-Beck (2007) and Langenohl (2007) argue that analysts manage this tension by distinguishing between short-term volatility and long-term convergence between fundamentally determined value and market price. The expectation of longterm rationality, then, is normative because it is inflexibly sustained despite counterfactual evidence which is interpreted as “deviance” (irrationalities). “Chart” or “technical analysis” is less well studied despite its long history (Lo and Hasanhodzic 2010), its institutionalization (Preda 2009: 148), and its ubiquitous use in some markets: traders in London’s foreign exchange market (the major FX trading spot) use fundamental and chart analysis (Allen and Taylor 1990; Cheung, Chinn, and Marsh 1999), hold heterogeneous expectations, and consequently generate unpredictable movements in exchange rates (Frankel 1993). Chart analysis is not integrated into economic theory but rests on the assumption of repetitive price behavior that can be analyzed by focusing on trends in aggregate dynamics. This basic assumption finds expression in various “rules of thumb” provided, among others, by the Dow theory. On these grounds, chart analysis has developed as a heuristic for visualizing and observing the market as a phenomenon sui generis (Lo and Hasanhodzic 2009).13 Charting techniques commenced with “cross-section paper (almost any kind can serve), a daily newspaper which gives full and accurate reports on stock exchange dealings, [and] a sharp pencil” (Edwards and Magee [1949] 1966: 8); today they rely on sophisticated computer applications and algorithms (Lo, Mamaysky, and Wang 2000), using feeds of real-time price data. Technical analysis is often understood as “subjective” not least because of the variety of techniques: annual, monthly, daily, or minute charts may include moving averages for different time intervals; bars indicating highest, lowest, and closing prices; trend channels; trading volumes; trading signals; manual drawings of arrows; and so on. “Technicians” work with these (moving) charts by visually identifying recurring patterns on their screens. They differentiate “primary” and “secondary trends” and identify

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“reversal” (e.g., “head-and-shoulders”) and “continuation formations” as well as “resistance” and “support levels”. The success of these practices is inconclusive: some economists liken chart analysis to astrology (e.g., Malkiel [1973] 2003), while others see some information content in pattern recognition (Lo, Mamaysky, and Wang 2000). At least as interesting is the question of what makes chart analysis so popular among practitioners. A possible analytic strategy could commence with the speculation that chart analysis’ “visual mode of analysis is more conducive to human cognition” (Lo, Mamaysky, and Wang 2000: 1,706).

Analysis as a profession In the 1960s, reflections about “whether financial analysis is a profession” became an explicit concern of the US Financial Analysts Federation. A committee was founded and various position papers presented at Federation meetings, which were later published in the Financial Analysts Journal.14 A key concern was the assembling, codifying, teaching, testing, and certifying of a body of analyst knowledge (Knorr Cetina 2010: 4–5). Ketchum—a finance professor involved in developing the first analyst certification curriculum—states that knowledge builds the “keystone of a profession” (1967: 35). The outcome of these reflections is a certified body of analyst knowledge: the CFA curriculum.15 Currently, CFA candidates are tested in a three-level exam procedure on subjects ranging from “Ethical and Professional Standards” (quantitative methods, economics, financial reporting and analysis, corporate finance), “Investment Tools” (equity, fixed income, derivatives, alternative investments), and “Asset Valuation,” all the way to “Portfolio Management and Wealth Planning” (CFA 2008). The current curriculum reflects both the growing importance of the buy-side (portfolio and fund managers) and CFA’s attempts to monopolize a globally accepted certification for finance professionals generally. Such attempts, however, still remain unsuccessful. Among the reasons are certainly resistance by established analysts without certification and the voluntary nature of such qualifications. While some business schools integrate CFA into their curricula and some organizations (such as the New York Stock Exchange) accept the CFA as a substitute for their own entry exams, there is only partial mandatory licensing in the financial services industry (Bauman 1988: 1,814).16 The main attack on attempts at knowledge codification, though, comes from outside of the profession, namely from financial economists. In 1933, Alfred Cowles had already published a paper, claiming that the recommendations of securities analysts could not generate any excess returns when compared to a portfolio reflecting the entire market. Burton Malkiel ([1973] 2003) and Ferraro and Stanley (2000) have, among others, continued this line of research, referring to the EMH as a theoretical explanation of ineffective expertise. Popular tests of analysts’ forecasting abilities such as The Wall Street Journal’s “Dartboard Contests” or the Chicago Sun-Times’ stock picking contest against the capuchin monkey Adam Monk, as well as huge losses among retail investors during

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financial crises, have further undermined trust in the knowledge foundation of finance professionals (Schmidt-Beck 2007: 160). A further line of research does not focus on market efficiencies but rather on the overreactions (De Bondt and Thaler 1990) and underreactions (Abarbanell and Bernard 1992) of analysts to information such as companies’ earnings announcements. Easterwood and Nutt (1999) synthesize these studies by arguing that analysts overreact to positive earnings announcements and underreact to negative figures. The primary underlying interest of this research strand is to integrate analysts into a behavioral picture of markets characterized by excessive volatility. Rao, Greve, and Davis (2001) add a neo-institutional interpretation of biases in recommendations by showing that because forecasting is uncertain and career paths depend on relative performance to other analysts, analysts imitate the judgments of their peers. However, the overall evidence on analysts’ forecasting performances is inconclusive. Womack (1996) shows that, on average, following analyst recommendations can, for a limited period of time, generate positive returns. Barber et al. (2001) confirm Womack’s results and find valuable information in analysts’ consensus recommendations. A more immediate inquiry into analysts’ knowledge does not focus on the value of aggregate analyst opinions but on possible differences between analyst competencies. Stickel (1992), Jacob, Lys, and Neale (1999), and Mikhail, Walther, and Willis (2004) show that there are persistent differences in analysts’ stock picking and forecasting abilities. Stickel shows that high-ranking analysts—that is those selected for Institutional Investor’s “All American Research Team”17—on average issue more accurate earnings forecasts. Jacob, Lys, and Neale (1999: 80) argue that such differences in forecasting accuracy are “both situational (created by the demands and environment of the brokerage house) and dispositional (analysts’ innate ability).” Some authors see these findings as evidence for the extended theory of market efficiency which considers information-seeking costs (Grossman and Stiglitz 1980). Another interpretation is that some forecasts are more accurate because they trigger the predicted price movements. But overall, the statistical value of analyst forecasts is inconclusive, at best. The second intensively reflected concern of analysts is their legitimacy as a profession. On the one hand, analysts have quickly identified a potential source of legitimacy: the fostering of economic prosperity through the efficient allocation of capital by welladvised investors (Bauman 1988: 1810; Preda 2009: ch, 6; Randell 1961: 70). On the other hand, analysts have considered that legitimacy might be hampered by their lack of association with a “social good” (Hayes 1967: 29), their exclusive contact to “affluent individuals or corporations” (Hayes 1967: 29), and the negative public image of financial markets in general (Hayes 1967: 31). Moreover, William Norby, once President of the FAF, noted as early as 1968 that a threat to legitimacy was posed by “the potential conflict at the professional level between research and sales” (Norby 1968: 12). The analyst associations have dealt with these legitimacy problems by designing “codes of ethics”. The current code of the CFA involves rules on lawful conduct, independence, objectivity, prudence, care, diligence and suitability in analysts’ research, and loyalty toward clients and employers, as well as disclosure of any conflicts of interest (CFA 2008). CFA candidates and members can be sanctioned if they violate these rules.

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However, these codes as well as their organizational counterparts—so called “Chinese Walls” between organizational units with conflicting interests—have proven largely “ceremonial” and “loosely coupled” to practices (Fogarty and Rogers 2005: 339), as became evident during a specific historical period: in the 1990s, mergers enabled by deregulation had dissolved the separation between investment banks and brokerage houses.18 This situation radically changed the position of sell-side analysts; they were now supposed to “originate deals” and help in the lucrative business of underwriting (Swedberg 2005: 189). This new role transformed analysts from back-office “statisticians” to full-fledged front-office workers whose status and salaries, in some cases, exceeded those of star traders (Ho 2009: 78). Status was increasingly constituted by analyst rankings such as Institutional Investor’s “All American Research Team” or, in Europe, the “Extel Awards,”19 and served as one of the key “assets” of investment banks in attracting corporate and institutional clients. However, this new situation also produced severe conflicts of interests: analysts issued reports on firms that were current or prospective clients of the corporate finance departments of their employers. Conflicts arose because “whereas corporate finance seeks to promote its clients’ deals (issuance of debt and equity securities and M&A deals) through favorable ratings, analysts seek to rate corporate finance clients independently and objectively” (Hayward and Boeker 1998: 2). Early on, economists and sociologists pointed out such conflicts, demonstrating that brokerage houses’ recommendations were positively biased in cases when these houses functioned as the lead underwriters for the recommended companies’ initial public offerings (Hayward and Boeker 1998; Michaely and Womack 1999). The Wall Street Journal and The New York Times also reported on conflicts of interests, including the fact that analysts’ compensations indeed depended on their contributions to their employers’ investment banking business.20 However, the actual processes within the organizations only became visible when Eliot Spitzer, then Attorney General of the State of New York, led an investigation against investment banks, scrutinizing thousands of e-mails and other internal documents. His investigations in two cases are particularly well documented, namely those concerned with the analysts Henry Blodget and Jack Grubman. Henry Blodget had become famous for his $400 call on Amazon.com in December 1998, a stock first trading at about $240 and then surpassing Blodget’s call within a month (Beunza and Garud 2007). In 1999, Blodget had taken the place of Jonathan Cohen at Merrill Lynch, becoming the top-rated Internet analyst and one of the most mass-mediated financial figures of the dotcom era. During Spitzer’s investigations, it became evident that Blodget had not always been convinced by his own bold buy recommendations on companies like “InfoSpace” and “GoTo.com”, referring to such stocks in internal memos as a “piece of shit” or “piece of junk”. The e-mails also explicitly revealed conflicts of interests.21 Spitzer’s second famous case was Jack Grubman, another star analyst and “rainmaker” of the dotcom boom, who with a 20-million dollar average salary had become the highest-paid stock analyst (Cassidy 2003: 12).22 But Spitzer’s target was neither Blodget nor Grubman. In an interview after the investigations and the “Global Settlement” with the banks, the Attorney General stated that

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the problems were structural . . . Everybody had permitted analysts to become appendages of the investment-banking system. It didn’t seem reasonable to drop the criminal axe on Merrill Lynch because of this. It did make sense to say to them, “You’ve got to change the way you do business in a pretty fundamental way.” (Cassidy 2003: 9)23

Studies by financial economists have confirmed Spitzer’s allegations (Barber, Lehavy, and Trueman 2007), showing for the period between 1996 and mid-2003 that investors following the buy recommendations of securities firms without investment banking arms had profited 3.1 basis points (almost 8 percent annualized) more than investors following the buy recommendations of investment banks. These differences, even more pronounced when banks were lead underwriters, largely stem from divergent returns during the bear market that began in March 2000. They confirm investment banking analysts’ reluctance to downgrade stocks underwritten by their banks even as prospects worsened. Hong and Kubik (2003) relate conflicts of interests to analyst career paths. They show that, while forecasting accuracy matters most, analysts’ careers are also boosted by a positive bias in their recommendations. The authors therefore conclude that conflicts of interests might be broader than the focus on investment banking relationships suggests. Indeed, they may well involve the general influence of sales interests on research, the dependence of analysts on companies for information (leading to an extreme buy bias (Fogarty and Rogers 2005), and the investment interests of the analysts themselves. Knorr Cetina suggests that the professional identity of analysts entails not only the “rationalization” of investments but also their “incentivization” (2011; see also Fogarty and Rogers 2005: 351).

Analysts, investors, and firms Since the 1990s, political economists and institutional sociologists, among them Michael Useem (1996), Neil Fligstein (2001), and Gerald Davis (2009), have identified a structural transformation of the US economy toward financial markets, consisting (among other aspects) of an increased orientation of firms toward their valuations on the stock markets. Neil Fligstein posits that while the rise of large conglomerates from the mid1960s onwards can be described as an emergent “finance conception of the firm,” this institutional model gave way to a “shareholder value conception”24 in the 1980s. Firms’ strategies to maximize shareholder value are: dediversification, that is, divestment in unproductive product lines; coupling of manager compensation to stock price performance; repurchase of company stocks; the rise of the chief financial officer (CFO); and active management of markets’ earnings expectations (e.g., through investor relations departments). In contrast to economists’ rationalization of shareholder value (Jensen and Meckling 1976), sociologists describe its institutionalization as the outcome of social movements. Zorn et al. (2005: 269) identify three strategic actors: institutional investors, financial analysts, and hostile takeover. In analogy, Rao and Sivakumar (1999) show

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the effects of investor rights campaigns (mostly led by institutional investors) and increases in analyst coverage on the establishment of investor relations departments. One reason why analysts are important to this process is, according to Rao and Sivakumar (1999), because their metrics, frames, and stories substantiate the concept of shareholder value. Zuckerman (1999, 2000, 2004) goes further: he posits that shareholder value is institutionalized by observational relationships which position different actors as financial candidates, critics, and audiences (Zuckerman 1999). As audiences, investors draw on analysts (critics) to learn about socially legitimated valuations, providing the “consideration sets” for rational choices; candidates (firms) address analysts because the latter function as interaction partners in aligning with market expectations and as “surrogate investors” whose recommendations can move markets. Zuckerman tests his proposition by asking what would happen if firms did not comply with the critics’ hegemonic valuation categories. As analyst coverage is organized according to industry classifications, Zuckerman reasons that firms unable to attract the attention of analysts who specialize within “their” industries would face an “illegitimacy discount,” measured as a firm’s excess value (according to sales and earnings) in relation to its share price. His results show that such a discount exists. In a subsequent article (2000), Zuckerman intervenes more directly in the shareholder value debate: he shows that, additional to variables such as economic performance and relatedness of firm divisions, an existing coverage mismatch between a firm and the analyst review network puts pressure on a firm to dediversify: Diversified firms contradict the dominant logic of valuation, which classifies firms by industry, and the division of labor among analysts, which rests on that categorization. As a result, such a corporation faces pressure to align its corporate identity with one that more readily fits its position in the analyst-review network. It is through such pressure by analysts to match the stock market’s industry-based product categories that investors exert control over the corporation. (Zuckerman 2000: 613)

Zuckerman’s work, completed by an article on the effects of analyst “coverage incoherence” on the volatility and trading volume of a stock (2004), provides the argument that market “efficiency,” as theorized by Eugene Fama, is in fact conditional upon an institutional fit between a firm’s identity and hegemonic financial categories.

Concluding remarks Despite the discussed contributions to histories, practices, professionalization, and financial market capitalism, the sociology of analysts, much like the sociology of finance, has hardly exhausted its potential. Generally speaking, there is evidence of the growing relevance of continued work in this area: the Bureau of Labor Statistics (BLS) (2009) projects that by 2018 the number of financial analysts will have increased by 20 percent to 300,000 in the US alone, and it concludes that the primary factors driving an

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expansion of financial expert work are increasing complexity, global diversification of investments, and growth in the overall amount of assets under management. More specifically, I see the following empirical and theoretical shortcomings: first, we need to go beyond general concepts of “framing” and “classification” in substantializing analysts’ knowledge practices. For instance, more in-depth studies are needed which explore analysis as a market expert practice, considering the affectivity and reflexivity of markets as well as the temporal and “proxy” character of the ground data. Unexplored sites of analyst work are rating agencies, hedge funds, or online retail brokerages; within these different contexts, how are analysts involved in evaluations (MacKenzie 2011), valuations, and the development of investment strategies (e.g., trading algorithms)? Second, while “professionalism” and “status hierarchy” appear to be relevant concepts for theorizing analysts’ internal organization as well as their relations to clients, these concepts to date merely serve as heuristics. For instance, the sociology of professions and experts has not been systematically related to the study of analysts. Third, our knowledge of analysts as agents of financialization is poor. Existing relevant studies define a point of departure but do not account for changes,25 sustained ambiguities,26 and practical instances27 of establishing hegemonic value categories.

