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English Pages 89 Year 2013
Reihe Alternative Investments Bd. 6
Sarah Kumpf
Listed Private Equity
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Investment Strategies and Returns
Diplomica Verlag
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Kumpf, Sarah: Listed Private Equity: Investment Strategies and Returns, Hamburg, Diplomica Verlag GmbH Umschlaggestaltung: Diplomica Verlag GmbH, Hamburg Covermotiv: © buchachon - Fotolia.com ISBN: 978-3-8428-3948-9 © Diplomica Verlag GmbH, Hamburg 2013 Bibliografische Information der Deutschen Nationalbibliothek:
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Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://dnb.d-nb.de abrufbar.
Dieses Werk ist urheberrechtlich geschützt. Die dadurch begründeten Rechte, insbesondere die der Übersetzung, des Nachdrucks, des Vortrags, der Entnahme von Abbildungen und Tabellen, der Funksendung, der Mikroverfilmung oder der Vervielfältigung auf anderen Wegen und der Speicherung in Datenverarbeitungsanlagen, bleiben, auch bei nur auszugsweiser Verwertung, vorbehalten. Eine Vervielfältigung dieses Werkes oder von Teilen dieses Werkes ist auch im Einzelfall nur in den Grenzen der gesetzlichen Bestimmungen des Urheberrechtsgesetzes der Bundesrepublik Deutschland in der jeweils geltenden Fassung zulässig. Sie ist grundsätzlich vergütungspflichtig. Zuwiderhandlungen unterliegen den Strafbestimmungen des Urheberrechtes. Die Wiedergabe von Gebrauchsnamen, Handelsnamen, Warenbezeichnungen usw. in diesem Werk berechtigt auch ohne besondere Kennzeichnung nicht zu der Annahme, dass solche Namen im Sinne der Warenzeichen- und Markenschutz-Gesetzgebung als frei zu betrachten wären und daher von jedermann benutzt werden dürften. Die Informationen in diesem Werk wurden mit Sorgfalt erarbeitet. Dennoch können Fehler nicht vollständig ausgeschlossen werden und die Diplomica GmbH, die Autoren oder Übersetzer übernehmen keine juristische Verantwortung oder irgendeine Haftung für evtl. verbliebene fehlerhafte Angaben und deren Folgen.
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Vorwort Sehr geehrter Leser, im Jahre 2010 entschloss sich der Bundesverband Alternative Investments e. V. (BAI), wissenschaftliche Arbeiten im Bereich der sog. Alternativen Investments zu fördern. Zu diesem Zweck wurde damals der BAI-Wissenschaftspreis ins Leben gerufen. Einer der Hauptgründe sowie die Intention für diese Förderung waren und sind, dass das Wissen über Alternative Investments sowohl in der Breite als auch in der Tiefe leider immer noch sehr rudimentär ist. In weiten Teilen der Öffentlichkeit, der Politik, der Medien, aber auch auf Seiten der Investoren herrschen oftmals vielfache Missverständnisse hinsichtlich Nutzen und Risiken von Alternative Investments. Mit dem Wissenschaftspreis will der BAI einen Anreiz für Studenten und Wissenschaftler in Deutschland schaffen, Forschungsarbeit in diesem für institutionelle Investoren zukünftig immer wichtiger werdenden Bereich zu leisten. Viele deutsche Hochschulen erklärten sich auf Anhieb bereit, den BAI bei der Bekanntmachung des Wissenschaftspreises zu unterstützen. Daraus resultierend erreichten den BAI zahlreiche anspruchsvolle Bewerbungen in den vier Kategorien „Dissertationen“, „Master-/Diplomarbeiten“, „Bachelorarbeiten“ und „Sonstige Wissenschaftliche Arbeiten“. Für diese wurde jährlich neben einem Award ein Preisgeld von 10.000 Euro an die Gewinner ausgelobt. Wir freuen uns sehr, dass der Diplomica Verlag die Reihe „Alternative Investments“ ins Leben gerufen hat. Diese Publikation wird sicherlich auch dazu beitragen, das Thema Alternative Investments einer Vielzahl von Personen näherzubringen. Wir wünschen dem Leser nun eine spannende Lektüre!
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Ihr Bundesverband Alternative Investments e. V.
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Copyright © 2013. Diplomica Verlag. All rights reserved. Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Table of contents Vorwort ..................................................................................................................................... 5 List of abbreviations ................................................................................................................. 9 List of figures .......................................................................................................................... 10 List of tables ............................................................................................................................ 11 1 Introduction ........................................................................................................................ 13 2 Theoretical considerations, literature review and derivation of testable hypotheses.. 17 2.1 Definition of Private Equity ......................................................................................... 17 2.2 Organizational forms of Private Equity ........................................................................ 18 2.2.1 Unlisted Limited Partnerships ............................................................................... 18 2.2.2 Listed Private Equity ............................................................................................. 21 2.4 Risk and return of Private Equity on investor level...................................................... 26 2.5 Testable hypotheses and exploratory analysis .............................................................. 28 2.5.1 Types of entry ........................................................................................................ 30 2.5.2 Types of exit .......................................................................................................... 33 2.5.3 Strategic decisions ................................................................................................. 34 3 Empirical analysis .............................................................................................................. 37 3.1 Data sample and descriptive statistics .......................................................................... 37 3.1.1 Investment and portfolio management strategies of German LPE entities .......... 37 3.1.2 Event study sample ................................................................................................ 40 3.1.3 Risk and return characteristics of the LPE securities ............................................ 44 Copyright © 2013. Diplomica Verlag. All rights reserved.
3.2 Event study methodology ............................................................................................. 47 3.3 Results of the event study ............................................................................................. 50 3.3.1 Acquisition announcements ................................................................................... 50 3.3.2 Exit announcements ............................................................................................... 56 3.4 Discussion..................................................................................................................... 62
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4 Conclusion and outlook .................................................................................................... 67 Appendix ................................................................................................................................. 69
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References ............................................................................................................................... 78
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Copyright © 2013. Diplomica Verlag. All rights reserved.
List of abbreviations AR
Abnormal return
BO
Buyout
CAR
Cumulative abnormal return
EBIT
Earnings before interest and tax
EBITDA
Earnings before interest, tax, depreciation and amortization
EV
Enterprise value
EVCA
European Private Equity and Venture Capital Association
GC
Growth capital
GP
General partner
HML
Fama-French high-minus-low factor
IPO
Initial public offering
IRR
Internal rate of return
LBO
Leveraged buyout
LP
Limited partnership
LPE
Listed private equity
MBI
Management buy-in
MBO
Management buyout
NAV
Net asset value
NPV
Net present value
OLS
Ordinary least squares
P/B
Price-to-book
PE
Private equity
PIPE
Private investment into public equity
PME
Public market equivalent
PV
Present value
SMB
Fama-French small-minus-big factor
UK
United Kingdom
US
United States
VC
Venture capital
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List of figures Figure 1: Structure of a Limited Partnership. .......................................................................... 18 Figure 2: Structure of an LPE investment company. ............................................................... 22 Figure 3: Number of deals per year. ........................................................................................ 42 Figure 4: Return on US$100 from 1997 till 2010. ................................................................... 45 Figure 5: Mean CARs to acquisition announcements.............................................................. 51
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Figure 6: Mean CARs to exit announcements. ........................................................................ 57
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List of tables Table 1: Investment strategies of German LPE entities. .......................................................... 39 Table 2: Descriptive statistics of acquisition and exits ............................................................ 43 Table 3: Descriptive statistics of index returns. ....................................................................... 45 Table 4: Alpha returns and Fama-French parameters for LPE indices. ................................... 46 Table 5: CARs to acquisition announcements.......................................................................... 51 Table 6: CARs to acquisition announcements for different types of entry. ............................. 53 Table 7: Differences in CARs to acquisition announcements by type of entry. ...................... 54 Table 8: Regression results on CARs to acquisition announcements. ..................................... 55 Table 9: CARs to exit announcements. .................................................................................... 56 Table 10: CARs to exit announcements for different types of exit. ......................................... 58 Table 11: Differences in CARs to exit announcements by type of exit ................................... 59
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Table 12: Regression results on CARs to exit announcements ................................................ 61
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1 Introduction The increasing popularity of private equity and especially leveraged buyout investments in the late 1980s established a novel field of research on these buyout transactions. Research was at first primarily centered on the taking private of large corporations in the United States (US). It focused on the question whether private equity firms created value through superior corporate governance mechanisms compared to public corporations or whether they exploited portfolio companies and rather transferred value from its stakeholders. In his seminal paper, Jensen (1989) claimed that private equity firms as activist investors incentivize the management of their portfolio companies to maximize value and concluded that private companies owned by private equity firms would outperform firms under public ownership in the long run.1 Others argued that private equity firms simply buy companies at a discount to fair value by exploiting private information about the takeover targets or reduce tax spending by highly leveraging the portfolio companies.2 Supporting the view of the critics, many of the highly levered portfolio companies had to declare bankruptcy after the crash of the junk bond market in the beginning of the 1990s and the overall buyout activity experienced a sharp decrease.3 However, in the late 1990s a new wave of buyout investments emerged.4
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Today, investment activity of private equity firms has spread internationally. The US private equity market remains the largest but the number of investments seen in Europe as well as in Asia has increased substantially.5 Furthermore, buyouts in new industries and private-toprivate deals have gained importance.6 In the period from 2001 to 2007, only 6.8% of all deals were public-to-private transactions, whereas private-to-private deals accounted for 36.9% of the overall buyout activity.7 The average equity ratio observed in larger European buyout deals amounted to only 31% in 2005 and increased after the turmoil of the recent financial crisis to 70% in the first half of 2010.8 In addition to changes in deal characteristics, the organizational form of private equity firms has become more diversified since the first buyout wave. Historically, institutional and wealthy private investors bought interests in unlisted limited partnerships that were set up and run by the private equity firm. However, many private equity firms went public over the past decade and have offered investors the opportunity to gain exposure to private equity by buying listed securities on an exchange. The initial public offering (IPO) of “Blackstone” in 2007 totaling proceeds of US$4.1 billion, for example, was the seventh largest in US history at that point in time.9 In general, the listed private equity universe is still considerably smaller than its unlisted counterpart. At the end of 2010, 1 2
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See Jensen (1989), p. 65. See for example DeAngelo/DeAngelo/Rice (1984), pp. 367-368, Lehn/Poulsen (1989), p. 773 and Lowenstein (1985), p. 731. See Kaplan/Strömberg (2009), p. 122. See Renneboog/Simons (2005), p. 2. Kaplan/Strömberg (2009), p. 126. See Strömberg (2007), p. 31. See Kaplan/Strömberg (2009), p. 128. Acharya/Hahn/Kehoe (2010), p. 6. See Strömberg (2007), p. 30. Private-to-private deals do not include divisional or secondary buyouts. See EVCA Buyout Report (2010), p. 14. Larger deals have deal sizes above €100 million. See Gogineni/Megginson (2010), p. 41.
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the worldwide listed private equity market amounted to about US$72 billion in contrast to more than US$1,000 billion committed capital to limited partnerships.10 The greater transparency of and availability of information about listed private equity firms offer a unique basis to conduct research. Research findings can lead to a better understanding of private equity as an asset class, which is especially relevant today in light of the increasing investment activity of private equity firms. Current research in the field of private equity and buyout investments first addresses the question how private equity firms generate value by means of an investment into a portfolio company. Drivers of value generation are typically classified into governance, financial and operational capabilities of private equity firms.11 Overall, the findings of recent literature suggest that private equity firms are skilled to improve the operations and governance of their portfolio companies.12 Financial arbitrage, for example by buying firms at a discount in expectation of higher exit multiples when disposing portfolio companies, further enhances the value added for the private equity firm.13 In addition to these direct drivers of value, investment and portfolio management strategies differ with respect to the ways of acquiring and divesting a portfolio company and these different entry and exit channels can in turn offer distinct potential for value generation. In an early study, Muscarella and Vetsuypens (1990) find portfolio companies that were divisions of larger corporations prior to the buyout to outperform portfolio firms bought out as a whole entity.14 Gottschalg and Phalippou (2009) show that investments subsequently exited via an IPO or a sale to a corporate acquirer generated higher cash flows for the private equity firm throughout the holding period.15 This leads to the question how cash flows generated on a portfolio company level translate into returns for investors, which constitutes a second field of research. Fees to the private equity firm for the management costs incurred can burn much of the value generated on portfolio firm level.16 Additionally, investors demand a compensation for their risk exposure. Risk and return figures for unlisted limited partnerships vary greatly due to difficulties in finding the appropriate measurement method.17 Listed private equity offers the opportunity to apply traditional risk and return measures since share price data are available.18 Recent studies find mostly insignificant risk-adjusted alpha returns and exposure to systematic market risk in terms of betas between 1 and 2 for listed private equity firms.19 However, these studies typically do not distinguish between different investment strategies of listed private equity firms. Only the study by Müller and Vasconcelos (2010) considers differences in returns by exit strategy.20
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10 11 12
13 14 15 16 17 18 19 20
See Brown/Kräussl (2010), p. 9. LPEQ (2011). See Kaplan/Strömberg (2009), p. 130. See Acharya/Hahn/Kehoe (2010), p. 3. Achleitner et al. (2010), p. 21. Bergström/Grubb/Jonsson (2007), p. 35. See Pindur (2007), pp. 260-262. Brigl et al. (2008) p. 10. See Muscarella/Vetsuypens (1990), p. 1412. See Gottschalg/Phalippou (2009), p. 1761. See Kaplan/Strömberg (2009), p. 136. See Kaserer et al. (2007), p. 178. See Bergmann et al. (2010), p. 53. See Bilo et al. (2005), p. 24. Lahr/Herschke (2009), p. 97. Jegadeesh/Kräussl/Pollet (2010), p. 42. See Müller/Vasconcelos (2010), pp. 9-11.
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Therefore, it is a first aim of this paper to present the investment and portfolio management strategies of private equity firms coherently. The strategies include different types of acquisitions and exits as well as the associated drivers of value creation. The second objective is to establish a link between different investment strategies of private equity firms and the expected returns generated on the investor level. Listed private equity allows analyzing the market’s reaction to the announcement of investments and divestments within an event study setting and hypotheses are derived for both of these types of events. Thereupon, the event study is conducted and different subsamples of announcements are constructed dependent on the way of entry and exit announced as well as on strategic decisions implemented in the portfolio company that is to be disposed. Positive abnormal returns upon the announcement of events indicate that investors believe in the value generation potential of private equity firms. The announcement of public-to-private takeovers for acquisitions and of IPOs and trade sales for exits resulted in significantly positive abnormal returns. Hence, the market seems to attribute higher wealth increases to these types of acquisitions and exits.
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The paper is structured into two main parts. Section 2 first defines private equity and related terms and continues with an overview of different listed and unlisted organizational forms of private equity. Furthermore, it provides a literature review for findings concerning drivers of value creation on a portfolio company level and concerning returns to investors. Finally, testable hypotheses based on these findings are derived and different investment strategies and their value generation potential are discussed. Section 3 constitutes the empirical part. First, investment and portfolio management strategies are presented for a sample of German listed private equity firms. Second, a risk and return analysis of listed private equity firms included in the larger event study sample is conducted. Third and most importantly, the event study on acquisition and exit announcement is performed and a discussion of the results is provided. Section 4 concludes and provides ideas for future areas of interest in private equity research.
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2 Theoretical considerations, literature review and derivation of testable hypotheses 2.1 Definition of Private Equity Private equity (PE) is a type of equity or equity-related ownership in either a non-listed company or a listed company with the intention to take it private.21 The PE firm acts as the financial intermediary that raises funds from institutional investors as well as high net worth individuals and subsequently allocates the raised capital to selected portfolio companies.22 Distinct from strategic investors such as corporate acquirers, the PE firm seeks to exit its investment within a medium-term investment horizon,23 during which it provides management and capital resources to the portfolio firms.24 The PE firm thus aims at creating value through the investment in the portfolio company in order to return the capital gain after fees to its investors. In a broader and more general definition of PE, one typically distinguishes between three investment styles that relate to the maturity of the portfolio firms and to the size of the equity stake acquired by the PE firm: venture capital, growth capital and buyouts.25 Venture capital (VC) is provided to young and potentially high growth firms without gaining a majority stake in the company.26 Upon the provision of growth capital (GC), the PE firm does usually not receive a majority stake either. Unlike VC, however, GC is typically invested in mature firms.27 Buyouts (BOs) refer to investments in mature portfolio firms with the purpose of obtaining majority control over the respective company and typically with the employment of substantial leverage on the firm level,28 wherefore the term buyout and leveraged buyout (LBO) is often applied synonymously. In a more narrow definition, solely (leveraged) buyouts are regarded as PE investments and the paper follows this definition. BO transactions may include the takeover of private companies from independent investors or from other PE firms, so called secondary (leveraged) buyouts29, but also comprise corporate divestitures of single divisions and the taking private of a public corporation.30 BOs can further be classified in management buyouts (MBOs) and management buy-ins (MBIs), where the former is an insider-driven and the latter an outsiderdriven BO.31 In both MBO and MBI, the management team of the portfolio company typically receives an incentivizing equity stake in the firm. However, in an MBO the existent key Copyright © 2013. Diplomica Verlag. All rights reserved.
21 22 23
24 25 26 27 28 29 30 31
See Bottazzi (2010), p. 437. Strömberg (2009), p. 4. See Kaplan/Strömberg (2009), p. 123. Kaplan and Strömberg find a median holding period of about six years for 17,171 worldwide buyout investments. See Kaplan/Strömberg (2009), p. 130. See Kaserer et al. (2007), p. 14. See Bergmann et al. (2010), p. 55. See Kaplan/Strömberg (2009), p. 121. See Bergmann et al. (2010), p. 56. See Kaplan/Strömberg (2009), p.121. Kaserer et al. (2007), p. 15. Bergmann et al. (2010), p. 55. “Secondary buyout” is applied as the generic term also for tertiary or quaternary buyouts. See Kaplan/Strömberg (2009), p. 127. See Cumming/Siegel/Wright (2007), p. 440.
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managemeent team wiill not be exxchanged aas a result oof the BO, whereas inn an MBI thhe PE firm puts a new manag gement team m in place tto take overr.32
2.2 Orgganization nal forms of Privatte Equity While the investment styles and therefore, tthe relation between thhe PE firm and a the porrtfolio Hence, companiess are alike ffor differennt PE firms, organizatiional structtures might differ.33 H distinct orgganizational structures bring abouut differencees in the rellation and contractual aarrangements beetween the investors annd the PE ffirm. The orrganizational forms caan be broadlly categorized into i unlisteed limited partnerships p s and listedd private eqquity entitiees that prim marily emerged ovver the pastt ten years.
2.2.1 Un nlisted Lim mited Parrtnershipss Limited paartnerships (LPs) or lim mited liabillity corporaations have traditionallly been andd still are the moost common n means to invest i in PE E.34 The LP P is set up bby the PE ffirm, which itself typically provides p 1% % of the LP’s capital. T The remainning 99% off capital is raised throuugh a private plaacement fro om institutioonal or weaalthy privatte investors, i.e. from the limited partners, by th he PE firm. The typicall structure oof an LP vehhicle is deppicted in Figgure 1. The capital is gradu ually drawn n down over the lifetim me of the LP P. As the ggeneral partnner (GP), thhe PE firm is the agent of th he limited paartners and its manageement team screens, sellects and addvises the portfollio companiies on a disscretionary bbasis in thee interest off the limitedd partners.35 The LP generallly has a fix xed life of teen years andd within thiis time fram me the limiteed partners rreceive the capiital appreciaation of the GP’s invesstment in thhe portfolio firm after compensatin c ng the 36 GP for his effort throu ugh manageement and pperformancee fees.
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Figure 1: Structuree of a Limited d Partnership p.
The figure shhows the typiccal structure off an LP. Limitted partners annd the GP obttain an interesst in the LP. The GP is responsiblee for the manaagement of thee portfolio firm ms. See Bergm mann et al. (20010), p. 57. 32 33 34 35 36
See Robbbie/Wright (19 995), p. 528. See Bergmann et al. (2 2010), p. 54. See Kaplan/Strömberg g (2009), p. 12 23. See Jenseen (1989), p. 61. 6 See Bergmann et al. (2 2010), p. 58.
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The management fees typically amount to 1.5% to 2.5%37 and are charged on the capital committed by the limited partners or more frequently, on the capital already invested into the portfolio firms.38 The performance fees, also called carried interest, account for the variable compensation of the GP.39 Typically, the limited partners retrieve their committed capital and earn a preferred return on their investment. The preferred return for the limited partner or hurdle rate is often set at 8% of committed capital.40 After the limited partners received the preferred return, a catch-up region might be agreed upon between the GP and the limited partners, during which the GP obtains all of the profits until he has earned the same return as the limited partners.41 Beyond that catch-up region, profits are split so that the limited partners receive 80% and the GP 20% of the profits as carried interest. If carried interest of the GP passes a certain percentage point, the GP is required to distribute the excess return to the limited partners (clawback provision).42 Additionally, the GP charges the portfolio firms transaction and monitoring fees, which are shared with the limited partners. While the transaction fees vary between 1% and 2% of the acquisition deal value,43 annual monitoring fees are reported to lie between 1% and 5% of the earnings before interest, tax, depreciation and amortization (EBITDA) of the portfolio firms.44 Due to the private placement of interests in a LP, LPs are not subject to regulation.45 However, considering principal-agent problems between the LP and the GP arising from the intermediary function of the PE firm, covenants are contractually agreed.46 Gompers and Lerner (1996) discuss the covenants between limited partners and GPs.47 Due to the option-like carried interest of the GP it is necessary to avoid excessive risk-taking.48 On the one hand, the use of debt on the LP level is constrained. On the other hand, diversification and thus constrains to risk are promoted through limited amounts of capital that can be invested in one single portfolio firm. Moreover, GPs are not allowed to cross-subsidize other, potentially troubled, LPs that they manage simultaneously to cover their worse performance. Finally, the proceeds from exited investment cannot or only with permission be reinvested, as the GP would otherwise continue to earn management fees on the not yet distributed capital. Besides these basic covenants, limited partners have few other rights. They can neither interfere in the investment decisions of the GP49 nor influence the timing of the investments and
37 38 39
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40 41 42 43 44 45 46 47
48
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See Kaplan/Schoar (2005), p. 1793. See Phalippou (2007), p. 11. See Metrick/Yasuda (2010), p. 2304. See Brown/Kräussl (2010), p. 3. See Axelson/Strömberg/Weisbach (2009), p. 1571. See Lahr/Herschke (2009), p. 97. See Bottazzi (2010), p. 440. See Metrick/Yasuda (2010), pp. 2319-2320. See Cumming/Fleming/Johan (2010), p. 2. See Kandel/Leshchinskii/Yuklea (2011), p. 432. See Gompers/Lerner (1996), pp. 480-484. Besides covenants concerning fund management presented here, they also discuss covenants relating to the GP’s activities and the types of investment. Jones and Rhodes-Kropf (2003), p. 19 argue that carried interest with a low strike price, i.e. hurdle rate, is best to incentivize GP’s effort and limit his risk proneness. See Bottazzi (2010), p. 439.