Notes 1. I am grateful to Karin Knorr Cetina and Alex Preda for critiques of previous versions of this chapter. 2. According to the BLS, US financial analysts earned a median annual salary of $73,150 in 2008, with bonuses constituting a large part of total earnings. 3. For other continents, comparable data are not available. 4. Thomas Fortune’s (1810) An Epithome of the Stocks and Public Funds, Jules Regnault’s (1863) Chance Calculus and the Philosophy of the Stock Exchange (an early formulation of the random walk hypothesis), and Henri Lefevre’s (1870) Traité des valeurs mobilières et des opérations de bourse, placement et spéculation are all cases in point. 5. Two authors are particularly worth mentioning: William Armstrong and his Stocks and Stock-Jobbing at Wall Street (1848) and Thomas F. Woodlock’s (1895) The Anatomy of a Railroad Report, a precursor to industry analysis. 6. Benjamin Graham was not alone, though. Methods and concepts, including the idea of intrinsic value, had been developed by many practitioners. Therefore, it makes sense to speak of his Security Analysis (1934) as a synthesis: “Graham’s definition is, indeed, a culmination of the trends in investment thought during the previous 20 years and a synthesis of the traditional view and the ideas of the new investment professionals, forged after the 1929 debacle” (Butler 2006: 7). 7. Marmer writes: “In the dark ages of the distant past, the investment world of the individual was ruled by an ancient monster, the dinosaur, also known as the stockbroker” (Marmer 1996: 9). According to Marmer, fund management then emerged in the wake of the Employee Retirement Income Security Act (ERISA) of 1974, modern portfolio theory, and the computerization of finance. 8. Charles Smith distinguishes between “fundamentalists,” “insiders,” “cyclicist-chartists,” “traders,” “efficient market adherents,” and those following “transformational ideas.” He

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argues that each of these beliefs entails what can be called its own “basic ‘vision’ of the market” (1999: 14). One important classification system is the North American Industry Classification System (NAICS), which is the successor of the National Industry Classification (NIC). It is important to recognize, however, that Mars conducted his research in the 1990s when the stocks of companies without many or any earnings achieved high stock market prices. Analysts’ rationalization was that these companies had superior future earnings power, expressed in high P/E ratios. Transposition of high P/Es from one high-tech company to another was then a way to forecast high stock prices in the absence of significant earnings of the company concerned. “It was clear from participant observation . . . that analysts are aware of the consensus earnings forecasts, and it is also improbable that conversations with fund managers do not (implicitly, at least) reference the opinions of others” (Barker 1998: 10). Chambost provides the following illustrative quote by an analyst: “Everyone uses the consensus and everyone asks everyone else’s opinion, everyone copies the same models and so the consensus becomes a consensus of the consensus. The consensus becomes too consensual” (2010: 17). Edwards and Magee write: “There was nothing to do but wait and see—let the market in its own time and way state its own case” ([1949] 1966: 28). See especially the 1967 articles in Vol. 23, No. 6. As already noted, reflexivity is manifest in analysts’ study of the sociological conceptualization of professions (e,g, Carr-Saunders, Parsons, Prandy, Taeusch) and in comparisons with other professional groups (especially physicians and lawyers); it can be construed as a strategy of analyst organizations to reinforce professionalization through institutional imitation (DiMaggio and Powell [1983] 2004). On the issue of forecasting, the CFA Institute (2008: 85–6) notes that “superior analysts” can, despite weak form market efficiency, make profitable recommendations if they make estimates of company earnings that are both correct and different from consensus. “The Financial Industry Regulatory Authority (FINRA) is the main licensing organization for the securities industry. Depending on an individual’s work, different licenses may be required, although buy-side analysts are less likely to need licenses (. . .) Although not always required, certifications enhance professional standing and are recommended by employers” (BLS 2010). A problem of the CFA might also lie in its high standards: the pass rate has fallen from 90 percent during the first exams in 1963 (284 candidates) to less than 50 percent in 2008 (115,000 candidates). This “All American Research Team” is assembled through a poll. “The poll is based on a questionnaire sent to money managers and institutions that asks them to rank analysts on buy/sell recommendations, earnings forecasts, reports and overall service. By industry, analysts are ranked one, two and three, and runner-ups” (Crockett et al. 2003: 15). “Union Bank of Switzerland acquired PaineWebber; Salomon merged with Smith Barney, which was owned by Travelers Group, which then merged with Citicorp. These deals, and many more like them, blurred the traditional line between retail brokerages, such as Merrill Lynch and Dean Witter, which catered principally to the investing public, and investment banks, like Morgan Stanley and Goldman Sachs, which dealt primarily with corporations. The new all-purpose financial supermarkets that resulted from the merger wave, such as Citigroup, J. P. Morgan Chase, and Morgan Stanley Dean Witter, were, in the words of Paul Volcker, a former chairman of the Federal Reserve Board, ‘bundles of conflicts of interests’ ” (Cassidy 2003). While the Glass–Steagall Act, separating retail and

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investment banking, was de facto repealed in the 1980s (Swedberg 2005: 188), it was only officially abandoned in 1999. “Well-known analysts are considered to be an essential marketing tool for investment banks in the IPO market. For example, when bankers do not have an established relationship with a potential issuer, they often use Investor polls to promote their firm . . . Whereas analysts were little known in the past, some became media stars in the 1990s, reaching out to millions of investors via television and the internet and attaining celebrity status. The financial press dubbed the 1990s the ‘Age of the Analysts’ ” (Crockett et al. 2003: 15–6). Already early in the 1990s, The Wall Street Journal published a document circulating within Morgan Stanley which stated that “‘our objective is to adopt a policy, fully understood by the entire Firm, including the Research Department, that we do not make negative or controversial comments about our clients as a matter of sound business practice” (The Wall Street Journal, July 14, 1992). Sanford I. Weill reportedly claimed that research has no value except getting banking fees (Knorr Cetina 2011). To a colleague, Blodget had written that “part of the reason we didn’t highlight [the riskiness of a stock is] b/c we wanted to protect icg’s banking business” (Cassidy 2003). Jack Grubman was also known to be very close to the companies he covered, even participating in board meetings (Swedberg 2005: 189). This attitude is well expressed by Grubman himself, saying during a Business Week interview in 2000 that “what used to be a conflict has now become a synergy.” Consequently, the “Global Settlement” concluding Spitzer’s investigations in December 2002 (voluntarily) involved all major Wall Street banks and consisted of “series of reforms designed to insure the independence of research analysts, a ban on issuing I.P.O. stocks to corporate executives, and fines totalling $1.4 billion” (Cassidy 2003). Further measures were taken by the SEC and the federal government (Sarbanes–Oxley Act). Fligstein gives the following definition: “The shareholder value conception of the firm uses rhetoric that diagnoses the problems of firms in terms of ideas imported from agency theory. The key idea in the shareholder conception of the firm is that the only legitimate purpose of firms is to maximize shareholder value. The main indicator of whether or not management teams are maximizing shareholder value is the share price of the firm on the stock market” (2001: 148). Zuckerman himself writes: “The economy continuously undergoes a vast amount of change along a wide variety of dimensions. . . . That is, financial valuation takes place not in a closed system but in one that sustains repeated exogenous shocks that resist easy interpretation. Investors must repeatedly manage the uncertainty generated by events that defy the categories of existing models” (Zuckerman 1999: 1411). Moreover, because of the influence of other investors’ decisions on the price, “financial participants must closely monitor changes in prevailing theories of valuation” (Zuckerman 1999: 1411). Chambost (2010) gives some indications of how firms actively make use of analyst consensuses; Bhojraj et al. (2009) show that firms which manage short-term earnings expectations (by reducing discretionary spending) indeed suffer losses in the long run. Faust, Bahnmüller, and Fisecker (2010: 18) write: “Because . . . stock price movements cannot be unambiguously related to articulated valuations and expectations, observed, valuated and influenced companies still maintain degrees of interpretative freedom which are exploited both in investor relations communications and in controversies within the companies.” Consider Useem’s account of two analyst conferences where CEOs of large companies artfully combine the disclosure of company information to analysts and investors with the creation of strategic intransparencies (Useem 1996: 72–7).

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chapter 14

r ati ng agencies m artha p oon

Introduction Rating agencies are specialized companies that exist to produce and sell a type of information that plays an essential role in debt markets. This chapter gives a history of the rating industry. It will outline how, over a century and a half, commercially produced ratings have become an unavoidable market institution and the handmaiden of regulatory intervention. What is a rating? A rating is an evaluation issued by a third party to a credit transaction. In other words, a rating is not just any freestanding assessment of credit quality. It is an information product, a statement crafted by a commercial organization with the express purpose of being communicated outward. What distinguishes ratings from other forms of credit assessment is that they are designed to be transferred from an information provider to an operating body. By definition, then, ratings are produced through interfirm organization. That many of the major ratings providers—recognizable names such as Dun & Bradstreet, Standard & Poor (S&P), and Moody’s—are as old as the market for rating itself provides compelling evidence that the rise of ratings (circulating market standards) cannot be separated from the history of the rating business (specialized firms). Throughout history, ratings have been repeatedly adapted for different purposes. While many of the original agency names have persisted, it is important to recognize that the form, content, and utility of the credit ratings these agencies issue is not identical across all financial transactions. The infamous “AAA” may be the timeless ideogram of the ratings industry, but it is far from being a universal or static marker of credit quality. The process that produces those letters, what they signal to the investment community, and how they get incorporated into decision-making has been subject to change over time. (The changes discussed here are summarized at the end of the chapter in Table 14.1.)

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The diversity of ways in which ratings have been used has been virtually unacknowledged in both political and academic discussions about their role in contemporary financial markets. In particular, attention should be paid to the growing tension in the industry between reporting (providing information) and analysis (information with a business decision built into it). If there is a take-home message of this chapter, then, it is that before leaping to conclusions about how to “fix” the ratings industry it is necessary to examine how the purpose of this information has evolved.

Before rating there was mercantile reporting Credit rating is an offshoot of nineteenth-century credit reporting. The Mercantile Agency founded by Lewis Tappan in 1841 was the most prominent of these companies.1 (It was absorbed into Dun & Bradstreet which continues to exist today.2) As the name suggests, the original purpose of credit reporting was to facilitate mercantile exchange— trade credit, not cash lending. In the words of historian Rowena Olegario, “Mercantile credit was not the loan of money but, rather, the advancement of goods to a buyer in exchange for the promise to pay at some future date” (Olegario 2006: 1). Credit reporting was first developed for mercantile exchange because trade credit was “unsecured.” This means that, legally, the claims of traders “ranked behind those of banks and other secured lenders and were among the last to be paid in the event of legal proceedings” (2006: 9). In conditions of rampant failure—figures suggest that in the nineteenth century at least 60 percent of businesses collapsed (2006: 36–7)—it was tremendously important to select one’s trading partners carefully from the get-go. It makes sense, then, that credit reporting should predate the financial intermediation of commercial channels by banks. Credit reporting supplanted older methods of credit assessment. Olegario explains that “In overseas trade where personal knowledge of buyers was frequently not possible, kinship and religious ties—Quakers, Hugenots and Jews, for example” (2006: 32)—were exploited as a means of assessing trading partners to minimize the risk of a sour transaction. It is, of course, precisely these kinds of closed social networks that must to be surmounted for more open markets to emerge. The British, for example, had devised trade societies to distribute information among those engaged in a similar type of trade. In these societies members were not related and did not trade with one another. In 1852, the London Times reported that mercantile agencies were an intriguing novelty found exclusively in the US. Unlike British trade societies, the American agencies were “for profit organizations” (Olegario 2006: 45). Even though merchants had been doing their own credit investigations, it had not been the normal course of business to

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record or distribute the findings. This fact alone marked an important innovation. Historian Scott Sandage remarks that “Credit agents got no direct use from recording other people’s business; they wrote for the market, and clients bought the product for its usefulness” (Sandage 2005: 143). Credit reporters inserted a systematic process into trading that fixed, reproduced, and transmitted data to paying market participants. In the offices of the Mercantile Agency “[t]housands of words about dozens of men” (Sandage 2005: 102) were handwritten into leather-bound 11-by-17 inch folio pages. It was through the concentrated efforts of these specialized operations that “[t]he marketplace now had a memory, an archive for permanent records of entire careers” (2005: 102). This is how mercantile trading underwent the shift from memory to written record (Clanchy 1993)—through the rise of secondparty information bureaucracies.3

From written ledgers to published ratings Credit reporting ranks among the multiple genres of writing and documentation that were developed in the nineteenth century to support increasing financial activity (Poovey 2008). Like bond certificates, shipping lists, and financial newspapers, credit reports were a particular format of writing tailored to mediate economic exchange. Reporting was a narrative device that inscribed the reasons for success and failure in business into the biographies of individual men. As the repositories for individuals’ stories, bureaucracies “such as credit-rating agencies, bankruptcy courts, and charity bureaus added their own form of discipline to that of the marketplace” (Sandage 2005: 9). The Mercantile Agency amassed its content by drawing on a network of correspondents who sent letters to local offices that in turn forwarded them onto the main office in New York.4 Correspondents, who worked for free, included “sheriffs, merchants, postmasters, and bank cashiers” (Olegario 2006: 49), although it was generally attorneys who were the largest contributors given their “central position in the commercial life of towns and localities” (2006: 49). Abraham Lincoln was himself at one point a correspondent. As Sandage observes, “More than a bank balance or a character reference, a credit report folded morals, talents, finances, past performance, and future potential into one summary judgment” (2005: 103).5 The material labor and organizational process involved in generating early credit reports was considerable. The following eyewitness account of the Mercantile Agency’s central New York office was recorded in 1851: “Upwards of thirty men are constantly occupied in the details of this office alone, condensing, copying, and giving out reports, carrying on the correspondence, &c., &c. Their records are contained in more than

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100 books, of the size of the largest leger [sic], extending to 600 and 700 pages each” (reported in Lauer 2008: 310). As one business writer remarked in the 1940s, “Lewis Tappan . . . was first to apply the principles of mass production to credit-reporting” (Lauer 2008: 308). Like a library, mercantile reports were heavy infrastructure. Subscribers were initially required to consult centralized handwritten ledgers in person. The agencies were reluctant to circulate printed summaries for fear of libel suits as well as of having their content poached by competitors. According to Olegario, intense competition to attract more clients in the 1850s put pressure on the agencies to resort to printed reference books, a first step toward condensing credit information into a more mobile format. The first edition evolved from a few printed loose-leaf sheets to become a “mammoth rededged quarto volume known as Bradstreet’s Reports” (Sandage 2005: 128). The “red book,” as it was known in the vernacular, was soon a recognizable fixture in trading offices across the country. It is of particular historical note that the first appearance of a rating scale coincides with the advent of printed manuals. “In 1857,” writes Olegario, pointing to the earliest circulating volumes, “Bradstreet began publishing a bound reference book that contained information, presented in the form of rating keys” (2006: 65). She indicates that the original purpose of the rating scheme was to package the content of lengthy texts more compactly into print copies.6 This suggests that although the rating key may have “allowed subscribers to compare potential borrowers more easily” this was merely a side effect of having introduced a more competitive printed format of product presentation into the credit reporting industry. (For an explanation of the cognitive effects of rating, see Carruthers and Cohen 2009.) Credit reporting was an organizational machine whose single-minded purpose was to dramatically amplify the amount of information available to traders. While the records did proffer analysis and voice opinion, the agencies were not in the business of drawing conclusions about the practical meaning of their information for trading. To be sure, presenting information in the form of ratings narrowed the interpretive gap between transmitting information and the act of decision-making. Nonetheless, the introduction of letter ratings did not signal a conscientious strategic shift in the agencies’ business model toward business analysis. The fundamental proposition of mercantile agencies was strictly to report. In stark contrast to the ratings agencies of today, reporting agencies were initially quite removed from how information was being converted into business transactions. The intellectual work of deciding how to act upon credit reports from a business perspective remained squarely at the discretion of agency clients—experienced business operators with specialized operating skills. The current confusion over who is responsible when a triple-A-rated investment goes bad—the raters that vetted the investment structure, the investors who took the rating at face value, or the regulator that required it—is a relatively recent development. How these ambiguities have emerged is a story this chapter will now unravel.

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Origins of the bond rating agencies To continue the story of ratings we now shift from trading goods to bond issuance.7 Standard & Poor’s and Moody’s, the predecessors of the firms that have become the most prominent bond rating agencies today, were originally established to provide published compendiums of information to investors about different companies. The earliest initiative was launched by Henry Varnum Poor,8 whose History of the Railroads and Canals of the United States (1860) sought to present “a comprehensive statement of the progress, cost, revenues, expenditures, and financial condition” (Poor 1860) of US railway and canal companies. This was by far the most capital-intensive industrial sector in the late 1800s. Like the mercantile reports before them, reports on stock and bond issuing companies circulated as thick reference manuals. The history of these publishing houses is similarly marked by intense competition for subscriptions followed by important mergers between rival firms.9 Among the names that survive today, John Moody released Moody’s Manual of Industrial and Miscellaneous Securities in 1900 to provide “information and statistics on stocks and bonds of financial institutions, government agencies, manufacturing, mining, utilities, and food companies”10 (Moody’s Analytics Inc. 2011); Luther Lee Blake founded the Standard Statistics Bureau in 1906 which issued 5-by-7 cards with information on industrials; and John Knowles Fitch published The Fitch Stock and Bond Manual in 1913. With bond rating, “publishing houses” morphed into “statistical corporations” (The Wall Street Journal 1931). It is important to recognize that the term “statistics” referred to descriptive data on companies, and not to probabilistic predictions of their performance (i.e., statements of risk). In 1909 Moody published Analysis of Railroad Investments in which he introduced a rating schema modeled after R. G. Dun & Company (Sinclair 2005: 24). (Since Henry Poor’s wife was Tappan’s niece (Chandler 1956: 24), it seems quite likely that Poor’s also adopted the scale from mercantile reporting.) Interagency imitation led to isomorphism in ratings, such that “By 1930, it was possible to match each agency’s rating symbols onefor-one with each of the other agency’s symbols” (Partnoy 2006: 642). Political economist Timothy Sinclair links the spread of the rating scale with the arrival of business decision-making at the bond rating agencies. According to him, “The transition between issuing compendiums of information and actually making judgments about the creditworthiness of debtors occurred between the 1907 financial crisis and the Pujo hearings of 1912” (Sinclair 2005: 24).11 The immediate effect of introducing letter grades on the profitability of the bond rating business as well as on the liquidity of the bond markets is unclear. This is perhaps because “most bond issues during the 1930s were not rated until after they were distributed” (Partnoy 1999: 643). Flandreau, Gaillard, and Packer (2009: 7) note that “some of the investment trusts created during the 1920s used ratings to provide investors with reassurance on the solidity of their portfolio.” This suggests that ratings were not originally used for trading bonds, but were used for justifying book value. This use of ratings

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among institutional investors in the early twentieth century is the backdrop against which to assess the impact of regulation in fixing a permanent role in market for the agencies.