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thus, the drawdown schedule of capital.50 However, audited financial statements and details about the investments as well as about cash flow streams are typically provided to the investors on a quarterly or semi-annual basis and meetings with limited partners and the GP are conducted regularly.51 The limited partners are usually prohibited from publishing the performance reports, which leads to information asymmetries within the secondary market for stakes in unlisted LPs.52 Hence, stakes in LPs can only be sold at large discounts and this contributes to the illiquidity of LPs. The rationale of choosing a finite life of ten years with a possible prolongation of three years is threefold.53 First, it gives limited partners the opportunity to liquidate their investment in the LP and hence, accommodates their need for liquidity. Second, GPs are incentivized to create value within their portfolio companies and divest them successfully until a fixed point in time. Third, investors can assess the GP’s performance and decide whether to commit capital in another fundraising round. The fixed life structure is yet controversial. Kandel, Leshchinskii and Yuklea (2011) show that it not only induces the GP to continue to invest resources in bad investments too long so that they hopefully will be sold successfully at maturity.54 The finite life also causes the GP to dispose well performing firms too early and to neglect these well performing companies instead of increasing the possible return through the provision of resources.
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Investors seeking to invest in LPs are typically large institutions such as pension funds, banks, endowments, corporations or foundations55 because minimum capital commitments amount to about US$5 million or more and diversified portfolios would be difficult if not impossible to achieve for even mid-sized institutional investors.56 An argument for an investment in an LP rather than in listed private equity entities is clearly the more efficient cash management, as cash is drawn down when an investment opportunity exists and returned when divestments take place. Further, the proceeds are more favorably taxed depending on the tax regime. Sometimes co-investment rights to invest directly and in parallel with the LP are granted to limited partners making an investment into an LP additionally attractive.
50 51 52 53 54 55 56
See Bergmann et al. (2010), p. 54. See Strömberg (2009), p. 5. See Phalippou (2007), p. 11. See Axelson/Strömberg/Weisbach (2009), pp. 1573-1574. See Kandel/Leshchinskii/Yuklea (2011), pp. 432-433. See Fleming (2010), p. 9. See here and following Brown/Kräussl (2010), pp 2-4.
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2.2.2 Listed Private Equity While some listed private equity (LPE) entities have been listed for many years,57 most LPE entities went public over the past decade and PE companies as listed entities are still a relatively new phenomenon.58 The going public of a PE firm was often driven by its founders’ wish to reduce their stake and hence, idiosyncratic risk.59 Secondly, PE firms needed a broadened investor base to attract more capital.60 Different from the unlisted PE universe with only one dominant legal structure, in the listed vehicles’ sector four distinct organizational forms can be identified. Bergmann et al. (2010) distinguish between listed indirect PE investment companies (listed fund-of-funds), listed private equity fund managers (firms) and listed direct PE (capital) investment companies.61 Lahr and Herschke (2009) as well as Jegadeesh, Kräussl and Pollet (2010) include listed funds as a fourth category.62 Listed fund-of-funds commit capital to various unlisted LPs or listed funds. The capital is either collected from investors prior to a first investment or an already existent portfolio of funds is sold in a public offering.63 Like unlisted PE fund-of-funds, listed fund-of-funds have the disadvantage of a “double fee structure” but investors profit from diversification with respect to the underlying LPs and listed funds.64 Listed funds resemble unlisted LPs in many ways except that the fund often has an infinite life and thus, managers of the PE firm might be less concerned about their performance and reputation, as they do not need to worry about upcoming fundraising rounds.65 Different from LPs, certain quoted funds pay special or occasional dividends to investors and reinvest the proceeds after divesting portfolio companies rather than paying them out to investors.66 Appendix 1 depicts the structure of a listed fund. Shares in LPE fund managers or LPE firms, used as a synonym by Lahr and Herschke (2009), are traded interests in GPs that manage unlisted LPs.67 Such LPE firms only represent a small fraction of the LPE universe and investors do not earn a direct return on the investments in portfolio companies.68 Instead, dividends received by shareholders are a function of the management and performance fees and hence, also of the fundraising capabilities of the quoted GP.69 Appendix 2 shows graphically how a LPE fund manager is structured.
57
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58 59 60 61 62 63 64 65 66 67 68 69
Three examples constitute Ratos SE (Sweden), listed since 1954 and a pure private equity firm since the beginning of the 1990s, Electra (UK) and Deutsche Beteiligungs AG (Germany) listed in 1976 and 1985, respectively. See Brown/Kräussl (2010), p. 9. See Damadoran (2008), p. 23. See Gogineni/Megginson (2010), p. 39. See Bergmann et al. (2010), p. 56. See Lahr/Herschke (2009), p. 91. Jegadeesh/Kräussl/Pollet (2010), p. 4. See Bergmann et al. (2010) p. 58. See Lahr/Herschke (2009), p. 91. See Jensen (2007), p. 26. See Bottazzi (2010), p. 440. See Lahr/Herschke (2009), p. 91. See Bergmann et al. (2010), p. 61. See Gogineni/Megginson (2010), p. 39.
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ment compannies providee a direct exxposure to tthe private pportfolio coompaLPE (capittal) investm nies and thhus to privaate equity caapital.70 Figgure 2 depiccts the typiccal structure of LPE innvestment comppanies, whiich represennt the majoority of LPE E organizattional formss. Most LP PE investment companies c c consolidate e the portfolio compannies as subssidiaries andd invest thrrough their own balance sheeet. They teend to avoiid long-term m debt finanncing as thee portfolio firms 71 already maake use of hhigh leveraage. Some LPE invesstment comppanies addiitionally runn LPs that co-invvest in the same portfollio firms. V Via such addditional fundd managem ment sharehoolders not only paarticipate in n the capitall gain of thee direct invvestment in the portfoliio firms, buut also do they reeceive a shaare of the managemen m nt and perfoormance feees. Like soome listed ffunds, generally all a LPE com mpanies payy their sharreholders occcasional diividends.72 S Such a poliicy of reinvestmeent of proceeeds leads to a “cash drag” if no immediatte investmeent opportuunities exist. Figure 2: Structure S of an LPE invesstment company.
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The LPE invvestment comppany invests directly d into tthe portfolio companies c andd only sometiimes runs addditional LPs that co-iinvest into porrtfolio compannies. See Berggmann et al. (22010), p. 57.
Brown andd Kräussl (2 2010) proviide an overvview of the advantagess and disadvvantages off LPE 73 versus unliisted LPs. 3 Considerinng the fact tthat LPE enntities raise permanentt capital from investors andd are so callled “evergrreens”, theyy can, on thhe one handd, invest lonnger in porrtfolio firms if necessary to maximize m reeturns.74 Onn the other hand, h potenntial agencyy problems eemerge as manaagers beneffit from lockked-in capittal and are not forced to raise addditional funnds by promoting past perforrmance.75 To T mitigate these probllems, manaagers of LPE E entities aare inhare optionss and bonuuses comparrable to thee carried innterest scheeme.76 centivized through sh f reporrting requireements like other listedd corporatioons. For com mpetiLPE entitiees have to follow 77 tive reasonns, such reports are lim mited to the nnecessary publications p . This is distinct d from m LPs 70 71 72 73 74 75 76 77
See here and followingg Bergmann ett al. (2010), p. 59. See Brow wn/Kräussl (20010), p. 12. See Brow wn/Kräussl (20010), p. 14. See Brow wn/Kräussl (20010), p. 29. See Brow wn/Kräussl (20010), p. 7. See Jenseen (2007), p. 26. 2 See Brow wn/Kräussl (20010), p. 15. See Lahr//Herschke (20009), p. 93.
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that provide investors but not the public with details, for example about the cash flow streams of the underlying portfolio firms. Furthermore, the daily share price of LPE entities provides only an estimation of the fair value as the LPE entity reports the total net asset value (NAV)78 of the underlying portfolio companies at most quarterly.79 LPE vehicles that frequently trade at a discount to their NAV, offer investors the opportunity to get exposure to PE at low prices. The greatest advantage of LPE is clearly higher liquidity. This gives investors the opportunity to rebalance their portfolios when desired and limited partners the chance to maintain their exposure to PE when they receive realizations from an LP.80 As no capital requirements exist and search cost for LPE are lower, smaller institutions and private pension funds, in which equity teams rather than alternative asset team are responsible for investment decisions, form a large group of investors.81 LPE is attractive for large institutional investors since they can easily maintain their exposure to PE when receiving proceeds from investments into LPs.82 2.3 Drivers of value creation on portfolio company level Both unlisted and listed PE entities pursue a common basic investment strategy: They buy stakes in private companies to later sell them at a possibly higher price. In his seminal paper, Jensen (1989) claimed that the means of PE firms to arrive at higher valuations, which can be broadly categorized into governance, financial and operational capabilities, are superior to those of public corporations and he predicted the prevalence of leveraged private firms owned by PE companies.83 The means employed by PE firms and their effectiveness constitute a broad field of research and will be discussed in the following. Better governance mechanisms can be attributed to effective incentive schemes that align the interests of managers and of the PE firm through the provision of high equity stakes to the managers of portfolio companies.84 Furthermore, managers are strongly monitored by the PE firm and make fewer discretionary decisions.85 The concentrated ownership of the PE firms allows for an extensive assessment of the current state of the portfolio companies and for farreaching changes such as exchanging underperforming managers in the portfolio firms.86 In contrast, well performing managers that previously faced bureaucratic and hierarchical obstacles are encouraged by a new sense of entrepreneurship promoted by the PE firm to identify opportunities of improvement and growth.87 According to the free cash flow theory, leverage induces managers to be more selective in allocating new capital to positive net
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78
79 80 81 82 83 84 85 86 87
NAV is defined as “the amount estimated as being attributable to the investors in a fund (own comment: in an LPE investment company) on the basis of fair value of the underlying investee companies and other assets and liabilities”. See International Private Equity and Venture Capital Valuation Guidelines (2010), p. 8. See here and following Brown/Kräussl (2010), p. 8. See Bergmann et al. (2010), pp. 54-55. See Cumming/Fleming/Johan (2010), p. 19. See Lahr (2010), p. 40. See Jensen (1989), pp. 61-65. See Jensen (1989), p 65. See Easterwood/Seth/Singer (1989), p. 35. See Cuny/Talmor (2007), p. 630. See Holmstrom (1989), p. 326.
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present value (NPV) projects only.88 Managers are incentivized to divest already existing projects with bad internal prospects, to serve debt with the proceeds and eventually, to arrive at a more efficient company.89 In sum, if the active governance of portfolio companies by PE firms leads to lower agency cost, PE enhances performance and creates value.90 Financial value drivers can be divided into financial engineering and financial arbitrage, which can rather be seen as redistributions of value from government or debt holders and from prior owners of the portfolio firms to the PE firm, respectively.91 Financial engineering refers to the exploitation of tax deductibility of interest payments possible in most tax regimes through highly leveraging portfolio companies.92 It also includes renegotiating bank debt since PE firms are more likely to achieve more favorable credit conditions due to longstanding relationships with banks.93 Financial arbitrage considers buy-and-hold strategies of PE firms that buy portfolio companies and profit from increases in valuation multiples over time, sometimes also referred to as multiple arbitrage.94 In addition, PE firms might be able to identify undervalued portfolio firms95 and to negotiate lower takeover prices.96 Especially in MBOs, incumbent management can provide valuable private information, e.g. about possibly higher than expected future profitability, to the PE firm that results in undervaluation of the takeover target at the expense of prior owners.97 Finally, financial arbitrage subsumes asset stripping, the separate sale of divisions at a higher price than achievable through divesting the company as a whole with all its divisions.98 Asset stripping is different from strategic refocusing in the way that refocusing occurs for strategic reasons and asset stripping for financial arbitrage opportunities. Systematic benefits from financial arbitrage might be difficult to maintain99 and changes in capital structure concerning higher borrowing cannot easily provide PE firms with higher returns as more leverage brings about higher expected costs of financial distress.100 Moreover, private-to-private deals have become more common and agency problems might be less of a concern in private firms prior to the buyout, so that governance means are possibly less effective in such deals.101 Since public and private firms today have appropriated many of the corporate governance means present in the first buyout cycle of the 1980s,102 the competitive edge of modern PE firms is based increasingly on hired experts and their strategic as well
88 89 90
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91 92 93 94 95 96 97 98 99 100 101 102
See Jensen (1986), p. 324. See Jensen (1989), p. 67. See Acharya/Hahn/Kehoe (2010), p. 31. See Kaserer et al. (2007), pp. 98-99. See Kaplan/Strömberg (2009), p. 131. See Ivashina/Kovner (2010), p. 8. See Berg/Gottschalg (2003), pp. 11-12. See Baker/Smith (1998), p. 25. See Bargeron et al. (2008), p. 376. See Lowenstein (1985), p. 731. See Berg/Gottschalg (2003), p. 16. See Kaserer et al. (2007), p. 98. See Modigliani/Miller (1958), p. 275. See Siegel (2010), p. 307. See Holmstrom/Kaplan (2001), p. 7.