In the interwar period regulators adopt ratings to demarcate prudent investments In 1931, the Office of the Comptroller of the Currency (OCC) “pioneered the regulatory use of ratings.” The OCC created “the distinction between investment- and non-investmentgrade securities when it ruled that, while bonds rated BBB or better were to be carried at book value by banks, lower-rated bonds had to be written down to market value and 50 percent of the resulting losses were to be charged against capital” (Adams, Mathieson, and Schinasi 1999: 200). The front-page explanation for the decision in The Wall Street Journal was that “state, municipal and government bonds and issues given the four highest ratings by statistical corporations did not have their intrinsic value impaired by market fluctuations” (The Wall Street Journal 1931). Through regulation, financial accounting became intertwined with the open market for commercial ratings. In the wake of the 1929 crash, regulators latched onto young information conventions to establish and communicate a threshold of prudence that might stabilize investor activity. In 1936, the OCC and the Federal Reserve Board (FRB) extended the use of ratings to define and enforce prudent investment as they “prohibited banks from holding bonds not rated investment grade by at least two agencies” (Adams, Mathieson, and Schinasi 1999: 200). In Rule 2a–7 of the Investment Company Act of 1940 (Pub. L. 76–768), which limited money-market funds to “eligible securities” demarcated by ratings, the government deepened its reliance on ratings to protect investors. (Ratings have also been used to create regulatory exceptions. Rule 3a–7 of the Investment Company Act added in 1992, exempts structured-finance vehicles that meet a set of requirements—which include having received one of the four highest ratings from an NRSRO (nationally recognized statistical rating organization)—from the Act.) Regulating investment quality through privately produced ratings established a symbiosis between the Federal government and an independent information industry. In passing thorough gradations that were already being used to communicate value to investors, the state demarcated a criterion of prudence without imposing an exogenous bureaucratic definition of what constituted a sound investment upon the markets. Working through commercial ratings, the government regulators were able to exert control without curtailing the established practices of financial decision-makers. The result was a curious contradiction—the regulation respected the principle of market

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freedom, while simultaneously assuring that agents would draw similar conclusions about the desirability of investment options.

The SEC ties net capital requirements to ratings By the late 1960s the concerns about financial prudence were sliding into questions about operating control in financial markets. Prudence treats the quality of investments while operating control has to do with the ability of the market to execute a transaction in an orderly fashion. A “Paperwork Crisis” occurred on the exchanges when the volume of trading at the exchanges increased beyond the capacity of manual bookkeeping. The event “brought to light and exacerbated other structural problems inherent in the industry” (H.R. Doc. No. 231 1971), including “the lack of adequate and permanent capital” resting in the system (Molinari and Kibler 1983–4: 10). Concern about overall liquidity in the financial system was exacerbated in 1970, when the Penn Central Transportation Co., in what was then the biggest collapse in US corporate history, found itself unable to refinance its short-term loans (TIME magazine 1970). “[L]ike many others in the market at the time” the defaulted bonds “had not been rated by any of the credit rating agencies” (CGA 2002). Shockwaves rippled through the markets for commercial paper, upsetting the primary holders of these debts—not banks but other companies. Several broker-dealers (agents that sell and trade securities both on behalf of clients and from their own accounts) imploded. As worries about the liquidity (whether the entities that traded bonds were retaining large enough capital reserves) collided with questions about the overall state of corporate creditworthiness (the ability of companies to pay back the bond obligations being traded), the SEC (US Securities and Exchange Commission) decided to adopt more stringent net capital requirements for broker-dealers. Rule 15c3 (1975), which requires a broker-dealer to keep a cushion of capital in reserve to ensure it can pay all of its obligations even if there is a delay in liquidating assets, was modeled after the cornerstone of financial rules designed by the New York Stock Exchange (NYSE). The NYSE’s standards were stricter than the original Federal rules established in the 1940s (Wolfson and Guttman 1972: 603).12 The SEC’s new Rule 15c3–1 yoked minimum net capital requirements “to the quality of the bonds of the broker-dealers’ portfolios” (White 2002–3: 40) within Federal law. Up to this moment, the SEC had been calculating capital reserves as a flat percentage of net capital or had stated it as a fixed dollar requirement. In contrast, under the “haircut rule” broker-dealers were allowed to take smaller discounts (a lower percentage of the market value) on assets in the highest ratings grades. In a subtle but very important shift, tying capital requirements to ratings established a novel regulatory regime in which reserves were linked to asset quality (grade or risk level) rather than asset volume (amount).

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Critics have noted that “the levels of net liquid assets required under the net capital rule appear arbitrary since there is no demonstrable statistical logic to the levels chosen” (Molinari and Kibler 1983–4: 22). Indeed, the requirements were expressed as simple percentages depending on the ratings grades following more or less the interpretation of ratings made by the OCC in the 1930s. Nonetheless, this conceptual shift is critical to the rise of structured finance (the consequences of which are discussed in the last section of the chapter), in which, in order to produce products that require lower capital reserves, products are engineered to meet the quality requirements that correspond to the desired rating. The appeal of investing in highly rated structured securities comes not only from the rating’s assessment of their superior quality but also from the lower regulatory requirements on capital that follow suit (Tett 2009).

The business model of ratings changes with the introduction of NRSROs The changes to the rating industry wrought by Regulation 15c3 did not stop at the way ratings were tied into capital requirements. The haircut rule also overturned the subscriber-pays business model of the ratings industry. In the subscriber model, investors shopped among competitive providers whose reputations for a high-quality product were constantly being tested. Free markets meant that the agencies must serve the financial world in open competition through product innovation and differentiation. Once ratings were entrenched in Federal regulations, however, policing could not be left up to the very market participants that were supposed to be submitting to regulatory control. Having relied on ratings to express the legislation the SEC found itself in a peculiar dilemma. If the purpose of regulating through ratings was to avoid imposing a restrictive definition of financial quality on the markets, the challenge was to identify acceptable ratings scales for the purposes of legal administration while also allowing the ultimate utility of the information to be sorted out by the investors themselves.13 In other words, the SEC had to enforce oversight of the agencies, without meddling in methodology. To solve this problem the SEC “established an entirely new regulatory category for bond rating firms—‘nationally recognized statistical rating organizations’ (NRSROs)” (White 2002–3: 40). Instead of defining how to do regulatory rating, the state defined which institutions could do it for them. The SEC handed the NRSRO designation to a select number of ratings firms. As critics have noted, “it neither defined the term nor indicated which agencies qualified” (Partnoy 2006: 64). Instead, it issued a “no action” letter to a handful of players indicating that the Commission’s staff “would take no enforcement action if ratings from these agencies were used to satisfy the requirements of Rule 15c3–1” (Sinclair 2005: 44). Moody’s, S&P, and Fitch were not the only firms designated, but by the end of 2000 a

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wave of mergers had “removed all of the entrants from the field” such that “only the three grandfathered incumbents” were left. (There are currently ten NRSROs.) NRSROs constitute a private ordering of public markets. As legal scholar Steven Schwartz explains, the designation ensures “that where the applicability of specific laws turns on a rating, the issuer of the rating—and thus the rating itself—is a reliable indicator of whether or not to apply those laws” (Schwartz 2002: 21). In addition to providing information to investors like other credit reporting agencies (CRAs), NRSROs also act as gatekeepers that dole out “regulatory licenses” (Partnoy 2006). It is in the interests of issuers to seek the “Good Housekeeping Seal of Approval” that NRSRO ratings provide if they want their financial products to be traded by entities operating under regulatory control. Thus, the stature of the ratings business in markets is as bound up in regulatory demarcation as it is in providing independent credit assessment. Regulation redefined the business of bond rating. As the subscription-based model of ratings established in the mid-1800s was undermined by the invention of the photocopier, it was replaced by a system in which the issuer instead of the subscriber would now pay. This is the model we know today, in which “roughly 90 percent of credit rating agencies’ revenues are from issuer fees” (Partnoy 2006: 62). Most ratings pertain to debt securities, but in a few cases ratings are required to assess a project’s eligibility for flows of government funding in areas as diverse as education, telecommunications, and transportation. By 2002, “at least eight federal statues and 47 federal regulations, along with over 100 state laws and regulations, reference[d] NRSRO ratings as a benchmark” (CGA 2002: 79). The use of ratings to express government policy explains why the most extensive discussion of the ratings industry to date is found in legal scholarship, and not in finance or economics.

The NRSROs become political superpowers In 1968, New York City’s finance administrator, Roy M. Goodman, appeared before Congress to “discuss the astonishing and little-understood impact of bond rating upon the borrowing costs of municipalities” (1968: 59). “I touched off a national debate on bond rating,” he stated, “when I called for a comprehensive overhaul of the private municipal credit-rating system.” This is how, as one contemporary commentator remarked, in the late 1960s the “subject of municipal bond ratings, usually of interest mostly to bond market professionals” ended up “in the limelight”—“because the city of New York . . . put it there” (Packer 1968: 93). Municipal bond rating was not new in this period. An outgrowth of corporate bond ratings, Moody’s had begun rating municipalities in 1919, S&P in the late 1920s. The event that pressed Goodman to raise questions about the process, however, was the “New York City Rating Fiasco.” In 1965 Moody’s lowered New York City’s tax-secured

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bond rating one notch; a year later S&P followed suit. In consequence, an estimated ten basis points were added to the city’s interest costs. “Investors are so accustomed to the system” Goodman protested, “that almost automatically, a rating will determine within certain limits the interest rate the issuer must pay on its bonds” (1968: 60). The New York City fiasco drew attention to the conflicting position of ratings as the chosen mediator between the state and financial markets. Linking ratings to capital requirements in Federal law had been a measure to protect “investors”; however, linking ratings to interest payments on government bonds was costing “citizens” money. The first situation was about enforcing financial prudence for the benefit of a greater good, while the second was seen as infringing upon the smooth functioning of democratic politics. From the perspective of financial theory, both actions could be reconciled under the aegis of “risk management.” But from the perspective of a city administrator, the appeal to ratings was nothing more than a bad habit that was “causing leading cities to be short changed out of hundreds of millions of dollars in unwarranted interest charges vitally needed for basic services” (Goodman 1968: 59).14 Through ratings, the government has been confronted by an ambitious financial logic (grounded principles such as risk versus return), which was being propagated by the very instrument it elevated into a handmaiden of domestic legal administration.15 The growing concern is that through the ubiquitous exercise of their particular form of investment judgment, ratings have ended up implementing and enforcing a mode of financialized governance that is “more conducive to private interests and increasingly less subject to democratic intervention” (Goodman 1968: 50). What Goodman presaged was a growing tension between political stability and financial gain. He astutely identified the rating agencies as a critical location where this battle was fermenting. Surfing the tide of globalization, the rating model established in the US has since been exported the world over, and Goodman’s concerns have been extended to the international level. Political scientist Timothy Sinclair has dubbed rating agencies The New Masters of Capital (Sinclair 2005) because they define which entities—both corporate and government—can gain access to low-cost capital and which cannot. Sinclair also marks a less visible dimension of their influence. “Rating agencies and the ratings process,” he argues “provide a means for transmitting policy and managerial orthodoxy to widely scattered governments and corporations” (2005: 71). To survive in a financescape (Appadurai 1996) ruled by ratings, capital-dependent organizations must concede to accounting and managerial practices that implement a set of values characterizing a growing regime of financial control. The effect “on national policy autonomy” is an affront to state sovereignty, a breach that is only exacerbated in countries “where the rating agency is not domestically owned and controlled” (Sinclair 2005: 119). This balance of power was captured in Friedman’s infamous 1995 quip: “We live again in a two-superpower world. [. . .] The U.S. can destroy a country by leveling it with bombs; Moody’s can destroy a country by downgrading its bonds” (Friedman 1995). Friedman’s somber advice to politicians the world over: “Don’t mess with Moody’s.”

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Rating agencies get downgraded by financial scandal The spectacular collapse of Enron Corporation at the end of 2001 is a cultural landmark in US business history. Like Penn Central before it, the bankruptcy “triggered a crisis in investor confidence in U.S. capital markets” (CGA 2002: 1) and sparked an intensive examination of the entities responsible for corporate governance in the US. The rating agencies found themselves front and center in Washington’s roundup of negligent private sector watchdogs, next to Enron’s board of directors, Arthur Anderson (the auditor), and numerous Wall Street stock analysts who had doggedly recommended the energy giant’s inflated stock. Throughout 2002, raters—whose reputations had already been tarnished by their failure to anticipate massive defaults of Washington Public Power Supply System (1983) as well as of Orange County, California (1994)—would be further implicated in a spate of corporate collapses at WorldCom, Tyco, and Global Crossing. Public ire led to the passage of Sarbanes–Oxley, also known as the “Public Company Accounting Reform and Investor Protection Act of 2002” (Pub. L. 107–204, 116 Stat. 745), which President George W. Bush hailed as “the most far-reaching reforms of American business practices since the time of Franklin D. Roosevelt” (Bumiller 2002). Sarbanes–Oxley did not take any immediate action with regards to rating agencies. This suggests that the evidence of how they may have contributed to Enron’s massive corporate bankruptcy was not conclusive enough to inspire remedial legislation. Instead, the rating industry was submitted to several Congressional hearings, in which the process of rating came under heavy fire from investigators. The final staff report of the SEC coolly concluded that “the credit rating agencies displayed a disappointing lack of diligence in their coverage and assessment of [Enron]” (SEC 2003: 4). Rating agencies were berated for “their failure to uncover the extent of Enron’s weakening financial condition” (Borrus and McNamee 2002). The fact that “the agencies kept it at an investment-grade rating until just four days before it filed for bankruptcy” was prime evidence of profound shortcomings in their analytic process. Securities analysts working for investment banks wanting to attract Enron’s considerable business had had every incentive to remain heedlessly optimistic about the company’s prospects. But, as investigators pointedly noted, “though unhampered by the kind of conflicts faced by securities analysts at major Wall Street Firms, [credit-rating agencies had] similarly failed to warn the public of Enron’s precarious situation” (CGA 2002: 5). Muckrakers Bethany Mclean and Peter Elkind were more scathing in their conclusions, remarking that “Analysts are supposed to dive into a company’s financial documents, pore over the footnotes, get past management’s assurances—and even get past accounting obfuscation. Their job, in short, is to analyze” (McLean and Elkind 2004: 407). In fact, they noted, because the agencies are exempt from SEC Regulation FD (2000), which prevents companies from divulging material to some analysts but not

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others, “credit analysts had access to lots more information than the equity analysts” (McLean and Elkind 2004: 239). The laws are expressly configured so that “The analysts from Moody’s, S&P or Fitch can have private conversations with company management” as well as “see financial information . . . without the company disclosing it publicly” (CGA 2002: 82). A decade of escalating financial havoc has left critics fuming over the agencies’ record of blown calls. In response to a string of collapses, “expressions of concern about rating performance—how good the agencies are in their business—have become the norm” (Sinclair 2005: 154). The troubling inconsistency is that “credit ratings purport to provide investors with valuable information . . .; credit rating agencies seem to have impressive reputations,” and yet, observes Partnoy, “particularly since the mid-1970s, the informational value of credit ratings has plummeted” (Partnoy 1999: 621). It would seem that reputation alone, the market’s putative internal mechanism of quality control, is failing to keep the agencies in check (Hunt 2009a). The agencies respond by claiming that their analytic process is fundamentally sound (see Figure 14.1). They argue that “it was Enron’s lies that caused the problem” (McLean and Elkind 2004: 407). “We agree that Enron was a tragic situation,” testified Vicki Tillman, Executive Vice-president of Market Services at S&P, “But we were also victimized. . . . [T]he ratings agencies were purposefully deceived” (Serial No. 110–62 2007: 26). Where they once prided themselves on being the premier source of accurate information on borrowers, the ratings agencies now claim to be at the behest of the information

At the largest rating organizations there are 4 basic steps for developing an initial rating. A primary analyst (1) reviews financial statements of the issuer and drafts a preliminary rating; (2) visits the management team of the issuer; (3) prepares a brief report explaining the rationale for the rating; and (4) convenes a committee consisting of 4 to 12 people which includes the analyst, their Managing Director and other analysts, managers or staff members with useful expertise. The committee, whose identity and deliberations are kept confidential, reviews the case and collectively determines a final rating through a voting procedure. The rating and report are sent to the issuer so it can correct factual inaccuracies and remove confidential information. If an issuer objects to the rating it can make an appeal, but agencies claim that retractions are rare. The rating is disseminated to the public by press release and the report is made available to paid subscribers. Once a company has been rated, the rating is monitored by reconvening a committee once a year to once every 18 months. The primary analyst can also place a company on “watch” or “review” at any time which indicates to the markets that a change may be forthcoming. Sources: Report 109–326 2006: 84; S. Prt. 107–75 2002: 2–3

figure 14.1 The Process of Corporate and Municipal Credit Rating

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provided to them by issuers. Here is the admission that ratings agencies have changed their mandate—they no longer do independent reporting, their business is to provide the markets with analysis.