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operational knowledge that they bring into the portfolio firms.103 These professionals revise a company’s strategy as well as its operational efficiency and introduce measures of improvement in various areas. Operational changes refer to higher fixed asset turnovers, inventory and liquidity management as well as margin improvement through lower costs.104 Strategic shifts address, on the one hand, the sale of divisions not in line with the primary corporate objectives and thus involve downsizing to achieve increased focus.105 On the other hand, the PE firm provides capital in support of organic or transactional growth strategies. Organic growth can be achieved via a greater focus on innovation as well as via changes or expansion of the product mix and markets.106 Transactional growth implies a “buy-and-build” strategy, in which a first portfolio firm serves as a platform and further add-on companies are acquired that provide a strategic fit with the platform investment.107 To conclude, strategic amendments can increase cash flows and hence, create value, as they improve a portfolio firm’s competitive uniqueness.108 Several studies attempt to measure the effectiveness of the different means presented above though quantitative approaches vary and sample sizes do often not exceed 100 firms.109 Kaplan (1989) finds operating income to increase in the third year after the buyout and substantiates this in management’s equity stakes rising from 6% pre-buyout to 23% post-buyout.110 For public-to-private transactions in countries with poor shareholder protection, Andres et. al (2007) justify positive abnormal returns to the target’s shareholders with improved corporate governance by the PE firm.111 However, Nikoskelainen and Wright (2007), who measure governance means in terms of leverage and management’s equity holdings, do not find a positive relation between returns on enterprise value and governance.112 Cressy et al. (2007) compare a portfolio firm’s pre-buyout profitability with the profitability when the company is in hands of the PE firm and find evidence for financial engineering and selection capabilities, as performance post-buyout was higher the more profitable the pre-buyout firm was.113 Recent studies distinguish more clearly between a leverage effect and operational value creation. Acharya et al. (2010) and Achleitner et al. (2010) analyze unlevered and levered returns. Acharya et al. (2010) find portfolio firms to operationally outperform industry peers indicated by differences in unlevered returns.114 Achleitner et al. (2010) divide unlevered returns further and find EBITDA growth with 31% to be one of the largest contributors to value creation and here especially sales growth rather than cost improvement.115 Increases in multiples, which 103
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104 105 106 107 108 109 110 111 112 113 114 115
See Cuny/Talmor (2007), p. 630. Kaplan/Strömberg (2009), p. 132. See Singh (1990), pp. 113-114. See Seth/Easterwood (1993), p. 256. See Zahra (1995), p. 230. See Wright/Hoskisson/Busenitz (2001), p. 117. See Berg/Gottschalg (2003), p. 24. See Achleitner et al. (2010), pp. 25-26. See Kaplan (1989), p. 220. See Andres/Betzer/Weir (2007), p. 422. See Nikoskelainen/Wright (2007), p. 531. See Cressy/Munari/Malipiero (2007), p. 667. See Acharya/Hahn/Kehoe (2010), p. 3. See here and following Achleitner et al. (2010), p. 21.
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are a measure of market timing and thus financial arbitrage,116 account for 18% and leverage for 32% of achieved returns in buyouts. Controlling for market timing, Bergström et al. (2007) contrast the performance of buyout with non-buyout firms in the same industry and conclude that EBITDA margin and the use of assets improves more than in the peer group, whereas leverage and management shareholdings cannot explain operating improvement.117 For public-to-private deals, Guo et al. (2011) attribute 34% of returns to tax savings, 18% to changes in multiples and 23% to better operating performance.118 Pindur (2007) and Brigl et al. (2008) relate 45% (56%) of a PE firm’s value creation to EBITDA growth and 28% (21%) to multiple expansion.119 Although few evidence is provided of portfolio companies’ performance once the PE firm exited its investment and some of the undergone changes potentially exacerbate long-run profitability,120 the presented studies hint at a positive contribution of PE firms to value creation with varying results concerning its key drivers.121
2.4 Risk and return of Private Equity on investor level Another field of research analyses how the returns created on the portfolio company level are translated into returns to investors net of fees and in comparison to standard public equity returns. However, performance data are difficult to obtain for unlisted LPs and if drawn from the Venture Economics database, returns are potentially upward biased, as data are selfreported.122 Standard risk and return measures, such as estimates for market risk, cannot be calculated due to a lack of market prices for unlisted LPs, which account for the majority of PE vehicles.123 Hence, the inference of performance of PE investments can significantly differ depending on the performance measure used.124 The most common method to measure performance is the internal rate of return (IRR) despite its drawback of assuming that reinvestments of cash flows are possible at the same rate. Based on realized cash flows excluding growth in NAVs in the IRR calculation, Ljungqvist and Richardson (2003) find an excess IRR relative to the S&P500 on the limited partner level of 5.71% as a lower bound depending on the assumed cash flow schedule.125 They also find nonventure funds, of which 90.4% are BO funds, to achieve higher IRRs than VC funds. Using a larger sample that also includes more recent performance of PE, Kaplan and Schoar (2005)
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116 117 118 119 120 121 122 123 124 125
See Pindur (2007), p. 108. See Bergström/Grubb/Jonsson (2007), p. 35. See Guo/Hotchkiss/Song (2011), p. 509. See Pindur (2007), pp. 260-262. Brigl et al. (2008), p. 10. See Renneboog/Simons (2005), p. 28. Kaplan/Strömberg (2009), p. 133. See Strömberg, (2009), p. 10. See Kaplan/Schoar (2005), p. 1794. See Bilo et al. (2005), p. 4. See Kaserer et al. (2007), p. 178. In the following only results for IRR and PME are presented. See here and following Ljungqvist/Richardson (2003), pp. 37-38. The results are based on the returns of a large limited partner invested in now liquidated 73 funds, of which 54 were non-venture funds, in the period from 1981-1993.
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calculate an average IRR of 18% for BO funds between 1980 and 2001.126 They introduce the public market equivalent (PME) as an alternative performance measure that accounts for market risk. PME is the ratio of the present value (PV) of cash inflows to the PV of cash outflows discounted at the public equity market return (here S&P500) and thus, assumes a beta of 1. Based on this measure, BO funds are found to have an average PME of 0.97 in the equallyweighted and 0.93 in the size-weighted sample that convert into cumulative alphas over the LP’s life of -3% and -7% respectively. Gottschalg and Phalippou (2009) extend the sample of Kaplan and Schoar (2005) until the year 2003 and correct for three potential biases: they write down the outstanding NAVs of virtually liquidated funds, weight returns by capital invested rather than committed and correct the selection bias by extrapolating performance where cash flow data are not available.127 After these corrections the average PME reduces from 1.01 to 0.88. However, BO funds performed better than VC funds and achieved a PME of 0.95, which translates into an alpha of -1.65% p.a. The aforementioned studies consistently remark that there is great dispersion in performance. Ljungqvist and Richardson (2003) as well as Kaplan and Schoar (2005) compute IRRs of 10% (5%) for the 25% worst performing BO funds and of 28% (22%) for the 25% best performing BO funds respectively.128 The IRR of 22% in the Kaplan and Schoar sample corresponds to an outperformance of the S&P 500 by 12% over the LP’s life. These LPs do not seem to outperform by chance but there is evidence that some GPs are able to persistently beat the market.129 Gottschalg and Phalippou (2009) confirm the finding of persistence measured by the performance of the past LP.130
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LPE allows for the application of conventional performance measures, as market data are available. Studies presented in the following, however, do not distinguish between BO and VC investments. Bilo et al. (2005) analyze returns of an equally-weighted, weekly rebalanced and an equally-weighted buy-and-hold strategy with varying results: the rebalanced strategy generated an alpha of 10.43% (beta of 0.99 compared to the MSCI World) between 1986 and 2003, while the buy-and-hold strategy generated an alpha of -0.05% (beta of 1.09).131 Extending the study of Bilo et al. (2005), Lahr and Herschke (2009) find an insignificant alpha of 2.89% p.a. and a beta of 1.2 with the MSCI World as the benchmark index for an equallyweighted, bid-ask spread adjusted strategy from 1986 to 2008.132 With respect to different LPE organizational forms, public funds performed worse than investment companies, fundof-funds or fund managers. In line with their findings, Jegadeesh et al. (2010) conclude that public funds earned insignificantly negative alphas from 1994 to 2008 considering a beta of
126 127 128 129 130 131 132
See here and following Kaplan/Schoar (2005), pp. 1797-1798. See Gottschalg/Phalippou (2009), pp. 1753-1763. See Ljungqvist/Richardson (2003) p. 38. Kaplan/Schoar (2005), p. 1798. See Kaplan/Schoar (2005), p. 1806. See Gottschalg/Phalippou (2009), p. 1770. See Bilo et al. (2005), p. 24. See Lahr/Herschke (2009), p. 97.
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1.08 for the MSCI World and positive exposure to the Fama-French small-minus-big (SMB) factor.133
2.5 Testable hypotheses and exploratory analysis The findings of prior literature mostly suggest that PE is able to generate value on a portfolio firm level through superior engineering capabilities.134 In accordance, PE is found to have earned positive returns for investors before risk adjustments, while underlying measurement problems should be kept in mind.135 Considering the wide dispersion and persistence in achieved returns, it is tremendously important for PE firms to signal their skills and deal making capabilities to the market. LPE allows analyzing the market’s reaction to acquisition and exit announcements, in general, as well as with respect to specific investment and divestment strategies.
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Positive returns for LPE entities upon acquisition announcements can be expected if profits arising from synergies are probable, if benefits specific for the LPE entity can be absorbed or if a portfolio firm can be bought below its fair value.136 Except for buy-and-build strategies, the creation of synergies by means of an acquisition, which are typical for strategic corporate acquirers, can usually be neglected.137 The latter two arguments for a positive market’s assessment of acquisitions by LPE entities, however, directly point to the identified drivers of value creation. As discussed, the professionals in PE firms have on average proven to be skilled and incentivized to serve the portfolio firms as valuable advisors in identifying opportunities for growth and improvement. Thus, if the gains of turning portfolio firms more profitable outweigh the costs incurred at PE firm level, LPE entities can absorb bidder-specific profits. Second, PE acquirers often pay a lower premium than other strategic acquirers as shown by Bargeron et al. (2008).138 PE firms’ managers are possibly reluctant to overpay since with portfolio firms being divested after a certain time period, they are less interested in empire building. Furthermore, the literature on acquisitions of private firms, which are the primary targets of PE firms, finds positive acquirer returns upon announcements.139 Officer et al. (2009) suggest that competition to take over private targets is lower and in turn, more favorable prices are probable.140 Additionally, investors get exposure to private equity and capture gains otherwise not achievable through the acquisition of a private target.141
133 134
135 136 137 138 139
140 141
See Jegadeesh/Kräussl/Pollet (2010), p. 42. See Acharya/Hahn/Kehoe (2010), p. 3. Achleitner et al. (2010), p. 21. Pindur (2007), pp. 260-262. Brigl et al. (2008), p. 10. See Kaplan/Strömberg (2009), p. 136. See Chang (1998), p. 774. See Ecker (2006), p. 75. See Bargeron et al. (2008), p. 390. See for example Chang (1998), Fuller/Netter/Stegemoller (2002), Cooney/Moeller/Stegemoller (2009) for US deals and Faccio/McConnell/Stolin (2006) for European transactions. See Officer/Poulsen/Stegemoller (2009), p. 468. See Hansen/Lott (1996), pp. 59-60.
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If the market was not able to assess or had already assessed the value added by an acquisition, no market reaction would be expected. Despite more publicly available information, information asymmetries are still prevalent in LPE and portfolio companies are difficult to value separately.142 However, a first set of information about portfolio firms is available upon acquisitions and the final valuations become known upon exit announcements giving the market the chance to evaluate transactions on announcement dates. As LPE entities are basically the sum of their holdings, they are equally hard to value. Consistent with this, Kaserer and Lahr (2010) argue that one of the reasons why LPE funds trade at a discount to their NAV are information asymmetries.143 Information asymmetries are expected to be lower for more reputable LPE entities as the market has already learned about their experience and skill.144 Consequently, the expected value added by future acquisitions and achievable exit multiples are already incorporated to some degree in the market price of more reputable LPE entities. Hence, returns to both acquisition and exit announcements and reputation are expected to be inversely related. In sum, positive returns to acquisition announcements will stem from the value generation of LPE entities as they are translated into on average positive though possibly insignificant alpha returns for investors. Value for investors will be generated through governance, strategic and operational capabilities and transferred from buying portfolio firms at discounts as well as other means of financial engineering. Therefore, the following hypothesis is derived: Hypothesis 1: LPE entities generate positive abnormal returns on acquisition announcements.
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While LPE funds are required to report the total NAV of their portfolio companies during the investment period, some of the LPE companies voluntarily report the NAV at least twice a year.145 Valuations, however, tend to rely on accounting book values and historical cost or on expected multiples and thus, provide often only a rough figure for investors.146 Moreover, LPE entities may retain information about the portfolio companies that the market would price instantaneously.147 Therefore, a final valuation can only take place on exit announcements when remaining uncertainties about a portfolio firm’s value resolve, which will then be reflected in the LPE vehicle’s market price.148 On average more successful than unsuccessful exits should be expected, as PE firms tend to carry unsuccessful, inefficient portfolio firms in the book rather than exiting them.149 This leads to the second hypothesis:
142 143 144 145 146
147 148 149
See Kaserer/Lahr (2010), pp. 14-15. See Kaserer/Lahr (2010), p. 38. See Demiroglu/James (2010), p. 308. See Müller/Vasconcelos (2010), p. 4. Brown/Kräussl (2010), p. 14. See Phalippou (2007) p. 15. For a detailed description on private equity valuation see “International Private Equity and Venture Capital Valuation Guidelines” (2010). See Lahr/Herschke (2009), p. 94. See Müller/Vasconcelos (2010), p. 7. See Phalippou/Gottschalg (2009), p. 1757. Kandel/Leshchinskii/Yuklea (2011), p. 432.
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Hypothesis 2: LPE entities generate positive abnormal returns upon exit announcements. If the market associates distinct investment strategies with varying value generation potential, these differences are possibly reflected in different announcement returns of LPE vehicles with respect to the investment strategy. Distinct investment and portfolio management strategies, such as the modes of entry and exit as well as strategic decisions made within the portfolio firms, will be discussed in the following within an exploratory analysis.
2.5.1 Types of entry
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Companies can be acquired by means of an MBO or alternatively, by an MBI. In the former case, incumbent management possesses information about the portfolio firm’s prospects that facilitate the PE firm’s decision-making processes since they give an idea of feasible strategic and operational undertakings.150 Critics argue that managers might engage in earnings management and inside information is exploited to negotiate takeover prices below fair value.151 Because the management, which is backed by the PE firm, usually pays part of the purchase price, it is not incentivized to maximize the price for the prior owners.152 Only few studies analyze separately the post-buyout performance of MBOs versus MBIs and the ease of implementing ideas for improvement. Amess and Wright (2007) relate higher employment growth in MBOs to the pursuance of growth strategies and lower growth in MBIs to strategic refocusing.153 It can be argued that incumbent management has developed personal ties with the company and prefers growth opportunities to downsizing.154 This will be disadvantageous for the performance of the company if far-reaching, unpopular changes are necessary for future prosperity of the organization. Hence, in MBIs the new management is less reluctant to break implicit contracts with other stakeholders such as suppliers or employees, for example by reducing wages.155 Furthermore, value creation with a new management in place is enhanced if it brings a vitalizing vision into the company and identifies areas of improvement that were previously overseen by the old management. On the one hand, in MBOs management’s willingness to continue with the firm can potentially be regarded as a signal that the portfolio firm is in a healthy state. Private information of the management reduces chances of overpayment and facilitates the early identification of improvement opportunities. In MBIs, on the other hand, bargaining is possibly more difficult. However, informational disadvantages will decrease over time and after scrutinizing all turnaround possibilities, the impact on performance might be even greater than or at least equal to MBOs.156 The ways of investing in portfolio firms do not only differ with respect to whether management is exchanged or not, but also by the type of the prior organizational form and owner. If 150 151 152 153 154 155 156
See Robbie/Wright (1995), p. 530. See Lowenstein (1985), p. 731. See Bae/Jo (2002), p. 249. See Amess/Wright (2007), p. 193. See Scholes/Westhead/Burrows (2008), p. 12. See Shleifer/Summers (1988), p. 41. See Siegel (2010), p. 307.
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an entire private company is acquired (whole company BO), organizational and governance changes are smallest: administrative functions are in place and ownership remains concentrated in the hands of the PE firm.157 Due to the often observed concentrated ownership in private firms, agency costs in privately-held firms are expected to be low also before the buyout.158 Prior market values for private firms do not exist and cannot serve as a point of reference for neither the buyer nor the seller when negotiating the takeover price.159 This can improve the bargaining position of the PE firm, especially when there are no other possible buyers. It can, however, as well be favorable for the seller, who has inside information about the firm.160 Divisional BOs refer to a public or private firm’s divestiture of a corporate unit that continues as a standalone business after the acquisition by the PE firm. Like for whole company BOs, market prices are not observable when subsidiaries are sold. In case of divisional BOs, this can be more advantageous for the PE firm if it negotiates the takeover price with the highest tier management of the corporate, which might lack in-depth knowledge about the often noncore division to be sold.161 Moreover, the management might be under pressure to quickly sell business units.162 A conglomerate might agree to a lower price for a non-strategic division, as it wants to augment focus.163 In the early phase after the takeover, the PE firm needs to establish general, administrative functions incurring higher costs than for whole company BOs. The arising organizational form, however, is likely to be less hierarchically and complex, management, whether new or old, is not constrained by the bureaucracy of a large conglomerate and encouraged to identify opportunities for improvement.164 Goossens et al. (2008) find no difference in performance of divisional to other BOs, whereas Singh (1990), Muscarella and Vetsuypens (1990), Desbrières and Schatt (2002) as well as Loos (2006) find performance to improve more in divisional BOs.165 Secondary BOs are anticipated to offer a low potential for value creation since the initial PE firm will have already introduced governance, financial, strategic or operational measures.166 Moreover, the selling PE firm is expected to be equally experienced in price negotiations rendering favorable purchase prices for the portfolio firm difficult to achieve.167 The high frequency of observed secondary and even tertiary BOs in the PE market casts doubt on a lack of value creation capacity though.168 First, different PE firms might be characterized by different 157 158 159
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160 161 162
163 164 165
166 167 168
See Loos (2006), p. 332. See Shleifer/Vishny (1997), p. 754. Cumming/Siegel/Wright (2007), p. 445. See Fuller/Netter/Stegemoller (2002), p. 1765. See Officer/Poulsen/Stegemoller (2009), p. 468. See Nikoskelainen/Wright (2007), p. 521. The German automotive supplier Bosch even accepted a negative purchase price of more than €100 million for the sale of its division Blaupunkt to Aurelius. See Maier (2009) in Financial Times Deutschland, July 23, 2009. See Fuller/Netter/Stegemoller (2002), p. 1782. See Lichtenberg/Siegel (1990), p. 166. Bae/Jo (2002), p. 252. See Goossens/Manigart/Meuleman (2008), p. 37. Singh (1990), p. 122. Muscarella/Vetsuypens (1990), p. 1412. Desbrières/Schatt (2002), p. 723. Loos (2006), p. 380. See Bergström/Grubb/Jonsson (2007), p. 25. See Loos (2006), p. 337. See Strömberg (2007), p. 4.
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strengths and weaknesses; they apply their divergent skill set to further improve performance on the portfolio firm level and generate an attractive return for their investors.169 Second, the selling PE firm might be under pressure to do so when the lifetime of its LP is approaching the end of the investment horizon and still ongoing investments need to be realized.170 Hence, the bidding PE firm might not achieve such an unattractive price in the end. However, both Wang (2010) as well as Achleitner and Figge (2011) support the conjecture that secondary BOs are higher priced than other transactions in the same industry.171 Evidence is mixed for the theory that secondary BOs do generate additional value in terms of operating performance and thus, specific gains that would offset the purchase price.172 Public-to-private BOs have been most researched due to better data availability and their greater popularity compared to private-to-private deals in the first buyout cycle of the 1980s. The undergone change in the organizational form is likely to reduce agency cost since the concentration in ownership increases and the PE firm acts as an effective monitor of the management.173 Despite of delisting costs that will be incurred once, listing costs will be eliminated in the long run.174 By going private, the management can focus more on long-term performance rather than constantly demonstrating profitability also in the short-run and taking a myopic view. Furthermore, when the market does not reward the actions undertaken by management, a public firm has difficulties to raise new capital needed for investments.175 If the taking private by the PE firm relieves a portfolio company from the pressure experienced by capital markets, a strategic redirection and new investments are possible, which might eventually show off in performance measures and value is generated for investors of the PE firm. Especially, if other investors have not closely followed the public firm that is to be taken private and positive undertakings by the management are not reflected in the share price prior to the buyout, the PE firm is able to invest into the portfolio firm below its fair value.176 In a more recent study on US public-to-private transactions, Guo et al. (2011) find evidence for slight but insignificant operating performance increases post-buyout, but even larger returns to the PE firm suggesting that PE firms indeed identify undervalued targets to delist them.177 So far there is no known study, however, that specifically addresses the value generation in public-to-private deals compared to private-to-private transactions. In summary, it is likely that the market expects whole company BOs and secondary BOs to provide the least potential for high investor returns, which will then be reflected in lower acquisition returns. Effective governance mechanisms might already be put in place by prior
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169 170 171 172
173 174 175 176 177
See Bergström/Grubb/Jonsson (2007) p. 37. See Achleitner/Figge (2011), p. 8. See Wang (2010), p. 3. Achleitner/Figge (2011), p. 27. Bergström/Grubb/Jonsson (2007) p. 37 as well as Achleitner/Figge (2011), p. 27 do not find secondary BOs to perform worse than other primary BOs. Evidence is mixed in Wang (2010), p. 27 depending on the performance measure used. In primary acquisitions, Bonini (2010), p. 28 finds operational performance to increase after the first BO but not in secondary BOs. See Jensen (1989), p. 61. See De Angelo/DeAngelo/Rice (1984), p. 369. See Renneboog/Simons (2005), p. 5. See Andres/Betzer/Weir (2007), p. 405. See Guo/Hotchkiss/Song (2011), pp. 503-508.
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independent private owners or the initial PE firm and financial arbitrage in terms of low purchase prices is most difficult. Implementing new strategic and operational measures might create additional value. Divisional and public-to-private BOs, on the other hand, can provide opportunities for value generation on all three dimensions of identified value drivers. Agency costs are reduced in divisional BOs since management is motivated through less bureaucracy and in going private deals through incentive alignment and monitoring by the PE firm. Both divisions and public companies might be acquired below fair value and finally, growth or refocusing strategies as well as operational measures can be implemented.