Reining in the ratings agencies A movement to rein in the agencies has been motivated by the simple political observation voiced by Senator Joseph Lieberman: “Power of this magnitude should go hand in hand with some accountability” (quoted in Borrus and McNamee 2002). The working assumption among regulators was that financial collapses would be avoided if only the industry would improve its ratings. “If history is a guide,” stated one report, “credit ratings agencies generally get it right: bonds rated AAA have less than one percent default rate over ten years or more, and S&P has found that there is almost an 88 percent likelihood that companies with ratings of A or above will still have that rating one year later” (Serial No. 110–62 2007: 26). The general diagnosis is that ensuring financial stability means improving the predictive accuracy of ratings. Current events suggest that the NRSROs have gotten sloppy in their analysis, or have failed to keep pace with the cutting-edge risk assessment techniques that smaller, lighter, newer players, who lack the Federal designation, have developed.16 Some blame regulation for creating artificial demand while giving the agencies a free ride: “Why not just abolish the agencies’ special status and let the market gauge creditworthiness?” (Borrus and McNamee 2002). The answer from a legal standpoint has been because “doing so would also leave capital regulators looking for a way to measure credit risk” (Hunt 2009b: 21). What is remarkable is that rather than honing in on corporate governance (the role ratings play in accounting and operations inside firms) government investigators harkened back to the historic role of ratings as facilitators of credit transactions. According to investigators the purpose of the rating industry was to “rate the creditworthiness of entities, such as public companies, and the debt they issue, so that those wishing to extend credit . . . can better understand the risk that they may not see a return on that investment” (CGA 2002: 76). The strategy to induce the desired improvements is to increase oversight and modify incentives. Some newer initiatives seek to make the agencies put their own skin in the game. In 2006, Congress passed the Credit Rating Agency Reform Act (Pub. L. No. 109–291. 120 Stat. 1327). The Act increased competition in the industry by formalizing the process of applying for NRSRO status (i.e., by listing the 20 largest securities issuers and subscribers and ten qualified institutional buyers (QIBs) that have used the ratings for at least three years); it increased transparency by requiring each NRSRO to prepare written policies for how they would prevent the misuse of nonpublic information as well as manage conflicts of interest; and it tackled compliance by requiring that each NRSRO appoint an officer responsible for reporting to the SEC.17 Congress also curbed three

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practices deemed abusive: unsolicited ratings (issuing a rating to corner an entity into becoming a paying client);18 notching (in which a rater would give an asset-backed security a better rating if it had also rated most of the underlying assets); and bundling (tying ratings to additional services). The evidence that ratings are somehow responsible for financial volatility has only become more staggering in the decade following the Enron scandal despite the 2006 regulatory interventions. The case had barely been put to rest, when the global financial system as a whole nearly ground to a halt in 2008 as triple-A-rated tranches of US mortgage-backed securities, which filled the balance sheets of institutional investors around the world, disintegrated into a smoldering pile of toxic assets. The next installment in the story of ratings is being played out as regulators debate the changes introduced by the 2010 Dodd–Frank Act (Pub. L. 111–203, H.R. 4173).19

The paradox of structured finance Frustration has mounted with “The Geeks Who Rule the World.” “How can the same entities be all-powerful and strangely after-the-fact at the same time?” vents journalist Bethany McLean. “That is one of the more puzzling conundrums in today’s capital markets” (McLean 2001). History holds some of the answers. In a world of gentlemanly partnerships, ratings were summaries of descriptively accurate information that served as an aid to business decision-making. When the FRB first resorted to ratings in the 1930s they were using them to weight the “desirability” of a portfolio (Partnoy 2006: 687). Today’s markets refer to the same letter grades as though they are—or should be—precisely calculated statements that foretell of future events. Thus, over time, the original meaning of “rating” as an endorsement has collapsed with a technical conception of “risk” as a verifiable prediction. When inserted into the universe of computer-assisted, mathematically inclined quants,20 ratings are treated as though they are statements that indicate whether a country, company, or security will eventually collapse into default. This is in stark contrast with the original, descriptive purpose of credit reporting. Just as a portrait in a gallery freezes an impression of a person yet reveals nothing about how they turned out 20 years later, to describe and to predict are not equivalent endeavors. The conflicting expectation of ratings manifests itself most clearly in debates about whether the agencies can be held liable when poor outcomes follow from strong ratings. A residual of their early history, the “NRSROs have long argued that their core activities are purely journalistic pursuits: gathering information on matters of public concern, analyzing the information, forming opinions about it, and then broadly disseminating those opinions to the public” (Partnoy 2006: 84). If agencies are financial publishers, that is, members of the press, then ratings are “the word’s shortest editorials.” They are “opinions, published in letter form” (Husisian 1989–90: 454).

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The most obvious if oblique indication that rating agencies are not old-fashioned publishers comes from the exponential growth of their revenue. While other formats of print media are in decline, the industry has enjoyed profit margins higher than Exxon and Microsoft, and an operating margin in the recent boom that averaged 53 percent (Morgenson 2008). Chairman of the Financial Crisis Inquiry Committee (FCIC), Phil Angelides, disapprovingly noted that between 1998 and 2007 “Moody’s revenues from rating complex financial instruments like mortgage securities grew by a whopping 523 percent.” “From 2000 to its peak in 2007,” he underscored, “the company stock price climbed more than six-fold” (FCIC 2010). Dig deeper, and the evidence that ratings are no longer just opinion-makers only gets more convincing. “In their traditional role of rating and writing for their subscribers about all debt securities offered and traded publicly, the rating agencies may have acted as members of the press,” concede lawyers writing for Bloomberg Law Reports. “But in rating structured securities like CDOs,” the report continues, “which the agencies normally rate only for a fee, often participate in the structure of, and which are usually sold and traded privately, the reverse is true: the rating agencies are not journalists gathering information and reporting to the public, but rather participants in the transactions that they rate” (Grais and Katsiris 2007: 4). During the Enron debacle agencies were reprimanded for not delving deeply enough in the company’s financials. “In order to do their jobs,” stated officials, “analysts must have regular, meaningful contact with the companies they cover” (CGA 2002: 69). The agencies now stand accused of exactly the opposite sin: of engaging in too much contact with issuers, of colluding with investment bankers to pump out complexly structured securities. And because “rating agencies can benefit from active capital markets without having to risk any of their own capital” (CGA 2002: 106), during the financial bubble their fortunes soared. The issue, then, is not that the objectivity ratings has been distorted by conflicts of interest (Sinclair 2010), but rather that agencies act as financial engineers to guide the design and assembly of products with capital structures, cash-flow projections, and, indeed, ratings, that make them attractive to investors. While ratings were originally used to “assess and grade the creditworthiness of companies and public entities that issue debt,” in a separate type of analysis agencies now also rate “the debt itself ” (Borrus and McNamee 2002). The startling paradox is that with the rise of structured finance, ratings that are incorrect from the point of view of prediction do not stymie financial action; on the contrary, they can produce roaring (if volatile) financial innovation. To catalyze financial production, rating information has to be stable, but it does not have to be “right.” Enron is a case in point. A strong credit rating ensured the company’s access to the steady flow of capital that allowed it to grow increasingly leveraged without defaulting. As Greg Whalley, head of Enron’s trading operation, wryly noted, the company’s “business model [did not] exist below investment grade” (quoted in McLean and Elkind 2004: 236). This is why Enron collapsed only after its rating was downgraded, a move that triggered $3.9 billion in collateral requirements and repayments, and sent the company hurling into a spiral of decreasing liquidity.

Table 14.1 Timeline summarizing the major events in the history of the ratings industry 1841 1857 1860 1909 1919 1931 1940 1968 1975 1975 1970s 2001 2006 2010

Mercantile Agency—For-profit credit reporting provides access to handwritten information to subscribers so they can select (long-distance) trading partners. Bradstreet rating scale—The rating scale is invented to compress credit information into published volumes that increase circulation. Poor’s railway manual—Poor begins compiling and publishing descriptive information about railway companies in thick manuals for investors. Moody’s bond rating—Moody’s adopts the rating scale from mercantile reporting and applies it to bond rating. The ratings are used to justify book value. Government bond rating—Bond rating agencies begin rating state and municipal bonds. OCC investment grade—The OCC adopts ratings from institutional investors to set and communicate prudent investment standards. Investment Company Act—Rule 2a–7 limits money-market funds to “eligible securities” demarcated by ratings. New York City Rating Fiasco—Moody’s lowers New York City’s tax-secured bond rating one notch; a year later S&P follows suit. SEC net capital requirements—To increase liquidity and operating reserves for broker-dealers the SEC ties ratings to capital requirements. NRSROs—The SEC identifies the agencies whose ratings will trigger “no action” if used to comply with securities law. This is an institutional solution to regulatory oversight. Structured finance—Predictive modeling techniques enabled by computers allow issuers to design and build securities that meet regulatory benchmarks. Enron collapse—The agencies come under fire with the eruption of a string of bankruptcies at the turn of the century, the most spectacular of which is the energy giant. Credit Rating Agency Reform Act—In response to Enron, the government seeks to increase competition, transparency, and compliance in the rating industry. Dodd–Frank Act—In response to the 2008 credit crisis, Dodd–Frank proposes to remove statutory reference to credit ratings from specified statutes by 2012.

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In debt structuring, ratings are not a reflection of creditworthiness. Instead, they constitute the baseline conditions—benchmarked in securities law—that financial engineering seeks to meet. In the hands of financial engineers, ratings serve not as an independent check on lending, but as a cornerstone for innovating financially attractive products. This is why in 2008, as one investment banker testified, “the blow-up is not confined to one company or security, but an entire asset class of structured finance” (Serial No. 110–62 2007: 9).21 Commercially produced ratings are the raw fuel of financial productivity. The more ratings the agencies issue, the greater the potential the capital markets will overheat. This brief overview of the history demonstrates that a great deal has changed since the rating industry got started. Simply put, with the rise of structured finance, the ratings agencies of today “face pressures that did not exist when John Moody was rating railroads” (Lowenstein 2008).

Notes 1. In addition to the editors, the author wishes to acknowledge the thoughtful assistance of Mary Poovey, Benjamin Taupin, Robert Wosnitzer, and especially Natalia Besedovsky. 2. According to Gilbert Harold, the seed for the credit reporting agencies was the credit information the Tappans, dry goods and silk merchants, had started keeping on their own customer base (Harold 1938). 3. The archive of R. G. Dun & Co. has been preserved at the Baker Library at Harvard Business School. 4. Scholarship in economics treats rating agencies as the result of disintermediation in which a function formerly carried out within separate firms is excised to save cost through economies of scale. This approach seems to ignore the qualitative difference between two modes of information-keeping: one in which the quality of internal data (often managed informally) is a source of competitive advantage that closes a market to newcomers, and the other, in which there is a collective benefit to centralized records that enhance trading activity but equalize business opportunity. 5. For an account of how difficult it is to organize flows of data from all corners of the US to a central administrator see Emmanuel Didier’s (2009) detailed account of US Federal authorities’ efforts to produce the statistics that were necessary to implement New Deal policies in the post-Depression era. 6. Olegario claims that creditors will not discriminate based on social type, if they are given access to transparent financial factors such as repayment histories and capital strength. The teleological slant of this argument should be treated with caution because it unwittingly trivializes discrimination as a temporary deviation that is all too easily dispelled by the unfolding of informed competitive markets. Yet, in the nineteenth century, being attentive to social hierarchy was hardly an accident of history—it was a primary socializing force. 7. Compression and conversion imply that information can—at least in theory—be decompressed and/or reconstituted with minimal distortion of the original form. Ratings do not compress or convert information, they permanently reduce it.

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8. Against the backdrop of the history of bonds, the business of bond rating is relatively new. The bond format of lending originated in Italy in the 1400s so that the state could borrow from its own citizens to fund wars. The instrument was later used to fund the exploits of colonial trading companies such that the first bond exchange was established in Amsterdam by the state-chartered Dutch East India Company in 1602 (Ferguson 2008). 9. Henry Varnum Poor was the great-grandfather of noted business historian Alfred Chandler. For a detailed biography see Chandler (1956). 10. For a summary of historical mergers and acquisitions in the ratings industry see Sinclair (2005). 11. A history of Moody’s can be found at . 12. The Pujo hearings were a Congressional subcommittee to investigate whether the concentration of control over US banking in the hands of a few financiers was the result of a “money trust,” an illegal agreement to form a cartel. 13. The original Federal rules established on October 29, 1942, “exempted from its provisions the members of certain exchanges whose capital requirements were ‘more comprehensive’ than those imposed by the [SEC’s] rule” (Wolfson and Guttman 1972: 606). 14. Sub-point 1.6 of a proposed Code of Standard Practices for Participants in the Credit Rating Process prepared by the Association of Corporate Treasurers (UK), the Association for Financial Professionals (US), and the Association Française Des Trésoriers d’Entreprise (France) states that “Regulators should not prescribe methodologies that CRAs may use, but require that each CRA document and adhere to its chosen, published methodologies, while recognizing that many judgements are involved in arriving at ratings other than purely statistical ratings” (Serial No. 108–111 2004). 15. One of Goodman’s main objections was that the rating agencies did not have the resources to thoroughly examine each municipality (Packer 1968). 16. The same argument can be made with regards to consumer credit risk ratings (see Poon 2011). 17. According to regulators, the SEC process of NRSRO registration is “a transparent and voluntary registration system that favors no particular business model, thus encouraging purely statistical models to compete with the qualitative models of the dominant rating agencies and investor subscription-based models to compete with fee-based models” (Credit Rating Agency Reform Act of 2006 (Report 109–326), U. S. S., 109th Congress). 18. For an analysis of how the rating agencies justify themselves on each of these issues see Taupin (2010). 19. The practice of unsolicited rating was originally used to combat “competitive laxity” by providing checks on solicited ratings. The practice became controversial when it was seen as a strong-arm tactic for forcing new business relationships. For a detailed case see Klein (2004). 20. Dodd–Frank proposes to remove statutory reference to credit ratings from specified statutes and to replace them with standards of creditworthiness prescribed by the appropriate regulator by 2012. 21. The term “quant” refers to financial engineers, many of who were trained in theoretical physics, who first entered Wall Street in the 1970s. For a biography that tells their story see Derman (2004). 22. For a more technical account of how structured securities get rated see MacKenzie (2010).

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Plattner, S. (1996). High Art Down Home: An Economic Ethnography of a Local Art Market. Chicago: Chicago University Press. Pogrebin, R. and Flynn, K. (2011). “Does Money Grow on Art Market Trees? Not for Everyone.” The New York Times, May 31: C1. Preda, A. (2006). “Socio-Technical Agency in Financial Markets: The Case of the Stock Ticker.” Social Studies of Science, 36/5: 753–82. ——— (2009). Framing Finance: The Boundaries of Markets and Modern Capitalism. Chicago: University of Chicago Press. Ralevski, O. (2008). “Hedging the Art Market: Creating Art Derivatives.” Working Paper. (accessed November 22, 2009). Renneboog, L. and Spaenjers, C. (Forthcoming). “Buying Beauty: On Prices and Returns in the Art Market.” Working Paper Management Science. Sassen, S. (2001). The Global City: New York, London, Tokyo. Princeton, NJ: Princeton University Press. Smith, C. W. (2007). “Markets as Definitional Practices.” Canadian Journal of Sociology, 32/1: 1–39. Star, S. L. and Griesemer, J. R. (1989). “Institutional Ecology, ‘Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907–39.” Social Studies of Science, 19/3: 387–420. Stark, D. (2009). The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton, NJ: Princeton University Press. ——— and Beunza, D. (2004). “Tools of the Trade: The Socio-Technology of Arbitrage in a Wall Street Trading Room.” Industrial and Corporate Change, 13/2: 369–400. Storper, M. and Venables, A. J. (2004). “Buzz: Face-to-Face Contact and the Urban Economy.” Journal of Economic Geography, 4/4: 351–70. Velthuis, O. (2003). “Symbolic Meanings of Prices: Constructing the Value of Contemporary Art in Amsterdam and New York Galleries.” Theory & Society, 31: 181–215. ——— (2005). Talking Prices: Symbolic Meanings of Prices on the Market for Contemporary Art. Princeton, NJ: Princeton University Press. ——— (2008). “Accounting for Taste.” Artforum, 46: 305–9. Wakin, D. (2009). “The Met Offers Chagalls as Collateral.” The New York Times, March 4: C3. (accessed July 27, 2011). Watson, P. (1992). From Manet to Manhattan. New York: Random House. Wolfe, T. (2007). “The Pirate Pose.” Portfolio Magazine, April 16. < http://www.portfolio.com/ executives/features/2007/04/16/The-Pirate-Pose/>, (accessed April 4, 2012). Zaloom, C. (2003). “Ambiguous Numbers: Trading Technologies and Interpretation in Financial Markets.” American Ethnologist, 30/2: 258–72. Zelizer, V. A. (2000). “The Purchase of Intimacy.” Law & Social Inquiry, 25/3: 817–48. ——— (2004). “Circuits of Commerce,” in J. Alexander, G. T. Marx, and C. Williams (eds.), Self, Social Structure, and Beliefs: Explorations in the Sociological Thought of Neil Smelser. Berkeley, CA: University of California Press, 122–44. Zuckerman, E. W. (1999). “The Categorical Imperative: Securities Analysts and the Illegitimacy Discount.” American Journal of Sociology, 104/5: 1398–438.

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part vi

T H E H ISTOR ICA L SOCIOLOGY OF FI NA NCE

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chapter 25

histor ica l sociology of moder n fi na nce b ruce g. c arruthers

Most historical sociologists have studied large-scale phenomena like social revolutions, welfare states, industrialization, class formation, social inequality, nationalism, state formation, and world systems (Adams, Clemens, and Orloff 2004). Not many showed an interest in finance (Arrighi 2010 is a rare exception). Perhaps finance was deemed epiphenomenal, or regarded as simply too boring and technical to warrant examination. Perhaps historical sociologists were not adventurous enough to encroach on the intellectual territory of financial economics. Recent developments, however, have kindled sociological interest in financial topics. Indeed, there are few events that so concentrate popular or scholarly minds, or that feature as prominently in historical narratives, as financial crises. Episodes like the South Sea and Mississippi bubbles of 1720, and the panics and crashes of 1837, 1873, 1907, and 1929 all precipitated recessions, popular commentary, and political interventions. In their aftermath, people reflected on the madness of crowds and the instability of value, and enacted new policies to ensure that such events did not happen again. Much the same was true of the crisis of 2008. Although crashes dazzle and collapses capture attention, there are other financial institutions and processes that warrant sociological analysis. One simple reason is that, in some fashion or other, finance enters into many sociological topics. Numerous scholars study inequality, for example, and access to credit forms one basis for social advantage. Others study state formation, and find that fiscal machinery provides crucial support for rulership, military conquest, and social provision. Conversely, social revolutions and state collapses are often preceded by fiscal crises. Countries pursuing economic development often use credit as a policy instrument, and so financial institutions figure in strategies to achieve long-term economic growth. Expanding international capital flows are also a key feature of globalization, and international financial institutions like the International Monetary Fund (IMF) have been accused of undermining the sovereignty of the nation-state. In one way or another, finance is seldom more than a step away from core sociological concerns.

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When viewed over the long term, financial history is indeed visibly punctuated by the drama of crisis. But financial history also possesses a longue durée undergirded by slower moving structures and institutions. Subprime mortgages figure prominently in recent events, but much of the institutional machinery that animates US home mortgage lending dates from the New Deal era. Some development economists (e.g., de Soto 2000) argue that mortgages for small landholders in today’s developing countries would help poor people to obtain credit and unleash economic growth, but the mortgage itself is a very old contractual device, dating back many centuries in the common law tradition (Simpson 1986: 141). The recent crisis featured a variety of strange objects like credit default swaps, collateralized debt obligations, asset-backed securities, and other financial derivatives, and some have assumed that these were all monstrous creations of recently deregulated financial markets. In fact, derivatives stem from the seventeenth century, and traders on the London or Amsterdam stock markets would have understood an option or futures contract (Murphy 2009: 24–30). In the twentieth century, installment loans in the US helped turn the automobile from a luxury item into a mass market good, but installment lending was actually invented in the nineteenth century to help sell durable consumer goods like pianos, sewing machines, and encyclopedias. Financial history features many devices, methods, and techniques that develop in one context and then spread across time and space. In this chapter I will use an historical perspective to consider that which historical sociologists have mostly overlooked—finance. I shift attention away from the most visible events, namely bubbles and crises, and toward underlying institutions and processes. I will point out how, in its historical development, finance challenges many of the simple dichotomies used to think about the economy. Financial history is vast and complicated, so I must be selective in my focus. I focus mostly on Anglo-American finance, foregoing many interesting and important topics. But I make three general points. First, that private financial institutions have been deeply affected by public finance in a number of ways. Second, that both private and public regulation have shaped finance, with effects that vary substantially over time and between different countries. Third, that finance directly connects to core sociological concerns, such as the study of inequality.

Public finance Contemporary discussions view the state and the market as rivals. According to neoliberal doctrine, heavy public taxation curtails market activity, public borrowing “crowds out” private borrowing, and public regulation constrains the “natural” operation of private markets. The relationship between public and private appears zero sum: more for one sphere means less for the other. And yet, the historical record reveals an important interdependence, even symbiosis, between private and public finance. The development of private financial institutions has been deeply affected by the financial imperatives of the state.

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Among other things, states tax, borrow, and spend. Their fiscal activities are backed by their monopoly (or at least comparative advantage) over the means of coercion. In fact, as Charles Tilly pointed out (1990), nation-states in early modern Europe developed through an interdependent dynamic of war-making and revenue extraction: taxes paid for war, and coercive capacity helped to raise taxes. But states also stimulated the development of financial institutions like banks and stock markets, in part because of how these could support public finance. Adam Smith famously referred to the Bank of England as a “great engine of state” because the Bank was founded in 1694 on the basis of a ₤1.2 million loan to the English government. The Bank subsequently became one of the central institutions in London’s financial market, and continues to be so today, but it was established chiefly to help the government resolve its financial problems (Carruthers 1996). Furthermore, the shares which the Bank issued to raise the loan capital were traded on the stock market and stimulated its development. So did the shares of the other large joint stock companies established on the same basis of long-term loans to the government (e.g., New East India Company and South Sea Company). In each case, the company was given a corporate charter in exchange for a loan. Sovereign debt often defines standards in financial markets. In contemporary markets, US Treasury bonds set the benchmark for a (virtually) riskless investment, and the interest rates paid on alternative investments diverge from there. Sometimes contractual forms are made especially salient by their use in sovereign debt, and then diffuse more broadly as investors become familiar with them. For example, annuities and tontines (a type of group annuity) were used to borrow in the seventeenth and eighteenth centuries by the governments of Holland, France, and Britain (Tracy 1985; Weir 1989), and the practicalities of pricing and designing these financial contracts spurred the development of actuarial mathematics (Hacking 1975: 112–15). Eventually, actuarial methods provided the calculative foundation for insurance, risk management, and other related financial activities, including the definition and estimation of risk and return (Clark 1999; Porter 1986: 18–19). Overall, sovereign borrowing helped to standardize some of the basic concepts, contracts, and devices that came to populate financial markets. In the era before general laws of incorporation, many corporations undertook a particular kind of exchange with their sovereign polities. Corporations received special rights through special legislative acts, but were expected to contribute, in some manner, to the common good. American financial institutions in the nineteenth century frequently received their charters from state, not Federal, government. In exchange, they might have to invest in state bonds, or state mortgages, in effect making loans to state government or to farmers. The same pattern emerged during the Civil War, when the Union government established the National Banking System. Nationally chartered banks could be created by investors who purchased Union government bonds, and then could issue paper currency backed by those bonds. The measure was a success in the dual sense that many national banks were established, and the Union government was able to finance its war-driven deficit (Bensel 1990: 163, 172). The financial interests of the government directly stimulated the creation of a new system of banks, which subsequently provided more reliable financial services to the US economy.

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Later changes in public borrowing inadvertently created new tools for monetary policy. As envisioned at its founding in 1913, the primary policy instrument of the Federal Reserve System was to be the discount window: a channel through which member banks could obtain emergency financing by “rediscounting” commercial paper. As an instrument, it embodied the central banking philosophy famously articulated by Walter Bagehot: that during a financial crisis the central bank should serve as the lender of last resort, lending freely but at a high interest rate. By raising or lowering the interest rate it charged (the “discount rate”), the Federal Reserve could influence money market conditions. But World War I intervened before the Federal Reserve actually did much, and by the time it resumed operations after the war, American monetary conditions had been transformed by the massive borrowing undertaken by the Federal government. The financial system was awash in Federal debt. The widespread possession of US Treasury securities by member banks created the possibility for another policy instrument: open market operations. Gradually, the Federal Reserve realized that by purchasing and selling Treasury securities, it could raise or lower the excess reserves held by member banks and influence their lending operations. Lowering the discount rate and purchasing Treasury securities provided a double financial stimulus to the economy. Sovereign borrowing has always posed unique legal and political problems. Will a sovereign borrower keep its promise to repay? Sovereign governments cannot be sued in a court of law as if they were ordinary debtors, and by extending a loan, sovereign creditors enter into a relationship that can be as much political as it is economic (sovereign creditors acquire an interest in the political survival of the regime to which they lend). According to North and Weingast (1989), sovereign borrowers can more credibly commit to repay their loans when they share political power with those from whom they borrow. By sharing power with parliament after the Glorious Revolution of 1689, British monarchs found it easier to borrow because national debts were “backed” by parliament. This argument works, however, only for domestic lenders. Foreign lenders are not regular members of the polity whose consent bolsters the credibility of sovereign debts. Instead, foreign creditors condition their willingness to lend on the reputation of a particular sovereign debtor (Tomz 2007). Creditors refuse to lend to borrowers with bad reputations, and their willingness to do so provides an incentive for borrowers to repay. Foreign creditors can impose other sanctions as well, and their ability to cooperate among themselves enhances the effectiveness of those sanctions. Modern sovereign debtors have also been subject to the public judgments of credit-rating agencies, like Moody’s and Standard & Poor’s (S&P), who offer consequential opinions about the creditworthiness of government borrowers. A high rating, that is, a favorable opinion, allows governments to borrow at lower interest rates, whereas a low rating raises the cost of borrowing (Sinclair 2005). Key episodes in public borrowing have also changed household behavior. During the Civil War, World War I, and World War II, the US government sold bonds widely and in relatively small denominations. Motivated by patriotism, and with incomes enlarged by a wartime economic boom, many ordinary Americans acquired their first financial asset in the form of a war bond. Financial holdings typically are concentrated among the

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wealthiest households, but wartime borrowing helped set a precedent for middle- and lower-income households and gave them some familiarity with intangible assets. During the Civil War, for example, the banker Jay Cooke changed how government securities were marketed, and reached out directly through the news media to small investors nationwide (Larson 1936: 100, 106). He was particularly successful in selling bonds to small-town households that had not previously invested in financial assets. Borrowing allows states to spend beyond their current income, in effect to soften their own budget constraints, but taxation remains the key source of public resources. Borrowing itself depends on taxation since repayments come out of future tax revenues (Brewer 1989: 88), and unless the state defaults (or unless inflation erodes the debt burden) there simply are no long-term alternatives to taxes. For a time, some polities generated revenue by selling off publicly owned property (e.g., land or valuable minerals), or were able to exploit traditional forms of property (e.g., Crown lands). Modern nations with large and well-performing state-owned enterprises (SOEs) have relied on SOE profits to fund government spending, but recent waves of privatization have reduced the size of the SOE sector in many countries, and their performance was such that they usually required subsidies. In the end, taxes are inevitable for a functioning state, and the history of taxation is the history of the state (Martin, Mehrotra, and Prasad 2009). Depending on the organizational and political capacity of public revenue authorities, and on the economy’s level of development, states can impose direct or indirect taxes. They can tax people (with, e.g., a poll or head tax), individuals’ income, or wealth (e.g., a property tax). Wealth taxes can be imposed on the living or the dead (via inheritance taxes), and on some types of property (e.g., land) but not others (e.g., moveables). States tax transactions, either domestic (as in an excise tax) or international (e.g., a tariff imposed on imports). Impositions can be uniform (charging the same rate on all income, regardless of source or type) or variable (charging different rates depending on the type of income). Sometimes states collect taxes themselves, and sometimes they rely on others (via, for example, tax farming (Kiser and Kane 2001)). Clearly, some taxes are easier to impose than others: a head tax can be imposed using a simple population enumeration, whereas some kinds of property taxes require intrusive assessments of individual wealth holdings. Systems of taxation show tremendous variability over time and space, but in general their historical development has increased their extractive capacity and resulted in more elaborate and effective revenue systems. And that historical trajectory is closely entwined with political developments, especially democratization. All forms of taxation involve measurement. From the standpoint of finance, taxation has influenced the definition and measurement of financial stocks and flows. As one of the largest economic entities in any given society, and in control of the means of coercion, states set the standards with which others must comply. In parallel with money, where the state can define monetary value by bestowing legal tender status on some medium of exchange, the imposition of taxes sets various metrics for measuring income and wealth. In the early modern era, European states taxed imports (via customs taxes) and domestic production (via excise taxes). In so doing, tax authorities had to measure goods physically and monetarily, where those goods were produced, transacted, or

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transported. Ashworth (2004) points out that many advances in metrology were driven by the fiscal interests of the British state. Revenue authorities had to devise standardized weights and measures for the physical measurement of the items they taxed (quantity of beer manufactured, volume of textiles imported, etc.). And if taxes were ad valorem (i.e., set as a function of monetary value), tax authorities had to devise rules for valuation. These standards invariably diffused beyond the customs house, excise office, or Treasury to the rest of the private economy. Financial standard setting was one of the unintended consequences of taxation. When the US Federal government imposed an income tax for both individuals and corporations, it spurred the development of accounting methods, increased demand for accountants, and set standards for how to calculate annual corporate profits and income (Edwards 1958: 75–7). Concepts like “depreciation,” as applied to capital goods, were given a specific meaning in the calculation of corporate income taxes (Pechman 1983: 131–2). It also, invariably, encouraged new methods of tax evasion. Even before the establishment of the Securities and Exchange Commission (SEC) in 1934, and the imposition of disclosure requirements on publicly traded corporations, the US government shaped how firms calculated and reported their own performance.1 As the US Federal tax code grew in complexity and progressivity, and as policymakers discovered the political value of tax breaks (so-called “tax expenditures”), it motivated further elaboration of numerous financial devices and contractual arrangements, known colloquially as tax shelters (Howard 1997; Brownlee 1996: 79–81, 109). Through its various fiscal activities, the modern state has shaped the evolution of finance. How states borrow affected the development of financial instruments and stock and bond markets. Wartime public debt often lay at the core of the banking system, as the Bank of England and National Banking System attest. When the wars ended, the banks still remained. In extracting resources to service debts and fund public policies (mostly warfare, in the early modern era, but also social welfare programs in the modern period), states taxed. Decisions about how to tax, what to tax, and how much to tax, affected financial activities directly by drawing resources out of the private economy, but also indirectly, via standard setting.

Public and private regulation Financial transactions, relationships, and institutions have rarely gone unregulated. Indeed, the prohibition against usury (charging interest on a loan) derives from the Bible and Qu’ran, and in justifying this prohibition the medieval papacy made ample reference to Aristotle’s analysis of money. And usury laws are still “on the books” in many US states, although they are now easily circumvented. Even before the South Sea Bubble, the British tried to regulate stock market activity in London by limiting the number and activities of brokers (Carruthers 1996: 168; Murphy 2009: 83–6). And regulation is done both privately and publicly. How public regulations wax and wane often mark key turn-

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ing points in financial history (consider the significance of the deregulatory prelude to the 2008 financial crisis, as well as the postcrisis push to reregulate), and such changes always involve politics. Financial regulations coevolve with financial markets. Regulation poses the problem of regulatory arbitrage. Since purely financial transactions are a relatively immaterial economic activity (in the sense that, unlike steel mills or oil refineries, they do not involve substantial physical assets), they are more sensitive to cross-jurisdictional regulatory differences. If one political jurisdiction imposes onerous regulations, it can encourage financial markets to migrate to competing jurisdictions with lighter regulations. The reality or prospect of such movement can set off “races to the bottom” as different jurisdictions undercut each other by weakening regulations in order to attract or retain financial activity. At the same time, however, regulatory competition can unleash “races to the top,” when more rigorous regulations and higher standards attract investors, savers, and lenders to a particular jurisdiction (Braithwaite and Drahos 2000: 128–42). Usury laws are probably the oldest type of financial regulation, and they continue to play a role in contemporary Islamic banking (Warde 2000). Their original intent was to prohibit lenders from charging any interest on their loans, but the unintended consequence was usually to reshape how lending occurred so that interest payments were disguised: a transaction might be restructured so that repayments which ostensibly conformed to the prohibition would be accompanied by “voluntary” gifts and fees or some kind of collateral transaction (e.g., a required additional purchase by the borrower), or would involve parties not subject to the law (e.g., Jews in the Middle Ages, out-of-state banks in the twentieth century). The prohibition also encouraged illegal lending activity. Older laws prohibited any interest on a loan but the proscription relaxed over time and recent usury laws simply put an upper limit on interest rates (Wood 2002: 159–80; Horack 1941). Given how sensitive financial transactions are to what the involved parties know, it is no surprise that much financial regulation concerns information. The potential for exploitation of unsophisticated investors and lenders is obvious. For financial markets that include large numbers of participants with varying levels of sophistication (proverbial widows and orphans, on the one hand, and investment banks, on the other), caveat emptor seems politically unsustainable. But redressing informational disparities leaves open many questions. How much information must parties to a transaction provide to each other, to regulatory agencies, or to the general public? What is the format for that information? Must disclosed information be certified by third parties, and if so by who? Does information have to be updated, and with what frequency (annually, quarterly, monthly)? And what are the penalties for misinformation? Many of the regulations that mandate disclosure reflect the classic problem of information asymmetries. In financial markets, it is common for some to know much more than others about the relevant risks and opportunities. Politically, such regulations seek to protect the less well-informed from those with inside information (similarly, usury laws tried to protect vulnerable debtors from predatory lenders), and their imposition often follows periods of speculative excess and even outright fraud. Various measures to