2.5.2 Types of exit Although an ideal type of divestment might have been announced upon investing into a portfolio company, the actual exit way is likely to be dependent on the firm’s development throughout the holding period.178 Hence, the announced exit channel allows for a final assessment of the realized return and serves as an important measure of success for investors.179
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It has been put forward that IPOs - or reverse LBOs in the case of portfolio firms that were public entities prior to the BO – are only an exit route for those companies that are the strongest and offer the highest growth opportunities.180 Thus, an announced IPO is expected to best signal the skills and engineering capabilities of the LPE entity. Furthermore, IPOs might generate the most favorable exit prices since the public investor has to rely only on information provided in the offering memorandum.181 However, chances for an IPO are limited when portfolio firms, though very successful in terms of performance, are too small to go public, when costs of being listed are too high or when market conditions are unfavorable.182 Under such circumstances and in general, a trade sale, which is the sale of a portfolio firm to a strategic corporate acquirer, can result as an equally good alternative for realizing a high return for investors. Additionally, the PE firm is not only likely to be more experienced in price negotiations than the corporate acquirer, but also possesses inside information about the portfolio company that can be used to achieve high exit prices in trade sales. High exit prices are also likely because the corporate acquirer realizes synergies and is thus willing to pay more.183 In line, Gottschalg and Phalippou (2009) find that the relation between performance and exit success is stronger when exit success includes both IPOs and trade sales and not just IPOs alone.184 Nikoskelainen and Wright (2007), on the other hand, report IPOs to provide the highest IRRs, trade sales come second, and secondary BOs offered the lowest though still positive returns.185
178 179 180 181 182 183 184 185
See Wright/Robbie/Albrighton (2000), p. 26. See Schmidt/Steffen/Szabó (2009), p. 2. See here and following Müller/Vasconcelos (2010), pp. 9-10. See Cumming/MacIntosh (2003), p. 116. See Brau/Fawcett (2006), p. 423. See Cumming/MacIntosh (2003), p. 105. See Gottschalg/Phalippou (2009), p. 1761. See Nikoskelainen/Wright (2007), p. 522.
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Secondary BOs potentially realize lower returns as takeover prices are negotiated with another sophisticated PE firm. Takeover prices are especially low if the PE firm must divest the portfolio firm at the end of a LP’s life to realize the investment.186 For LPE entities, however, this problem is less pronounced due to their infinite life suggesting that LPE entities might achieve more favorable exit prices than unlisted GPs. The announcement of insolvency and subsequent write-off of a portfolio company is clearly a signal of investment failure sent to the market and might cast doubt on future deal making capabilities.187 Especially if the market did not anticipate the precarious state of the portfolio company, a negative market reaction is expected. Alternatively, one can argue that the write off is better than holding the company as a “living dead” in the portfolio. A write off is preferred if the PE firm would otherwise waste resources to turn the company around. The announcement of insolvency then signals a PE firm’s ability to distinguish between good and bad investments and divesting the bad investments early enough.188 In line, the length of the holding period might additionally reveal information about the success of the investment. However, two opposing theories exist. On the one hand, the PE firm might spend more time and effort on less well performing firms and divest them later so that a long holding period is rather a bad signal.189 On the other hand, Cumming and MacIntosh (2003) argue that value can only be created in the long run after information uncertainties about the portfolio firm have resolved and thus, longer holding periods generate higher returns but they only find weak evidence.190 Schmidt et al. (2009) support their theory and conclude that write-offs are less probable the longer the holding period,191 whereas Nikoskelainen and Wright (2007) find a negative relation between IRR and holding period.192
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2.5.3 Strategic decisions Finally, exit success and thus returns to investors might only be indirectly associated with the exit channel but the strategic decisions made during the holding period rather influence the exit success. Strategic decisions are in the following defined as either growth strategies or strategies of refocusing on core products or divisions. Growth strategies can be subdivided into organic and inorganic, transactional growth (“buy-and-build”) strategies. In an early study, Singh (1990) notices that portfolio companies exited via an IPO had shown high sales growth suggesting that growth strategies create more value if IPOs are the preferred exit channel.193 Especially buy-and-build strategies might offer high returns in fragmented industries, where potential for synergies exists.194 In accordance, Chapman and Klein (2010) find 186 187 188 189 190 191 192 193 194
See Achleitner/Figge (2011), p. 8. See Easterwood/Seth/Singer (1989), p. 36. See Schmidt/Steffen/Szabó (2009), p. 2. See Kandel/Leshchinskii/Yuklea (2011), p. 432. See Cumming/MacIntosh (2003), pp. 194-195. See Schmidt/Steffen/Szabó (2009), p. 22. See Nikoskelainen/Wright (2007), p. 523. See Singh (1990), p. 122. See Chapman/Klein (2010), p. 242.
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add-on acquisitions to specifically enhance investor IRR. However, a buy-and-build strategy is also the most complex, as acquired companies have to be integrated into an already existing company. Organic growth strategies often entail expansion into new markets or innovation of new products. This diversification over different products and markets reduces risk. PE backed firms have also shown to successfully encourage innovation.195 Moreover, according to the findings of Acharya et al. (2010) active corporate governance measures are more often present in organic strategies.196 Refocusing strategies aim to establish a competitive advantage within one product market and thus, often lead to the sale of non-core divisions. The portfolio company can concentrate on its strengths and does not waste resources on less profitable units despite possibly accepting higher risk as it gives up on diversification benefits.197 It might additionally be easier to find a buyer for a company with a limited product offering than for a more diversified one.
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It can be assumed that any of the described strategies can create substantial value as long as the strategy is clearly defined and elaborated. In the case of BOs, however, portfolio firms are mostly highly levered and have to pay down debt, which potentially limits the flexibility to make further investments for growth. Therefore, refocusing strategies might be more appropriate as the cash generated through the sale of divisions can be used to pay down debt. Long and Ravenscraft (1993) do not find divestments aiming at greater focus to influence performance.198 One reason might be that cash flows become more volatile when focusing on a narrow product range and debt capacity is thus limited. While offering similar potential for value creation before considering the high debt level, organic growth strategies might be most appropriate for BO investments: they are less risky than inorganic or refocusing strategies, necessary investments might be not as high as in a buy-and-build strategy and should generate enough cash flows through growth to service debt.
195 196 197 198
See Lerner/Sorensen/Strömberg (2011), p. 474. See Acharya/Hahn/Kehoe (2010), p. 5. See Easterwood/Seth/Singer (1989), p. 39. Loos (2006), p. 351. See Long/Ravenscraft (1993), p. 22.
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3 Empirical analysis The hypotheses derived in Section 2 concerning the market’s reaction to acquisition and exit announcements in general as well as the expectations about the value generation potential of different investment strategies are tested in the empirical part of the paper. First, the data sample for the event study is described in detail. Second, the event study is conducted and a discussion about the results is provided.
3.1 Data sample and descriptive statistics For the empirical analysis, a first assessment of the investment strategies of German LPE entities was performed to arrive at an understanding of the investment and portfolio management strategies of LPE entities and their representativeness for the PE market in general. The data sample was then extended and further LPE entities were included so that the final sample for the event study was more internationally diversified.
3.1.1 Investment and portfolio management strategies of German LPE entities
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For a preliminary analysis of the investment strategies applied by LPE entities, data on LPE entities and their respective transactions was collected from CapitalIQ199. To be included in the sample, the LPE entity needed to be classified in Capital IQ as either a “public investment firm” or a “public fund” headquartered and listed in Germany. This resulted in a sample of 27 firms. The sample was then restricted to only those entities with a market capitalization larger than €2 million200 as of December 31, 2010. After revising the transactions filed in CapitalIQ, those LPE entities were eliminated that were more akin to be investors into VC, GC or in public equity, so called private investments into public equity (PIPEs).201 The final sample consists of nine LPE entities, which account for 107 BO investments into portfolio companies from 1997 to 2010. The period was chosen since CapitalIQ may lack information before the middle of the 1990s.202 48.6% of those 107 investments are of the three largest LPE entities by market capitalization. VC and GC transactions as well as transactions where the LPE entities together with potential syndicate partners acquired less than a 25% stake were dropped.203 199
200
201
202 203
CapitalIQ is a database of Standard&Poors. It provides information about public and private companies as well as about M&A transactions for professionals and academia. This minimum market capitalization was required as a liquidity criterion for the traded securities. See Bilo et al. (2010), p. 7. For example, “Deutsche Effecten- und Wechselbeteiligungsgesellschaft AG” or “U.C.A. AG” are classified in CapitalIQ as being interested in turnaround and buyout investments but the actual transactions’ primary features are with very few exceptions only VC, GC or PIPE deals. See Kaplan/Strömberg (2009), p. 126. Although the chosen LPE entities primarily engage in BO transactions, a VC or GC deal was sometimes recorded. The 25% stake was required because it might be difficult for the LPE entity to effectively influence the activities of a portfolio company if it acquired less than a 25% stake.
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Further information especially on the applied value drivers was hand collected from annual reports and from searches in Factiva. If not available in annual reports or news reports, data on revenues and the number of employees were added by searching Amadeus.204 Table 1 summarizes the investment strategies for the sample of German LPE entities. Overall, MBIs were more common than MBOs and portfolio companies were mostly acquired by means of a divisional BO. The greater relevance of private-to-private as compared to public-toprivate deals is also reflected in the fact that only one public-to-private transaction was filed in CapitalIQ for the respective period. Trade sales accounting for 38.46% of all exits and secondary LBOs with 33.85% were most often observed. The percentage of insolvencies (23.08%) seems high compared, for example, to the study of Strömberg (2007) but becomes more reasonable when considering that 55 out of the 107 portfolio companies (not reported in Table 1) were in distressed situations prior to the BO according to information provided in annual or news reports.205 At the same time, 12 out of 15 bankrupt firms were in distress prior to the BO suggesting that they are more prone to become insolvent. Organic growth strategies and operational measures, such as process efficiency improvements, were implemented in more than half of all portfolio firms. The fact that organic growth was the most popular of all strategic decisions independent of the entry mode might be an indicator for its suitability in highly levered BO investments. Sometimes, more than one strategic decision was made. This was possible, for example, when a portfolio company refocused on its core products and subsequently, aimed at growing organically by entering new markets or by acquisitions within its reduced product range. The median holding period of 2.36 years appears rather short, especially since LPE entities theoretically have an infinite investment horizon.
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Columns 2 and 3 compare MBOs to MBIs. Interestingly, the holding period for MBOs of four years was substantially higher than for MBIs of 2.31 years and also not yet exited investments have been ongoing for a longer time.206 Despite potential informational advantages in price negotiations in MBOs, the LPE entity does not seem to buy undervalued portfolio firms to quickly resell them at a higher price, so called “quick flips”.207 Furthermore, MBOs
204
205 206 207
Amadeus is a database by Bureau van Dijk containing information on both public and private European firms. See Strömberg (2007), p. 14. See Achleitner et al. (2010), p. 19 for a comparison of holding periods found in different studies. See Strömberg (2007), p. 15.
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3.08 38.46 33.85 23.08
23.36 31.78 57.01 56.07 23.36 25.23 8.41 mean median
2 25 22 15 42
25 34 61 60 25 27 9 N
50.00 204
89.56 100.00 7.16 5.30
107 47
105 140.59 104 848
2.57 3.19
65 42
2.36 3.25
19.63 80.37 38.32 57.01 0.93 3.74
%
21 86 41 61 1 4
N
(1) All
78.18 10.44
3.99 4.67 80.00 14.80
3.32 4.17
19.05 33.33 71.43 19.05 19.05 0.00 23.81 mean median
10.00 50.00 20.00 20.00
57.14 28.57 4.76 9.52
21 322.86 254.00 20 2677 830
21 14
10 11
4 7 15 4 4 0 5 N
1 5 2 2 11
12 6 1 2
(2) MBO N %
84 84
86 33
55 31
21 27 46 56 21 27 4 N
1 20 20 13 31
55 29 0 2
N
2.31 3.08
92.81 371
41.00 183
91.30 100.00 1.37 0.00
2.31 2.66
24.42 31.40 53.49 65.12 24.42 31.40 4.65 mean median
1.82 36.36 36.36 23.64
63.95 33.72 0.00 2.33
(3) MBI %
2.36 3.25
50.00 204
84.74 100.00 4.45 5.30
3.38 2.74
14.63 43.90 58.54 43.90 34.15 21.95 12.20 mean median
4.55 40.91 40.91 13.64
29.27 70.73
41 100.73 40 534
41 15
22 19
6 18 24 18 14 9 5 N
1 9 9 3 19
12 29
(4) Whole company N %
2.11 3.14
58.00 211
92.71 100.00 2.31 0.00
2.17 3.46
29.51 24.59 55.74 63.93 16.39 27.87 4.92 mean median
2.50 37.50 30.00 27.50
9.84 90.16
59 150.41 59 969
61 30
40 21
18 15 34 39 10 17 3 N
1 15 12 11 21
6 55
(5) Divisional buyout N %
Taable 1: Investmentt strategies of Germ man LPE entities.
90.00 10.00
1.50 n/a
90.00 10.00
1.50 n/a
1 766.90 766.90 1 4692 4692
1 1
1 0
0 0.00 0 0.00 1 100.00 0 0.00 0 0.00 0 0.00 0 0.00 N mean median
0 0.00 1 100.00 0 0.00 0 0.00 0
1 100.00 0 0.00
(6) Public-to-Private N %
68.50 0.80
1.96 4.62
98.85 721
63.95 3.20
1.96 4.62
25.00 25.00 50.00 75.00 25.00 25.00 25.00 mean median
0.00 0.00 50.00 50.00
50.00 50.00
4 172.43 1 610
4 1
2 2
1 1 2 3 1 1 1 N
0 0 1 1 2
2 2
(7) Secondary LBO N %
This table reports th he deal characteristtics of German LPE E entities in the period from 1997 to 20010 and includes both realized and stilll ongoing investmennts. Column 1 summarizes all obsserved transactions, while columns 2 too 7 differentiate by the type of entry. N is the number of observations o for each characteristic.
Holding period (in years) Holding period if exited Holding period if ongoing Acquired stakes (in %) By LPE entity By target's management Size of the target at acquisition Revenues (in €m) Number of employees
Type of entry MBO MBI Whole company Divisional buyout Public-to-Private Secondary LBO Type of exit IPO Trade sale Secondary LBO Insolvency Not yet exited Value drivers Refocusing Transactional growth Organic growth Operational engineering Governance engineering Financial engineering Syndicated deals
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might indeed be a signal for a more healthy company to be taken over since operational engineering and refocusing in spite of the larger size was less often observed than in MBIs. However, it might also be the case that the incumbent management simply preferred growth to unpopular but necessary downsizing and cost cutting within the portfolio company. A drawback is that “Deutsche Beteiligungs AG”, which is also the largest LPE entity in the sample in terms of market capitalization, initiated almost all MBOs and generalizations are thus limited. Appendix 4 shows a detailed breakdown of investments for the single LPE entities. Columns 4 to 7 display the deal characteristics by the portfolio firms’ prior organizational form. Contradictory to the conjecture that potential for agency cost reduction is low in whole company BOs, governance engineering was more common in whole company BOs (34.15%) than in divisional BOs (16.39%). The acquired stake by management of 4.45% in whole company BOs versus 2.31% in divisional BOs further underlines the importance of incentive alignment between the new PE owners and management. Whole company BOs were more often syndicated and the holding period was longer. At the same time, they ended less often in bankruptcy suggesting that deal syndication with other PE firms and longer holding periods were related to investment success. No general conclusions can be drawn for public-to-private or secondary LBOs as the sample size is too small. However, it is still interesting to note that both already exited secondary LBOs could not be divested by means of a trade sale or even IPO. These portfolio companies were rather sold after a short holding period in a tertiary BO or went bankrupt. The findings for this small sample of LPE entities show that LPE entities pursue similar strategies and apply the same set of value drivers when investing into portfolio firms as unlisted PE companies. Hence, results of return analyses of listed entities with respect to investment strategies can also provide meaningful insights for the larger unlisted universe.
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3.1.2 Event study sample To arrive at a larger sample size of acquisition and exit announcements for the event study on PE investment strategies, the first sample was extended by LPE entities listed in the “LPX Buyout Index”, which ensures a higher degree of liquidity of the traded securities.208 Return characteristics of this index will be presented in section 3.2.3. Only those listed vehicles were included that were classified as “direct private equity” companies as opposed to “direct private mezzanine” capital providers, “private equity fund managers” or “private equity fund of funds”. “Direct private equity” companies, which include public investment firms and public funds, profit most directly from value creation in the respective portfolio firms, which will potentially be reflected in the market reaction to transaction announcements. Investor returns depend only on management fee income and thus fundraising capabilities when a public investment firm engages in additional fund management. Additionally, they do not depend on the fund selection skills of a fund-of-funds manager. Once again, the transactions filed in CapitalIQ for these firms were revised and 10 out of 32 entities were dropped, for which CapitalIQ had only recorded VC, GC or PIPE deals. Moreover, four entities 208
Please refer to LPX Group’s “Guide to LPX Equity Indices“ and www.lpx-group.com for a detailed description of the index composition.
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were excluded because of unreliable stock price data as the return series from Datastream did only display very few price movements. “3i Group” was excluded from the main sample as at least one weekly transaction was reported and it would not be possible to separate the transactions in the event study. Finally, 17 additional LPE entities were included in the sample, while three German LPE companies listed in the LPX Buyout Index were already covered by the first sample of German LPE entities.209 The final sample thus includes 26 listed entities, of which 21 are public investment firms and the remaining five public funds. The majority is listed in Continental Europe, three are listed in the United Kingdom (UK), two in North America and one in Brazil.
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Information on the deals of these 26 LPE entities was taken from CapitalIQ. All GC, VC and PIPE transactions as well as acquisitions of solar or wind energy parks were eliminated. The event date is the “announcement date including bids and letters of intent” recorded in CapitalIQ. The event date was matched with the press announcement on the LPE entities’ website and in case of divergence, the website date was chosen as event date, as it was more likely the date, when the information reached the market. To avoid overlapping event windows with confounding information, all transactions were excluded where the LPE entity acquired or divested more than one firm or earnings were announced surrounding the five days of the event date. After these corrections, the main sample consists of 326 acquisition announcements and 185 exit announcements. The five LPE entities with the greatest number of deals account for 44.8% of all acquisition and for 56.8% of all exit events. Figure 3 shows the timing of the deals with a peak of investment and divestment activity in the beginning of 2007, which is in line with the overall PE market.210 Furthermore, Appendix 3 provides a separate, detailed description of the single LPE entities and Appendix 4 shows a breakdown of their deals and investment strategies.
209 210
These companies are “Deutsche Beteiligungs AG“, “Aurelius“ and “Gigaset AG (Arques)“. See Kaplan/Strömberg (2009), p. 122.
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Figure 3: N Number of deaals per year.
The graph deepicts the distrribution of acqquisition and exit announceements from 11997 to 2010.
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Table 2 prresents the descriptive statistics fo for the acquuisition and exit transaactions incluuded in thee event studyy. MBOs (4 46.3% of all deals) andd MBIs (53.7%) are noow more baalanced as compared too the prelimiinary samplle. The perccentage of ppublic-to-prrivate deals and seconddary LBOs is more re-presentativve for the PE P market in i general.2211 Insolvenncies reduceed in percenntage figurees to 7.0%.. The averagge holding period increased to 4.1 years witth a sample standard deviation d off 2.7. Againn organic groowth was th he most com mmon strattegy and puursued in alm most half (446.5%) of aall portfolioo companiess. The strateegic decisionns are integgrated into the t event stuudy of exit announcem ment to ana-lyze to what extent thee final valuation of an investment, reflected iin the markeet’s reactionn to the exitt announcem ment, depen nds on the strategic meeasures takeen during thhe holding period. p “Tottal strategicc decisions” is the num mber of all strategies iimplemented in one poortfolio com mpany and most oftenn does not exxceed 1. To controll for reputattion of the LPE entity,, variables for f syndication, age annd price-to--book (P/B)) ratio are inntroduced. A reduced signaling efffect of annoouncements is expectedd as the marrket alreadyy learned about reputab ble LPE entities’ skills.. Syndicatioon is used tto measure reputation aas it can bee assumed thhat only rep putable LPE E entities aare able to eestablish a network off syndicate partners.2122 Firm age iss a common n measure used u for repuutation sincce age refleccts
211 212
See Ström mberg (2007),, p. 30. See Meulleman et al. (22009), p. 617.
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Table 2: 2 Descriptivee statistics of acquisition aand exits
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Number of deals in sample Avg. number of deals/firm Min. number of deals/firm Max. number of deals/firm Fraction of deals of 5 largest firms Fraction of deals of the 5 firms with most deals Type of entry MBO MBI Whole company Divisional buyout Public-to-Private Secondary LBO Privatization Variables for reputation and learning Syndicated deals LPE entities' age (in years) LPE entities' price-to-book ratio Variables for size Target's revenues (in €m) Transaction size (in €m) Implied target's enterprise value (in €m) LPE entities' market capitalization (in €m)
Number of deals in sample Avg. number of deals/firm Min. number of deals/firm Max. number of deals/firm Fraction of deals of 5 largest firms Fraction of deals of the 5 firms with most deals Strategic decisions Refocusing Transactional growth Organic growth Total strategic decisons Type of exit and holding period IPO Trade sale Secondary LBO Insolvency Holding period (in years) Variables for reputation and learning Syndicated deals LPE entities' age (in years) LPE entities' price-to-book ratio Variables for size Target's revenues (in €m) Transaction size (in €m) Implied target's enterprise value (in €m) LPE entities' market capitalization (in €m)
N 326 13 1 45
%
Acquisitions mean median
standard deviation
25.46 44.79 151 175 147 101 19 58 1
46.32 53.68 45.09 30.98 5.83 17.79 0.31
79 326 326
24.23
221 183 285 326
N 185 7 0 31
%
23.23 1.40
15.00 0.99
38.68 1.27
240.82 263.46 211.25 651.44
65.91 70.69 61.25 284.05
604.65 591.92 496.13 942.73
Exits mean
median
standard deviation
20.54 56.76 26 47 86 160
14.05 25.41 46.49
5 103 64 13 144
2.70 55.68 34.59 7.03
64 185 185
34.59
135 133 170 185
1
1
0.63
4.07
3.54
2.67
28.92 1.13
19.00 0.90
48.60 0.83
256.95 145.65 188.13 592.27
82.30 72.79 75.18 249.40
724.87 786.02 615.15 1142.15
Descriptive statistics s of thhe variables foor the type of entry and exiit as well as foor syndicated deals, refocussing, transac-tional growthh and organicc growth are dummy variabbles equal to 1 if applicable and 0 otherwise. LPE enntities’ age iss derived from m the foundingg date providedd in CapitalIQ Q. For public ffunds, the GP’s age was takken. LPE entitties’ P/B ratioo and market capitalization c at the date off the announccement is from m Datastream.. Transaction size is taken from Capital-IQ. Target’s revenue is deerived from CaapitalIQ, annuual reports or Amadeus. A
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433
BO experience and survivorship.213 The P/B ratio approximates the NAV discount, which in turn should reflect present information asymmetries between the market and the LPE entity.214 Information asymmetries are expected to be lower for more reputable companies and funds reflected in a higher P/B ratio. The median LPE P/B ratio is below 1 in both samples and shows that some of the LPE entities might be undervalued, as the market possibly has not (yet) incorporated growth expectations in the market price. After the market has assessed the information content of new deal announcements, market inefficiencies should resolve and thus the signaling effect is expected to be stronger for less reputable LPE entities with a lower P/B ratio.215 The target’s enterprise value (EV) and the LPE entity’s market capitalization serve as further control variables for target and LPE entity specific characteristics besides reputation. CapitalIQ reported only very rarely the target’s EV. If, however, the transaction size was reported this was used as a proxy.216 In this case, EV is biased downward when less than a 100% stake was acquired. If neither EV nor transaction size were reported, the EV was calculated by using historic revenue multiples by industry sector provided in CapitalIQ. For the event study, the closing stock price data and the market index return data were obtained from Datastream.217 The market index is a broad MSCI country index of the country, where the LPE entity is listed since LPE entities primarily invest in and thus have greatest exposure to the country of listing.