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protect individual consumers as borrowers mandate the provision of standardized information. For example, the Uniform Small Loan Law adopted by many US states in the early twentieth century required small loan lenders to provide certain kinds of information about loan terms to borrowers (Anderson 2008). In so doing, the law aimed to prevent lenders from disguising or under-representing the true cost of a loan, and helped to ensure that borrowers knew what they were getting into. Similarly, the Truth in Lending Act of 1968, a Federal law, protected consumers by requiring lenders to present certain kinds of information in a loan contract, including a standardized measure of interest (the annual percentage rate, or APR). It did not directly set interest rates (as usury laws did), but sought greater transparency for borrowers. The most famous regulatory regime governing the provision of financial information was the Securities and Exchange Act of 1934. This measure came in the wake of a decade of stock market speculation followed by the 1929 crash, a combination which seemed to offer clear lessons for the importance of informed investors, and the dangers of insider information. But it also followed several decades of state-level attempts to regulate securities transactions (so-called “Blue Sky” laws). The latter typically required brokerage firms to obtain a state license and file a financial report on the securities they proposed to sell, but in fact state regulators were easily circumvented, and they were generally unable to distinguish between fraudulent investments and those that were merely risky (Mahoney 2003: 231–3; Anonymous 1924). Blue Sky laws were widely adopted in the 1910s and 1920s, but proved ineffective. With the stock market collapse in 1929, Federal legislation seemed necessary. By passing the Securities Act of 1933 and then establishing the SEC, Congress mandated the provision of more credible information by publicly traded firms, and dedicated a new Federal agency to the task of enforcement. Corporations issuing new securities now had to register with the SEC and provide 32 categories of information (Allison and Prentice 1990: 462–3; Braithwaite and Drahos 2000: 152). In determining the format, organization, sourcing, and interpretation of that information, however, the SEC entered into a long-term partnership with the legal and accounting professions, and granted them considerable power and discretion in standard setting (Baskin and Miranti 1997: 202; Fung, Graham, and Weil 2007: 108). Standards were not unilaterally dictated by the SEC, but rather emerged from an interaction between agency officials and expert professionals. As numerous financial scandals attest, legal and accounting firms faced recurrent conflicts of interest, and SEC vigilance in enforcing securities laws varied depending on the political administration in power. Nevertheless, establishment of the SEC marked a sea change in the amount of information publicly available to investors. Other types of regulation required financial information, but not to ensure that market participants were fully informed about their own transactions. Rather, information was used to ensure compliance with a regulatory standard by measuring some aspect of a transaction, or a set of transactions. Often, states have solicited and organized information in order to regulate corporate profitability (Powers 1914). For example, in the late nineteenth century agrarian groups contested the monopoly power of the railroads. In

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response to political pressure, the Interstate Commerce Commission (ICC) was established in 1887 to regulate rates, and to prevent railroads from exploiting small customers by charging them higher prices. The ICC developed accounting standards so that it could determine railroad costs and set “fair” prices that would give railways a “fair” rate of return (Baskin and Miranti 1997: 183–4; Berk 2009: 74–81). The ICC’s policies accelerated the development of cost accounting, methods of valuation, and general measures of profitability (Miranti 1989). Later on, during World War II, US politicians worried about wartime profiteering, especially among government contractors and subcontractors. The War Profits Control Act required firms to keep adequate records so that the Federal government could, if necessary, renegotiate its contracts and adjust prices to remove “excess profits” (Edwards 1956: 453–4). The Act problematized definitions of profit, in both its “normal” and “excess” variants. Regulations are also directed at a variety of financial institutions, including commercial banks, credit unions, thrifts, savings and loans, investment banks, insurance companies, trust companies, pension funds, and so on. The history of institutional regulation is pathdependent and politically shaped, and has produced some idiosyncratic outcomes. For example, because US insurance companies are chartered at the state level, and because most of the largest insurance companies are based in New York, the New York State Insurance Department played a surprisingly important role in tracking the American International Group (AIG) insurance company during the financial crisis of 2008. Or consider that because US commercial banks can be chartered at either the state or Federal level, the banking sector is regulated by a large number of different regulatory agencies. Banner (1998) claims that securities regulation in both the US and UK has deep historical roots. The proximate motivation for regulation is often a crisis, but in every instance regulation draws upon durable cultural and political attitudes toward finance. Both British and American publics were skeptical about market speculation, which made many financial transactions appear illegitimate. Financial markets were prone to deceitful and predatory behavior, threatened the social order, and did not involve “productive” labor (Banner 1998: 15–17, 48, 131). Mark Roe argues that the modern American pattern of corporate finance, in which large corporations have widely dispersed shareholdings, resulted directly from political decisions, and not from the imperatives of market efficiency. The American antipathy toward large financial institutions was translated into policy that curtailed the development of large banks. Instead, the US financial landscape is dotted with many state-chartered small banks, whose survival was enhanced by New Deal-era deposit insurance. And, once established, small banks became another political force against large banks. Furthermore, prudential rules governing insurance companies, pensions funds, and mutual funds enforced diversification and prohibited controlling interests in firms (Roe 1994: 42, 48, 60–1, 93). Financial regulations have sometimes been imposed privately. One example comes from the New York Stock Exchange (NYSE), which imposed reporting requirements on listed companies even before the establishment of the SEC, including that listed companies publish an audited financial statement (Baskin and Miranti 1997: 187; Sivakumar and Waymire 1993: 65). The NYSE regulated itself in a variety of ways, both formal and

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informal (Neal and Davis 2005; Preda 2009: 62–3, 71–4). The other large stock exchanges of the nineteenth century also set out explicit conditions for a listing, which in the cases of Paris and Berlin included auditing requirements (Davis, Neal, and White 2003). Although the London Stock Market dates to the seventeenth century, when the London Stock Exchange was formally established in 1801, it became able to impose rules and regulations on its member firms (Michie 1999: 35–7). Other private institutions have had a regulatory effect, although that was not their original intent. The major credit-rating agencies, for example, are for-profit firms that provide information about creditworthiness (Sinclair 2005). Starting in the early twentieth century, Moody’s (and subsequently S&P’s, and Fitch) sold ratings of railroad bonds to investors. The credit risk of a bond issue would be judged using a now-familiar ordinal category system. The highest ratings (“AAA”) signaled the lowest risk. The rating agencies expanded their activities to include corporate bonds and sovereign debt. Since the ratings helped determine the interest rate paid by the issuer (high ratings meant lower interest), rating agencies in effect regulated borrowers by imposing an implicit standard and rewarding those borrowers that best complied. Every borrower had a financial incentive to appease the rating agency, that is, to do whatever rating agencies thought would enhance creditworthiness. Moody’s did not invent credit rating. Rather, John Moody adopted a method previously developed for trade credit (short-term unsecured credit that suppliers extend to customers). Since the 1840s, the precursors of Dun & Bradstreet had been gathering information and selling credit ratings and reports to their clients (Olegario 2006). The ratings, in particular, directly anticipated Moody in that they were cast in the form of ordinal categories which, at the highest level, signaled strong creditworthiness, and, at the other extreme, unworthiness. By the end of the nineteenth century, a large “mercantile agency” like R. G. Dun had an international network of branch offices and was rating over 1 million firms annually (Norris 1978: 110). The ratings these agencies produced were used by wholesalers, suppliers, sellers, bank credit departments, and credit insurers. Until recently the regulatory effects of the rating agencies have not been controversial where private borrowers were concerned, but matters have been different when sovereign governments borrow. Although their exact methods are not generally known, it is clear that the rating agencies reward orthodox fiscal rectitude when it comes to public finance. Rating agencies may not officially endorse a neoliberal approach, but countries that cut public spending, balance their budgets, harden their currencies, and privatize state-owned assets are more likely to get a higher credit rating, and hence pay lower interest rates.2 Since governments regularly borrow on the bond markets, the rating agencies have more continuous oversight with respect to public finances. The role played by the credit-rating agencies has expanded over time. At first, Moody’s focus was on railroad bonds. But now virtually any publicly traded debt instrument issued by a private or sovereign debtor gets rated. Furthermore, the process of financial disintermediation that occurred during the 1980s and 1990s has made US corporate borrowers even more dependent on capital markets, and less on their banks (Davis 2009). Increasingly, US banks have replaced their originate-and-hold business model

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with an originate-and-distribute model. Instead of making loans and keeping them as assets, banks make loans, securitize them, and then sell them off to investors. By providing ratings, the agencies play a key role in making securitized loans acceptable to investors. And the business model of the rating agencies has itself shifted over time. Until the 1970s, investors paid for the ratings, and then used the ratings for investment decisions. Now, it is the borrowers who pay for the ratings, in effect paying the rating agencies to rate their own debt securities. The conflict of interest this poses has provoked much recent commentary. Some rules that governments establish sit somewhere between property rights and regulations. Such rules are so constitutive of market activity that it is misleading to call them “regulations,” as if there were an autonomous and preexisting activity on which an external rule was imposed. Following Campbell and Lindberg (1990) on how property rights organize economic activity, we can examine how constitutive rules organize finance. Clearly, the rules that govern corporate chartering affect finance. After all, modern financial markets are dominated by the debt and equity that private corporations issue to raise capital, and modern corporations culminate a long succession of legal forms used to mobilize capital for business (starting with the medieval commenda; see Pryor 1977). Rules of incorporation both constrain and enable those who wish to create the “fictive individuals” that dominate market economies. In the US, states charter corporations and the rules have evolved substantially over time. The changes occurring across multiple states have prompted considerable discussion about whether they constitute a race to the bottom or to the top (Kahan and Kamar 2002). For example, at the end of the nineteenth century New Jersey changed its laws to allow corporations to own stock in other corporations, and other states followed suit (Grandy 1989). Without this provision, complex and multitiered equity interests among US corporations would simply not be possible (Horwitz 1992: 83–4). And whatever the direction of change, it is clear that the state of Delaware has been a big winner since so many firms now incorporate there, regardless of where they put their headquarters, warehouses, or factories (Bebchuk and Hamdani 2002). In effect, US corporations are able to choose which set of legal rules they will operate under. Incorporation creates a fictive individual who, by law, can sue and be sued, own property, and sign contracts. A corporation enjoys the power of perpetual succession, so that even if the original owners or shareholders have died or transferred their interest to someone else, the corporation continues (unlike, for example, a partnership, which dissolves upon the death or departure of one of the partners). In other words, a corporation has a legal personality that is separate from its owners (Cooke 1951: 17). Early corporations included municipalities, guilds, universities, charitable organizations, and businesses. As a creation of law, a corporation only has those features given to it, and so the sovereign powers that create corporations can bestow different kinds of features, including rights and encumbrances. For example, state-chartered corporations can be required, as a condition of their charter, to provide an annual report to shareholders. One important change in these constitutive rules involved the establishment of limited liability. This change rebalanced the financial burden of failure, where a firm lost

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money or went bankrupt. In both Britain and the US, the establishment of limited liability meant that investors in corporations or joint stock companies could lose no more than their total investment, regardless of how great the losses sustained by the company they owned. This shifted the burden of excessive losses from company shareholders to company creditors (Baskin and Miranti 1997: 139). In Britain, the change occurred at the national level, in an 1855 amendment to the Joint Stock Companies Act of 1844 (Bryer 1997). Since the 1810s, various proposals in parliament had called attention to the advantages of limited liability, and made envious comparisons to French and Irish law (Harris 2000: 273). Some arguments in favor simply represented investor interests, claiming that people would be more willing to invest in companies knowing ex ante their maximum possible losses. Other arguments were more complex, and asserted that limited liability would also serve the interests of the working class, either as small investors or as the beneficiaries of increased investment flowing into public works and housing (Loftus 2002). The Companies Act of 1844 itself marked the shift in Britain from special to general laws of incorporation. After passage, investors could form corporations merely through registration, and did not have to obtain a special act of parliament (Harris 2000: 282–3). This changed incorporation, shifting it from an unusual privilege occasionally bestowed by sovereign power to a routine legal form that private parties could adopt if and when they saw fit. With this legal change, the number of corporations rose sharply (Harris 2000: 288). Change came less dramatically in the US, in part because it occurred at the state level and so in a less centralized fashion. Whether they were formed for business, education, or philanthropy, early US corporations were established by a special act of incorporation, passed by the relevant state legislature (Seavoy 1978). Vulnerable to the charge of political favoritism, states passed general laws of incorporation in the early nineteenth century, transforming incorporation from a special privilege to a more ordinary legal vehicle for doing business (Horwitz 1992: 73). And while limited liability was uncommon at first, it too was adopted by leading states and spread to the others (Baskin and Miranti 1997: 141). Limited liability shifted the balance between corporate owners and creditors. General laws of incorporation allowed limited liability to spread widely and affect creditor interests throughout the economy, and also for it to spread at the behest of private interests. Given that some states “competed” for corporate charters by offering favorable corporation law, the availability of limited liability increased quickly. On the positive side, limited liability encouraged people to invest in company stock since it meant that their losses were capped. However, this came at the expense of creditors, who now bore a greater proportion of the losses in case a company failed. The significance of the formal rules governing corporate debt and equity depend on the overall financial system, and how corporations typically raised money. Scholars have generally distinguished between capital market-based and bank-based financial systems (Allen and Gale 2000; Vogel 1996: 169–72; Woo-Cumings 1999: 10–12; Zysman 1983).3 In the former, exemplified by the US and UK, large firms generally mobilize capital through capital markets, relying on a balance of publicly traded stocks and bonds. In the latter, exemplified by Germany, France, Japan, and South Korea, large firms historically relied

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on large banks for loans, and developed long-term relationships with their bankers. Often, banks were part owners of the firms they loaned to, and provided “patient capital” (i.e., as investors, they were concerned about long-term performance, not just quarterly earnings). Japanese corporations have large shareholdings owned by financial groups, whereas the holdings of US corporations are widely dispersed (Roe 1994: 15, 182). Bank-based financial systems facilitated credit-based industrial policy. Governments that wished to develop an industry used their leverage over the small number of large banks to ensure that credit was “steered” into that industry. For example, “policy loans” were extended by South Korean banks, at the behest of the government, to fund heavy industry and chemicals during the 1970s (Woo 1991: 162–9). Such state-directed credit is much harder to accomplish in a capital market-based financial system. The difference between the two kinds of financial systems has implications for information as well as industrial policy. When large corporations depend on large banks for funding, they are dealing with sophisticated, knowledgeable lenders who know a great deal about the borrower. By contrast, large corporations that go to capital markets are raising money from a heterogeneous group of investors, some of whom are relatively unsophisticated. Public policy supporting greater equality of information between corporate borrowers and lenders clearly has more of a problem to solve in the second case. There is greater demand for SEC-style public disclosure in financial systems that depend on capital markets.

Finance and inequality Economic inequality is a staple topic for sociologists. The traditional focus has been on income inequality (in part because it was easy to measure) and, to a lesser extent, on wealth inequality. Sociologists explored the causes of inequality, and documented variations by gender, race, nationality, occupation, age, education, and so on. Access to credit is another dimension of inequality that has mostly been overlooked by sociologists. But looking at credit from an historical perspective makes its significance abundantly clear. Financial relationships can produce or reinforce inequality in several different ways. Most obviously, access to credit is valuable and so differential access can be used to favor some groups over others. As well, some coercive laws enhanced the power that creditors had over debtors so that being indebted was a truly subservient and onerous situation. In the US, homeownership rates among African-Americans have for many decades trailed those of whites (Carruthers and Ariovich 2010: 107). One factor behind this racial disparity involved the availability of home mortgages (Pager and Shepherd 2008). Evidence suggests that discrimination against minorities has operated at many different levels in housing markets, including access to mortgages, valuation of real estate, and availability (and pricing) of home insurance (Immergluck 2009; Yinger 1995). As Stuart (2003) shows, racial disparities were inscribed deeply within the institutional practices

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of many of the New Deal organizations founded to help the US housing market recover from the Great Depression. Robb and Fairly (2007) find a similar racial disparity when considering business credit. Financial relationships can be used directly to reinforce extreme social inequality. Debt peonage and debt servitude entailed the use of law to subordinate debtors to creditors. In late nineteenth-century Central America, for example, rural workers were typically indebted to rural landlords, and although they were nominally free they were kept in a situation of de facto servitude (McCreery 1983). Debt peonage was also common in southeastern Mexico and the Yucatán (Knight 1986). In the colonial era, European immigrants to North America frequently undertook “indentured servitude,” in effect borrowing the cost of transportation and entering into servitude until the debt was repaid (which often took four years or more; see Galenson 1984: 7). And eighteenth-century American creditors could use the law to imprison their debtors (Mann 2002: 79). After the US Civil War, crop lien laws were enacted in southern states that gave landlords enormous power over their rural tenants (Woodman 1995: 39, 65). Slavery was abolished but white landlords remained dominant over their black tenant farmers. If debt rules could be used to subordinate some groups, they could also privilege others. In early modern England, for example, it was notoriously difficult to use the courts to force aristocrats to pay their debts (Stone 1965: 235). Creditors had to find other ways to exact repayment. A person burdened with debt and beholden to his or her creditors can still sometimes obtain relief depending on bankruptcy law. In general, personal bankruptcy puts an insolvent individual through a legal proceeding in which his or her assets are seized and distributed to creditors, but afterwards the individual is discharged from whatever debts are not satisfied by liquidation of their assets. This process is modified by categories of nondischargeable debts (which still encumber the post-bankruptcy debtor) and exempt property (which the debtor gets to keep), but basically personal bankruptcy releases the debtor from his or her obligations, and grants a form of economic redemption. The history of bankruptcy in the US reflects the changing balance of power between debtor and creditor groups. Bankruptcy laws were passed in 1800, 1841, and 1867 largely in response to people who sought relief from their debts. But each law was repealed after a few years because of political pressure from creditor interests who argued that debtors were abusing the law and failing to live up to their obligations (Mann 2002: 223–8; Skeel 2001: 24–8). In general, through informal market practices and legal regulation, relationships between debtors and creditors can be cast, and recast, in ways that accentuate, or mitigate, other processes of economic inequality.

Conclusion Financial crises are occasions to recall previous financial crises, and interest in the South Sea Bubble, for example, grew as the 2008 bubble burst. But this thin historical sensibility is no substitute for a proper appreciation of financial history. Even as brief a

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treatment as I offer here underscores the sociological richness of finance. Most obviously, finance links promise-makers to promise-takers. How credible do borrowers’ pledges seem to lenders? Who do they decide to trust? In practical life, the answers to these questions are socially structured: some enjoy more trust than others, and the benefits and risks of credit are not shared equally. Financial relationships pervaded early modern economies, and their complexity and importance have only increased since then. Today, a web of intangible promises knits the economy together, supported by a changing legal and institutional infrastructure. But such increase did not occur simply because the latent potential of private interest was given freer and fuller expression, for the state mattered in how finance developed. For raison d’état and through its taxing and borrowing activities, the state has both compelled financial development and determined its direction. Sometimes financial institutions like banks and stock markets have been harnessed directly to serve the state, and sometimes the state worked indirectly and even unintentionally, via standard setting. Financial relationships also reflect the influence of private and public regulation. Rules undergird finance, imposing constraints that enable people (both real and fictive) to make promises and construct relationships across time and space. The imposition of new public financial regulations often follows a crisis, while private regulations operate less visibly in the background. But to be invisible is not to be inconsequential. Quite the opposite, the ability of private organizations like the rating agencies to regulate the pricing and flow of credit has endured precisely because of their low profile. Private regulators, like public ones, value, measure, and report. They produce technical knowledge recurrently and bureaucratically, and in so doing enact the longue durée that lies behind modern finance.

Notes 1. The newly established Federal Reserve System also inadvertently set accounting standards via the discount window. The Fed restricted the assets which were eligible for “re-discounting” to “real bills,” a form of short-term self-liquidating commercial paper. In order to ensure assets met the required standard, the Fed insisted that the issuer’s financial statements be certified by a public accountant (Edwards 1958: 80). 2. A similar process works at the level of municipal finance. See Yinger (2009). 3. This difference also affects corporate governance, but I shall not deal with that issue here.

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chapter 26

gen der a n d fi na nce j osephine m altby and j anette r utterford

Introduction In reviewing a recent collection of papers on Victorian investments, R. J. Morris comments that “Gender tends to be a category rather than a relationship in these essays . . . cultural processes are crucial to historical understanding but they need to be examined in association with economic and social relationships” (Morris 2010: 253–4). This chapter explores the tension between historical developments in women’s economic agency as savers and investors and changing cultural views of the relationship between gender and finance. A number of themes reappear over time—the gendered nature of investing, and women’s preferences for taking or avoiding risks. Is investing essentially a masculine or a feminine activity? Does its riskiness attract or repel women? Do women take on more or less investment risk as investors or as employees? The cultural “category,” we argue, has effects on the economic contexts in which women are able to operate and the opportunities made available to them, both as investors and when employed in the financial services sector. This chapter aims to provide a survey of the historically changing views of women and finance, with a special focus on women and risk. We begin by outlining the significant historical changes in women’s financial activity from the eighteenth to the twentieth centuries. We then contrast an eighteenth- and nineteenth-century view of women as speculators and of speculation as “female,” with a nineteenth- and twentieth-century view of women as cautious investors. We then move on to the twentieth and twenty-first centuries and explore contemporary views and evidence on women and risk. We consider two specific areas where “category” has an impact on context: women’s investments in pensions, and their role as workers in the financial services sector. We find that public perception of women investors in the eighteenth and early nineteenth centuries was that they were speculators, and that speculation itself was attributed a feminine character. This view of women as not understanding investment and

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speculating through emotion or through risk-seeking had disappeared by the twentieth century. The contrasting view of women as investors rather than speculators, with a natural preference and need for lower-risk securities, emerged in the mid- to late nineteenth century and has prevailed ever since. In the twentieth and twenty-first centuries, empirical evidence still points to women as less risk-taking than men, but there is debate as to whether this is due to an emotional preference for low-risk investment or is merely due to social and economic factors which force women to choose low-risk alternatives. The credit crunch of 2008 and 2009 has led to renewed discussion of women’s risk preference compared to men. Observers have argued that financial institutions would have taken on less risk had they been run by women, supporting the perception that women are fundamentally risk averse compared to men, even after allowing for socioeconomic gender differences.

Background A growing body of work has pointed out that women were active as investors from early modern times. Property was a significant asset for women as well as men from the eighteenth century onward (see, for instance, Berg 1993 and Owens 2001 for a discussion of the extent of its importance for women) but women also managed financial assets as they became available. Spicksley (2007: 206) finds that single women in the seventeenth century were very active as lenders, “more deeply embedded in the credit market than any other social group.” In the early eighteenth century, as well as loans secured on property (Miles 1981), women’s portfolios included shares in the new joint stock companies (Carlos, Maguire, and Neal 2009; Froide 2003; Laurence 2009); later in the century women took up shares in canals as these were promoted nationwide (Hudson 2001). The nineteenth century saw the arrival of a range of new assets. Government stocks were among the most significant, and work by Green and Owens (2003) has pointed out the very high incidence of women’s investment in these. Britain became “a nation of shareholders” (Robb 1992: 3) from the 1840s onward. Throughout the nineteenth century, new types of securities became available, offering fixed or variable returns. Railroad companies’ massive flotations were a key part in this opportunity, but other categories of shares, in particular those of banks and utilities, were popular. And during the late nineteenth and early twentieth centuries, women represented an increasing proportion of a growing population of individual investors (Maltby and Rutterford 2006a, 2006b; Rutterford and Maltby 2006, 2007). For example, in a study of 47 English- and Welsh-registered companies between 1870 and 1935, women represented 15.0 percent in number and 5.0 percent by value of shareholdings sampled in the 1870s; by the 1930s, the equivalent figures for women were 45.4 percent and 33.4 percent of shareholdings (Rutterford et al. 2011). A variety of factors increased women’s share ownership opportunities during the nineteenth century. Under common law, wives’ wealth was their husbands’ property, but

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marriage settlements were popular with the middle classes as well as the affluent: they offered wives security for their assets and possibly control over both income and underlying investments (see Laurence, Maltby, and Rutterford 2009: 8–9; Newton et al. 2009: 88–9). The Married Women’s Property Acts of 1870 and 1882 allowed married women to hold securities directly, without the need for a marriage settlement. In addition, the increasing number of single women, first officially recognized in the 1851 census (Rutterford and Maltby 2006: 116) and still an issue after World War I, pointed to a need for investment income for such women, many of whom were unable to earn enough to live on (Rutterford and Maltby 2007). And, despite exclusion from male business networks, women could take advantage of new sources of investment information, from the increasing number of financial newspapers and from investment manuals, some aimed specifically at women readers (see, for instance, A Guide to the Unprotected (1863) by “A Banker’s Daughter”). There was also increased marketing of financial services aimed directly at women: Robb describes the provision in the US in the late nineteenth/ early twentieth centuries of ladies’ departments and “ladies rooms” by banks and brokerage services, promoted via advertisements in women’s magazines (Robb 2009: 123–4). Women became increasingly important as investors. And, as share investment became less risky over time, with long-lasting “blue-chip” companies emerging, women began to buy ordinary shares as well as low-risk alternatives. As early as 1903, the Chairman of Spratt’s Patent stated at the annual general meeting that, out of 1,482 shareholders, there were “585 ladies, who were generally investors and who were therefore, as a rule, preferable to those who bought the shares merely as speculation” (Rutterford 2010: 9–10). World War I had an impact on women’s attitude to investment, as they became familiar with investment through Liberty Bonds or War Loans, which massive marketing campaigns encouraged them to buy (Rutterford and Maltby 2007: 7–8). By 1924, the US firm National Biscuits had women accounting for nearly half its shareholder base and American Telephone and Telegraph Corporation (AT&T) proudly announced that it had more women shareholders than men (Rutterford 2010: 17, 15). By the 1950s, in the UK and the US, women were increasingly recognized as serious investors, although they still held more lower-risk preference shares than they did ordinary shares, compared to male investors (Kimmel 1952: 17; Rutterford et al. 2011: 172).

Women as speculators We now explore historical views of women as speculators. From the early eighteenth century onward, there was anxiety about women’s possible involvement in speculation on the stock exchange. Searle (1998: 163–5) argues that the recurrence of these themes in the eighteenth century can be related partly to the view that women were thought liable to be “ill-informed” and acting on a “whim” (164) in speculating, but also because of

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concern that they exposed another face of capitalism. Rather than being a masculine, rational activity, capitalism was revealed by women’s fondness for it as a world ruled by the goddess of fortune. Searle relates this to Pocock’s suggestion that the investor was “a feminized, even effeminate being . . . wrestling with his own passions and hysterias” (Searle 1998: 164). For Pocock, the markets’ instability, their dependence on “self-generated hysteria (in the full sexist sense)” (Pocock 1985: 112–13) was enough to condemn them. Ingrassia in her study of the impact of the South Sea Bubble on finance and society in the early eighteenth century argues that “the intangible nature of speculative investment prompted representations of stock-jobbers and moneyed men preoccupied with paper credit as ‘feminized’ creatures guided by the fickle female goddesses who symbolically controlled the new economic world” (Ingrassia 1998: 20). This symbolic association of investment with feminine instability is, she argues, intensified by the growing level of involvement by women as investors (see, for instance, Laurence 2006, 2009). A set of playing cards produced in 1721 with the South Sea Bubble as its theme often shows scenes of women rejoicing or bewailing the results of their investments. The eight of spades shows a mournful woman holding a scroll that reads, “Oh fatal blow to lose at once what through artfull charms I’ve got these many years—undone, undone!” The caption below the picture sums up her situation: A Broker went to let a lady know That South Sea stock was falling very low Says she, then what I gain in my good calling By rising things, I find I lose by falling. (Carington Bowles 1721)

The metaphor links her activities as a prostitute who makes “things” rise and as an investor who loses if “things” fall. The image creates a web of connections between women and investment—it is an activity carried out by disreputable women, it is an activity that reflects the risks associated with them, and, implicitly it is one that draws in men, with potentially disastrous results. Robb (2009: 121) sees two contrasting reasons in the nineteenth century for concern about “financial chicanery” and its impact on women investors. For social conservatives, it was evidence that “the business world was too insecure for women,” for reformers proof “that an economic system in which men held most of the cards was untenable.” But as well as an index of danger in the markets, women’s speculating was seen as a reflection on their character flaws. Women gambled on the exchanges partly as the result of idleness and the need for distraction. For example, Elizabeth Caton, a spinster, speculated between 1833 and 1845 in Spanish, Chilean Portuguese, Argentinian, and Dalmatian bonds, as well as American banking shares, using a mixture of sources—newspapers, friends, her banker, and intuition (Rutterford and Maltby 2006: 126). Other women speculated out of ignorance, naïvety, or bad judgment, resulting in hasty and thoughtless buying, possibly in an attempt to increase income to meet household needs. An 1876 journalist (Blackwood’s Edinburgh Magazine 1876: 294) described the widow left “with £5,000 and a rising family” moving from government stock or railway debentures (the

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accepted “safe” securities for women) “to some of those more highly priced stocks which are the refuge of the widow, the clergyman and the reckless” in order to raise her income and thereby marry off her daughters and find employment for her sons. As the playing-card metaphor quoted above suggests, speculation was seen as evidence of the worse side of women’s natures—amoral, inconstant, and heartless. Robb’s account of women’s entry into Wall Street in the late nineteenth century identifies similar reactions. There were claims that women could not safely invest because they lacked the ability to identify risks and would be deceived more easily than men. But there was also concern that the woman broker would “change her tender heart into stone” and “crush out her human sympathies with the unfortunate and distressed” (Robb 2009: 135, quoting Fowler 1880). Thompson (2000) quotes the view taken by nineteenth-century French commentators that it was women’s innate lack of self-control that led to enthusiasm for risk-taking. Feydeau described their airy lack of concern: one hears [the women playing the market] laugh at times at tales of public disaster that make the entire nation shudder . . . sometimes also they stand there, pale and stupefied, while all the citizens of the country congratulate each other on a victory that should hasten the conclusion of peace. (Thompson 2000: 163, quoting Feydeau 1868)

Where women chose to take risks, via speculation or outright gambling for pleasure, it reflected their moral depravity. O’Connor quotes from an 1884 text on the dangers of Monte Carlo: every fourth player is a woman; and such women! Hundreds of demi-monde flock here in winter from every capital in Europe to allure and entangle well-to-do young men, who are always found present in great numbers. Truly they represent the sirens of old, and are infinitely more dangerous, often ruining entirely those whom they circumvent. (O’Connor 2005: 13)

The 1870s and 1880s saw renewed stock market speculation, during which there were claims that women were “not only frequent but daring speculators” (Robb 2009: 131, quoting Fowler 1880). However, Itzkowitz (2009) has argued that, by the 1890s, the conflation of gambling, speculation, and investment began to be clarified, with a line drawn between “fair enterprise and extravagant speculation, between legitimate commerce and illegitimate gambling” (Itzkowitz 2009: 117). He attributes this to a new type of financial press which emerged in the 1890s dedicated to the protection of the investor, and to changes in stockbroking practice, in which registered stock exchange members were distinct from disreputable bucket shops. At the same time as investment was becoming separate from speculation, so investment gradually came to be seen as a masculine, rational activity to which women were essentially unfitted (see, for example, Searle 1998: 163–5). Women were at risk of being outwitted by market practices, and so needed protection from risk. We discuss the historical discourse on women and investment in the next section.

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Women as investors In this section, we examine how the socioeconomic context caused women to be labeled as cautious investors from the late nineteenth century onward, and how this view first dominated and then displaced the view of women as speculators and, indeed, of speculation. Nancy Folbre describes Victorian values as contrasting “selfishness and altruism, the market and the family” and creating “a sacred space in which traditional moral values remained exempt from the demands of economic rationality” (Folbre 2009: 235). Part of the duty to this “sacred space,” however, was the creation and maintenance of security and order in the household’s prosperity. These were themes that appeared in writing about women as household managers from the Middle Ages onward (see, for instance, Laurence, Maltby, and Rutterford 2009: 11–12). Septimus Hansard, Rector of Bethnal Green argued that women were “the great representatives of the virtue of providence amongst the working classes” (Report of the Select Committee on Married Women’s Property Bill 1868: para. 1146). An essential element in working-class welfare as depicted by Smiles in his tract Thrift was the role of the woman. He stressed the importance of mother and wife in promoting savings: “Men may hold the reins . . . but . . . the women . . . tell them which way to drive” (Smiles 1875: 162). The wife needed to be “housekeeper, nurse and servant, all in one,” for if she were thriftless “putting money into her hands will be like pouring water through a sieve” (Smiles 1875: 188). This was partly a matter of a practical as well as a moral lead. Smiles quoted examples of thriftless working men who had reformed their ways on discovering that the wife had a savings account (Smiles 1875: 154, 183). Prudent investment was an intrinsic part of household management, and this was a role that applied to the middle-class as well as the working-class wife—see, for example, Vickery (1998: 9), who identifies “the administration of the household, the management of servants, the guardianship of material culture and the organization of family consumption” as part of the affluent woman’s role. However, there has been extensive questioning of the “separate spheres” model of nineteenth-century society which views women as confined to the private realm of home and family and thereby excluded from economic activity (see, for instance, Hamlett and Wiggins 2009: 707–9). Recent commentators (Beachy, Craig, and Owens 2006; Owens 2006) suggest that it is appropriate to see investment as linking rather than separating the private and the public spheres. According to this interpretation, it was acceptable for women to carry out financial activities provided that these harmonized with expectations of their behavior. It was not investment itself that was repugnant to femininity, but certain kinds of activity that were cause for concern. The wide activity of women as investors was reflected in literature throughout the period (see, for instance, Henry 2007 and Maltby et al. 2011) where it was sometimes viewed as exposure to danger and depravity and sometimes viewed as a basis for a safe, propertied way of life.

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There were a number of reasons encouraging women to make investments, related in part to their economic position and in part to social expectations of their behavior. The nineteenth century was a period when a reliable source of income was essential for the unprotected middle-class woman, whether widow or single, dependent on the return she could get from money left to her by her husband or father. In addition, there was an abiding expectation that women would make safe investments so that they could act as a source of support for other family members. Hall comments that daughters of the middle class “inherited forms of property which would provide an income and allow them to be independent—a life assurance, an annuity, money in trust . . . women did not operate freely in the market” (1992: 177). Women were encouraged to make choices that were low risk and involved little intervention—investing but not voting on their shares, rarely altering their portfolios. As suppliers of finance, they were “important but mostly silent actors” (Petersson 2006: 49–50). Morris, for instance, views the middle-class woman as potentially the “rescue agency” for a family network by providing relatives with access to funds that they had been safeguarding, if, as an example, brothers’ or sons’ businesses failed (Morris 2004: 374). This made government stocks, debentures, preference shares, or ordinary shares associated with lower-risk industries an attractive source of predictable, albeit low, income. Low-risk investments were therefore popular with women investors (see Rutterford and Maltby 2007). This preference for low-risk securities continued well into the twentieth century (Rutterford 2010).

Women and risk A crucial element in accounts of gender and financial decision-making is the view taken toward the differences between male and female attitudes to risk. Pocock’s account of eighteenth-century comments, outlined above, stressed the belief that risk-taking was an essentially feminine preoccupation, but nineteenth-century writing suggested that women’s natures were unsuited to risky choices. The twentieth and twenty-first centuries are marked by a continuation of the belief that women are more risk averse than men: A lot of women have a nesting instinct in terms of looking after their family and their future . . . [t]hey don’t want to risk gambling their future away . . . Men want to show they are good by finding investments which do better than the average. A lot of men like bragging about it in the pub—when it goes right, anyway. (MacErlean 2004: 9)

Barber and Odean (2001), in an influential article, looked at online trading on 35,000 accounts between 1991 and 1997. They concluded that women were likely to trade less often than men and to show less confidence in their activity. This is one of a number of studies which have reached similar conclusions—see, for instance, Prince (1993: 179), who found that men felt they had a greater propensity to gamble. Men were also more

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likely to think highly of their competence in financial dealings; they regarded themselves as thorough and took pride in their money management skills. Gerrans and ClarkMurphy (2004) found that gender had a significant effect on behavior, Dwyer, Gilkeson, and List (2002) concluded that women were more risk averse than men, and Sunden and Surette (1998), Bajtelsmit and Bernasek (1999), and VanDerhei and Olsen (2000) drew similar conclusions about “money styles” (Prince 1993: 179). There is some evidence that women are less affected by behavioral biases such as the disposition effect—greater reluctance to sell after price falls than after price gains (Da Costa Jr., Mineto, and Da Silva 2007). However, it has more recently been argued that this view of the difference between male and female risk-aversion has been exaggerated. Schubert, Gysler, and Brachinger (1999) have pointed out that evidence based on experiments did not necessarily correspond with reactions to real-life situations—for example the choice to invest or the choice to insure against risk. Work by Hibbert, Lawrence, and Prakash (2009: 3) pointed out the possibility that “risk aversion has been found to be inversely related to the level of education.” They conclude that “when individuals have the same level of education, after controlling for age, income, debts, race and the number of children in the household, single women are no more averse than their male counterparts” (Hibbert, Lawrence, and Prakash 2009: 30). Bertocchi, Brunetti, and Torricelli (2010) suggest that women’s changing views of the security of marriage, combined with expanding work opportunities, have altered their risk aversion. A large study by Christiansen, Schröter, and Rangvid (2010), which reviewed a 10 percent sample of the Danish population 1997–2004, pointed to the importance of taking account of what they describe as “background characteristics” (Christiansen, Schröter, and Rangvid 2010: 4) in comparing male and female behavior. In particular, “labor income risk and financial wealth” affect the decision to invest: men invest more and more riskily to the extent that they are wealthier and higher paid than women. This finding is echoed by Badunenko, Barasinska, and Schäfer (2009) in a survey covering behavior in Austria, Cyprus, Germany, Italy, and the Netherlands. They conclude that: the hypothesis that females take more conservative investment decisions because they are by nature more risk averse than males cannot be confirmed by the data. Other factors which cannot be taken into account in our model may play a role, such [sic] differences in human capital, duration of work life, knowledge of financial markets, or even trust in financial institutions. (Badunenko, Barasinska, and Schäfer 2009: 22)

Barasinska (2010) carries out a study of peer-to-peer lending to compare the risk attitudes of male and female participants in the market, with a view to testing the claim that “as Neelie Kroes, the EU competition commissioner, put it: ‘… the collapse of Lehman Brothers would never have happened if there’d been Lehman Sisters with them.’ ” (Barasinska 2010: 2). She finds no difference in risk aversion between the groups, nor does one group outperform the other in terms of results—loan quality, actual versus expected cash flows, and so on.

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The arguments that women are naturally risk averse have been extensively highlighted (see, for instance, Sibert 2010 for a recent overview). They have been variously interpreted in investment advice and journalism. Some commentators, following Barber and Odean, argue that women trade less often and less confidently than men but gain by their prudence (DiCosmo 2008). Others conclude that women are handicapped because risk aversion makes them miss opportunities, for example: Studies have found that women in general are far more concerned with the fear of losing money (risk) than the chance of gaining it (return). Women tend to blame themselves if an investment loses money, whereas men will blame weak markets, bad advice, or bad luck. Because of this fear of losing money, too many women put their savings into more conservative, easy-to-understand investments—like savings accounts or US Treasuries. (Wachovia 2012)

It has been argued that the substantial literature which attributes higher risk aversion to women than to men has had an impact on the advice given to women. Eckel and Grossmann (2002: 292) warn that the belief that women are always highly risk averse may reduce the choices they are offered, so that, for instance, “an investment advisor may offer a different range of options to a female than to a male investor, leading to less risky (and less lucrative) portfolios of assets.” Roszkowski and Grable (2005: 189) similarly suggest—based on a study of investment advisors’ estimates of their clients’ risk preferences—that “advisors seem to overapply the stereotype that men are more risk tolerant than women as they subjectively assess client attitudes.” The belief in women’s risk aversion is very tenacious: the idea of low-risk portfolios as being more suitable to women investors, current in the nineteenth and twentieth centuries, seems to persist today, even where challenged by empirical evidence to the contrary.

Women and pensions We now turn to the topic of pensions, where women’s attitude to risk can have a significant impact on income in retirement. Pensions represent an important object for financial planning, increasingly so as life expectancy rises and state provision is retrenched (Clark and Strauss 2008: 848). Pensions are relevant to a discussion of finance and gender because a number of issues affecting women and their pensions have attracted attention from governments and from the financial services industry—the pensions to which women are entitled, the extent to which women engage in the planning of their pensions, their understanding of the problems involved, and the extent to which they save/ invest for retirement. And pensions are also relevant to a discussion of the extent to which women engage in financial planning—how far is this seen as an activity in which women can/should engage?

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Women in the UK are potentially entitled to pensions from the state and from paid employment and/or from private savings and investments. The state pension is dependent on the contributions paid by the beneficiary; women’s contributions are more likely than those of men to have been reduced by periods of unavailability for work (particularly whilst caring for children). As a result, many women currently receive less than the full amount of basic state pension (BSP): in 2008 34 percent of women received 60 percent or less of BSP, compared with 2 percent of men (Office for National Statistics 2009). Occupational and private pension contributions will also depend on contribution levels, again affected by interruptions in work and also the propensity to save. A survey of UK women by Sykes et al. (2005: 3) found “little evidence of detailed, realistic, forward financial planning . . . vagueness about how much retirement income women or their families might need, and how much they might expect.” This was coupled with limited knowledge and understanding of pension sources and entitlements, and an apparently low priority being assigned to pensions (Sykes et al. 2005: 4–5). Similar findings about women’s understanding of pensions and planning for retirement have been made by Clark, Knox-Hayes, and Strauss (2009) and Bajtelsmit (2006: 135). Women have also been found less likely to save, and to save less than men. For example, the number of men who are now saving enough for an adequate retirement income rose from 55 percent to 59 percent between 2008 and 2009, while the number of women has barely changed, increasing from 46 percent to 47 percent (Scottish Widows 2009: 1) with women saving lower amounts of their salaries than men (8 percent and 10 percent respectively). This has been attributed to the lower level of women’s earnings (see, e.g., Office for National Statistics 2010) but also to women’s different outlook on saving. It is claimed that women are more likely to save for the short term and to be more affected by short-term (consumer) debt, and that women with dependent children are almost twice as likely as men to stop long-term savings as a result of having children: “12 percent of the women with dependent children we surveyed have had to stop all pension contributions and long term savings because of starting a family, compared to just 7 percent of men” (Scottish Widows 2009: 9). Sykes et al. (2005: 98) argue that women “put the needs of their family above their own” in their financial planning and expenditure. Surveys have also found a view that “pension planning and provision is essentially a male role linked to breadwinning” (Sykes et al. 2005: 4–5) with women generally attaching lower importance than men to financial planning (Clark, Knox-Hayes, and Strauss 2009: 2504). Women appeared to attach more importance to benefits such as employers’ assistance with childcare than to occupational pension provisions (Scottish Widows 2009: 36). These findings combine to build what Bajtelsmit (2006: 125) describes as a “dire picture” of women’s pension provision and prospects. What are the factors underlying this? Some seem to be features of the employment and benefit system within which women live and work. A contribution-based state system, in combination with female careers that are liable to be interrupted for family needs, increases the likelihood of less than full entitlement to BSP. This effect is likely to be intensified

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by the unequal distribution of private pensions, to which the majority of women are not entitled (Ginn 2003: 320). Women’s pensions are likely to perpetuate low income into retirement. Apart from lower entitlement as a result of lower earnings and contributions, women’s pension prospects are arguably affected by the tension between individual and household. The view noted above reported by Sykes et al. (2005)—that pension planning is “a male role”—can be linked with a view that a woman is part of a household and can therefore rely on the husband’s pension entitlement. Clark, Knox-Hayes, and Strauss (2009: 2510) comment that “Some respondents are clearly influenced by the existence of a SPOUSAL pension entitlement. This could mean that there is mutual learning between partners. As such, the relevant retirement income planning unit could, in fact, be the household not the individual.” Certainly, Clark and Strauss found that having a spousal pension increased the marginal probability that an individual would make riskier asset allocations (i.e., allocate a larger amount to equities) with her long-term savings, unless she was a low-income woman. Conversely, being in a household where the spouse did not have a pension entitlement decreased this likelihood, except for high income and older groups (2008: 861). Women whose husbands have a planned pension feel able to make riskier investments than those who do not—they are influenced by the household’s pension entitlement. Again, this need not be interpreted as evidence of essential female risk-aversion: it may be seen as evidence that women in more affluent households believe they can take more investment risks than those with less security. This argument is consonant with the point made by Sunden and Surette (1998: 209) that investment choices are “driven by a combination of gender and marital status.” This is a reflection of the added security that may be derived from marital status, and also the better level of information available to someone who lives in a household where there is another investor—what Clark, Knox-Hayes, and Strauss call (2009: 2496) “intimate . . . advisory relationships.” Once again, it is important to place women’s investment behavior within context in order to understand it fully.

Women and financial services We next examine women’s attitude to risk in the financial services sector. It could be argued that this offers an opportunity to investigate women’s attitude to risk in a relatively gender-neutral context, without, for example, the tension between individual and household which we observed when examining women and pensions. However, there is already gender difference in the relative numbers of men and women employed in the financial services sector. In both the UK and the US, women have taken substantial shares of lower-paid jobs in the financial services sector but are less well represented in the upper echelons of management. In the UK in 2009, for instance, women accounted for 50 percent of banking sector employees but less than 2

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percent of banks’ executive directors (House of Commons Treasury Committee 2010: 9). In the UK, there is a gender pay gap of 60 percent in financial services compared with a national gap of 42 percent at the level of gross earnings. When these figures are adjusted for hourly pay, excluding overtime, the differences are even more marked—a gap of 41 percent in finance compared with 21 percent for the economy overall (House of Commons Treasury Committee 2010: 5). In the US, women’s positions, it is now being claimed, are less secure than those of men, with women suffering disproportionately in the layoffs following the debacle of 2007 onward on Wall Street. Female employment in the US finance sector has fallen 4.7 percent since December 2006, compared with 3.2 percent for men (Raghavan 2009). In the UK, it is claimed that a variety of factors contributed to the slow progress made by women in financial services. On the supply side, these include a shortage of women applicants with a suitable background in mathematics/economics (House of Commons Treasury Committee 2010: 12) and conditions of work (long, inflexible hours, lack of parental leave) that either deter women or irretrievably interrupt their careers (House of Commons Treasury Committee 2010: Banyard Q53; Ogden, McTavish, and McKean 2006: 47–8). But these are, in turn, attributed to a pervasively masculine culture in financial services which creates a working environment designed by and for men. Presenteeism is combined with an emphasis on networking—a social life based on work contacts (see, for instance, Confessions of a City Girl (Anonymous 2009)) of a kind that exclude women. In both the UK and the US this underlies the pervasive sexism that leads to repeated claims for sex discrimination (see, for instance, Roth 2006: 24–5) and to reports by women of continuing “jokey” harassment—for example, Offensive sexual “advice” was reportedly given to women, for example “keep your legs closed” to a woman in a senior executive role working for an international bank who had just returned from her second period of maternity leave, and a male manager suggesting that a female member of his team should wear fishnet tights for a month in order to get re-graded. Comments like these often get explained away as friendly workplace banter by the men making them. (House of Commons Treasury Committee 2010: Ev 67)

A theme that recurs in discussions of women’s activity in the financial markets is one that has been discussed earlier in this chapter—the difference between male and female attitudes to risk. In addition to work on women’s personal choices, a number of recent studies have considered the activities of workers in the financial services sector. Work in this area is summarized by, for instance, Basch and Zehner (2009: 5–7) and is a popular theme in discussions of women’s role or absence in financial services. In the evidence given to the 2009–10 Treasury Committee, for example, the Association of Chartered Certified Accountants (ACCA) (House of Commons Treasury Committee 2010: Ev 34) referred to evidence which had found that “Goal-driven (often mostly male) management teams in the financial services industry have been blamed for a culture of excessive risk-taking that has damaged the global banking system.” The

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Downing Street Project1 (House of Commons Treasury Committee 2010: Ev 46) claimed that the “masculine culture” involved “the absence of emotional input in decision-making, the emphasis of task over relationship . . . a win-lose mindset . . . an emphasis on hard power . . . the taking of excessive risk.” Critics of City/Wall Street culture often go on to argue that women’s influence would have a beneficial role on financial services by replacing the current masculine emphasis on risk with a more thoughtful, careful investment strategy. Charles Goodhart argued in evidence to the UK Treasury Committee that “a very much larger number of women CEOs” would have brought “the longer term, more cautious tendency with less of the alpha male” (House of Commons Treasury Committee 2010: Q36). The ACCA continued its evidence quoted above with the suggestion that “women managers tended to take less extreme risk and to adopt more measured investment styles (which perform well over time)” (House of Commons Treasury Committee 2010: Ev 34). Basch and Zehner (2009: 7–8) suggest that women’s risk aversion is particularly relevant when markets are “highly turbulent” as it will have a “moderating effect.” This is with the proviso, though, that women’s style of “conservative investing and low turnover” is likely to lead to lower returns as well as lower risk than the male approach. Quoting Nicholas Kristof, they endorse the conclusion that “the optimal bank would have been Lehman Brothers and Sisters.” This theme—that men and women are fundamentally different and need to complement each other by playing to their strengths—is one that appears elsewhere. Altmann, in evidence to the Treasury Committee, argues that women and men should choose different areas of finance: I think I would advise young women to focus on the asset management side of the business rather than the trading side of the business. It is a lot easier for women to make progress in areas which do not require the sort of short-term, aggressive trading but require long-term, research focused activity. (House of Commons Treasury Committee 2010: Ev 34: Q59)

There is a strain which emphasizes another difference: that women’s attitude to financial decision-making is marked by emotion as well as rational evaluation. Lascu, Babb, and Phillips (1993: 81) advised that “female brokers may make substantial inroads in the market by emphasizing their gender-related qualities of empathy and nurturing.” This line is followed by Hersch, reporting advice on effective investment selling to “boomer women.” The advisor needs to approach the sexes differently: “While men tend to focus on the merits of the transaction, women attach greater importance to developing the advisor-client relationship …” He also recommends that advisors select gender-specific phrases that will help establish connections (e.g., “I know what you feel”), display similarities (“yes, I felt the same way, when …”) and match experiences (“let me share how it …”) (Hersch 2008: 62). So, the debate on gender differences in finance continues to apply in the financial services sector as well as with respect to investment decision-making.

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Conclusion This chapter has offered an overview of attitudes to gender and finance from the early eighteenth century onward that suggests that certain categories persist. A connection between women, investment, and immorality—the investment market as a reflection of female unpredictability and inconstancy—was first made at the time of the South Sea Bubble and persisted until the end of the nineteenth century with warnings of the cruelty women were tempted to display if allowed into the financial markets. The competing view—that women were too risk averse to be able to enter the market on the same terms as men—has persisted from the Victorian period to the present day and has become the dominant theme of the twentieth and twenty-first centuries. The Downing Street Project described the contrast between “hard-powered—i.e. selfinterested, coercive, risky—and soft-powered—co-operative, holistic, developmental— strategies” (House of Commons Treasury Committee 2010: Ev 46). It is interesting to compare this reading with the eighteenth-century interpretation of finance outlined above by Pocock (1985: 112–13), who identifies an eighteenth-century view of speculative finance as essentially feminine, with prices soaring and swooping like precarious female emotions. This, he finds, changed in the nineteenth century to the perception of commerce as a masculine activity, with the male as the “conquering hero” (Pocock 1985: 114). Many commentators in the twentieth and twenty-first centuries have continued to identify speculative, competitive risk-taking as masculine, and cautious, low-risk/low-return activity as feminine. This gender divide may, it has been suggested, have implications for the financial advice given to women, and for the roles allotted to them in financial services. Research has concentrated on whether this relative risk aversion on the part of women is still present once factors such as wealth, education, and household circumstances are taken into account, but results are so far inconclusive. There is, however, some evidence that women lose less money and exhibit less disposition effect when trading stock market securities. Whether due to risk aversion or other factors, these results are of interest to the financial services sector. In evidence to the Treasury Committee, one witness suggested that these were “gender stereotypes” (House of Commons Treasury Committee 2010: Banyard Q39) that were not supported by differences in performance. Certainly, the possibility that men and women approach risk differently because of their “background characteristics” (Christiansen, Schröter, and Rangvid 2010), and their human capital, still seems to be less popular than the allocation of financial behavior to an essentialist model of the differences between men and women. The claim made in the wake of the 2007 financial crash that Lehman Sisters would have performed better than Lehman Brothers— because the sisters would have been more cautious and prudent—can be readily linked with Hansard’s 1868 description of women as “great representatives of the virtue of providence.” In both cases, women’s financial behavior is forcibly assigned to a category: but it is still necessary, this chapter argues, for it to be understood in the context of the economic and social relationships within which women continue to operate.

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Notes 1. Which describes itself as an initiative “to promote and enable balanced leadership between men and women at every level of society” (The Downing Street Project 2011).

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