3.1.3 Risk and return characteristics of the LPE securities
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To obtain an intuition for the return distribution of LPE entities, inherent risk and return characteristics are presented in the following. Figure 4 shows the return on US$100 invested in January 1997 until December 2010 compared to standard equity indices.218 The equally- and value-weighted indices comprise only the LPE entities included in the study, while the LPX Buyout Index is the broader index. The equally-weighted index is rebalanced weekly, whereas the value-weighted index is rebalanced only upon new listings based on the market capitalization of the respective entities.
213 214 215 216 217
218
See Demiroglu/James (2010), p. 318. See Kaserer/Lahr (2010), pp. 2-4. See Andres/Betzer/Weir (2007), p. 411. Müller/Vasconcelos (2010), p. 12, for example, use the same approach. An exception are the stock price data for the Brazilian firm „GP Investments“, which were obtained from Bloomberg. Return data for the LPX Buyout Index were only available since 01/01/1999 in Bloomberg.
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Figurre 4: Return on US$100 frrom 1997 till 2010.
The graph prresents the retturn developm ment of the LP PX Buyout Inndex, of an eqqually and off a value-weigghted index off LPE entities compared to the t MSCI Woorld and the M MSCI Europe for f the period under investiggation.
The figure indicates th hat the LPE E vehicles m most of the time t perform med better (worse) ( thann the stand-ard equity indices wh hen the markket was in aan upswingg (downswinng). Overalll, the LPE indices andd especially the LPX Buyout B Index generatedd higher ariithmetic meean returns than the M MSCI Worldd and MSCI Europe as presented in i Table 3. However, the standarrd deviationns were alsoo higher forr the LPE inndices excep pt for the eqqually-weighhted index.
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Tab ble 3: Descriptive statisticss of index retu urns.
The table proovides an overrview of the return r distribuution for differrent LPE and broad equity indices from 1997 to 2010.. All per annuum returns annd standard deeviations are calculated based on weeklly logarithmicc returns for tthe respectivee indices. *** denotes signifficance at the 1% level.
All indicess are negatiively skeweed and yielld a stronglly leptokurttic return diistribution. Hence, thee Jarque-Berra test rejeccts the hypothesis of nnormal disttribution foollowing a cchi-square ddistributionn 219 with two degrees d of freedom. f Considerinng only the higher mom ments of thee LPX Buyout Index’ss 219
See Jarquue/Bera (19800), p. 257.
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return distrribution, thee LPX Buyoout Index w was less attrractive for thhe risk-averrse investorr because off the high sttandard dev viation, neggative skew and fat taiils. On the other hand,, the equallly-weightedd index, whiich puts hig gher weight on the smaaller LPE enntities, show ws a comparrably low standard de-viation andd is only slightly skew wed. The Ljung-Box Q-statistic Q reeveals that returns r exhhibit signifi-220 cant autocoorrelation att the 1% siggnificance leevel and doo not follow w a random w walk. Alphas aree determineed to estimaate a risk-addjusted retuurn figure ffor the LPE E indices baased on thee 221 Fama-Frennch three facctor model. Thus, noot only the exposure too market rissk is measurred but alsoo to firm sizze and to vaalue versus growth firm ms. Due too autocorrelation, the matching m annd 7 laggedd excess maarket returnns are incluuded to esstimate Dim mson betass similar too Lahr andd Herschkee 222 (2009). The T followiing ordinaryy least squaares (OLS) rregression eequation waas employedd: 7
rt − rf ,t = α + βk × (rm,t −kk − rf ,t −k ) + βs × SMBt + βv × HMLt + ε t , k =0 =
where rt is the weekly y log return of the indeex, rf,t is the risk-free raate and apprroximated bby calculat-ing the weeekly return on three-m month US-treasury billss. rm,t-k are tthe (lagged)) weekly logg returns off the markett index, SMB MBt is the sm mall-minus-bbig firm sizee factor andd HMLt the high-minuss-low book-223 to-market value v factorr. t is thee error term and is thee constant oof the regresssion equatiion. Resultss are shown in Table 4. Tab ble 4: Alpha returns r and F Fama-French h parameters for LPE indices. LPX Buyout Model 1 1.1994***
Model 2
Equally-weighted Model 3 1.1485***
Model 4
Value-weighted Model 5 1.4292***
Model 6
MSCI World MSCI Europe SMB HML
0.0040*** 0.0073***
1.0012*** 0.0041*** 0.0073***
0.0000 0.0000
0.9645*** 0.0001 0.0001
0.0005 0.0003
1.2145*** 0.0006 0.0005
alpha alpha p.a.
0.0003 0.0167
0.0003 0.0148
0.0002 0.0118
0.0001 0.0055
0.0001 0.0030
-0.0001 -0.0050
R2
0.4439
0.3927
0.4046
0.3864
0.3761
0.3513
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The table preesents the parrameter estimaates for the ddifferent LPE indices as deppendent variabbles. In Modeel 1 and 2 thee LPX Buyoutt weekly log return r is the dependent d varriable, in Moddel 3 and 4 thhe equally-weiighted index rreturn, and inn Model 5 andd 6 the value-w weighted indeex return. MSC CI World and MSCI Europpe are the sum m of the beta estimates from m lag 0 to 7 (Dimson beta). Their T significaance is tested using Wald teests. *** denootes significannce at the 1% llevel.
220 221
222 223
See Ljungg/Box (1978),, pp. 297-298.. See Fam ma/French (19992), p. 428. The T weekly rreturn data foor the SMB aand the HML L factors werre taken from m http://mba.tuck.dartmoouth.edu/pagess/faculty/ken.ffrench/data_liibrary.html. See Dimsson (1979), p. 204. Lahr/Heerschke (20099), p. 95. The Carhhart four factoor model, whiich introducess a momentum m factor as thhe fourth factor, could not be employedd because weekly w data foor the momenttum factor weere not availabble.
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All LPE indices have significant factor loadings for the MSCI World with Dimson betas between 1.15 and 1.43 and hence, part of their return can be explained by exposure to systematic market risk. Surprisingly, Dimson betas are lower for the MSCI Europe although the equally-weighted and the value-weighted index are primarily composed of entities listed in Europe. Coefficients for the SMB and the HML factors are only significantly positive for the LPX Buyout Index, which is potentially because data for the SMB and HML factors were only available for the US and the LPX Buyout Index has greater exposure to the US market.224 The positive factor loadings indicate that LPE returns are partly explained by investments into small and value firms. Finally, the weekly Fama-French three-factor-alphas, which are defined as the difference between the actual return and the return predicted by the Fama-French model, are insignificant in all model specifications and translate into annual alphas between -0.05% and 1.67%. In conclusion, LPE securities generated positive returns between 4.22% and 8.48% annually but the returns earned are to a great extent compensation for the systematic risk incurred and LPE entities add only little value on top of the market return. .
3.2 Event study methodology To examine more directly whether value is generated for investors through acquisitions and divestments of portfolio companies, the abnormal returns (ARs) of LPE entities on the days surrounding the announcement of a transaction are measured in an event study. Given that the market is efficient and stock prices thus incorporate all available information, the information content of an event, in this case of the deal announcement, will be evaluated by the market and will be reflected in the stock price immediately.225 The event study methodology is based on the research design by Brown and Warner (1985).226 First, the normal return is determined. To prevent the normal return estimates to be affected by the event itself the estimation period for the normal return includes the days t = 220 to t = -21 before the day of the transaction announcement. The abnormal return (ARit) for LPE entity i on day t relative to the event date (t = 0) is the difference between the actually observed return (Rit) and the expected normal return (E(Rit|Xt)) conditional that the announcement had not taken place:
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ARit = ε it* = Rit − E(Rit | X t )
(1)
The market and the constant mean return model are applied to derive the normal return. Under both models the daily returns are required to be jointly multivariate normal and independently and identically distributed over time, which can be assumed under the central limit theorem given a long enough estimation period (>30 days).227 The constant mean model presumes that the average return of a listed entity does not change over time, while the market model establishes a linear relation between the entity’s return and the market return.228 The market model is the more sophisticated model and potentially improves the parameter estimates of the test statistics since the entities’ nor224 225 226 227 228
See here and following Jegadeesh/Kräussl/Pollet (2010), pp. 24-26. See Campbell/Lo/MacKinlay (1997), p. 149. See here and following Brown/Warner (1985), pp. 6-8. See Campbell/Lo/MacKinlay (1997), p. 154. See MacKinlay (1997), p. 15.
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mal return variance can be reduced by eliminating the variance induced by the market return.229 In practice, however, they often lead to comparable results. The constant mean model is formally: Rit = μi + ξit ,
E(ξit ) = 0 ,
(2)
Var(ξit ) = σ ξ2i ,
where μi it the average logarithmic return for the listed entity i, Rit its logarithmic return on day t and ξit is the error term of the equation. The market model is given by:
Rit = α i + βi × Rmt + ε it , E(ε it ) = 0 ,
(3)
Var(ε it ) = σε2i ,
where Rit is the log return of security i and Rmt the market log return at time t, respectively. i, i and σε2i are the parameter estimates of the OLS regression over the estimation period. ε it is the disturbance term of the equation. If the LPE securities do not trade synchronously with the market, the i estimate will be downward biased. Such a bias should, however, not cause problems within the event study, as the bias is neutralized by an upward bias in the i estimate.230 The abnormal returns for the single announcements of interest are subsequently aggregated assuming that they are not correlated, which is generally the case when event windows, i.e. the days surrounding the event date and the event date itself, do not overlap.231 The transaction announcements of the LPE entities in the sample are spread over the period of interest and in the few cases232, where event windows do overlap across different entities, it can still be assumed that the announcement returns are independent of each other. Hence, the announcement of a transaction by one LPE entity should not affect the return of another LPE entity that also announces a transaction and hence, ARs would not be biased. The average abnormal return on day t across a sample of N announcement events can be calculated as: N
1 AR t = ε = ε *it . N i =1
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* t
(4)
The cumulative abnormal return (CAR) is the sum of the average abnormal returns on the days from t1 to t2 in the event window. The CAR is of interest besides the AR on the event date itself, due to possible leakage of information before the announcement and slow processing of the new information after the announcement. The CAR over an interval [t1;t2] can be written as follows: t2
CAR[ t1 ;t 2 ] = AR t . t = t1
229 230 231 232
See Campbell/Lo/MacKinlay (1997), p. 155. See Brown/Warner (1985), p. 16. See Campbell/Lo/MacKinlay (1997), p. 161. Event dates are the same across different entities for 8.0% of all acquisition and 3.8% of all exit announcements.
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(5)
Under the null hypothesis the announcement of an acquisition or divestment of a portfolio company has no impact on the LPE vehicle’s value and observed returns are only by chance different from zero. Therefore,
H0 : CAR[t1 ;t 2 ] = 0 . Using a t-test, the test statistics becomes:
t=
CAR[t1 ;t 2 ] N
,
(6)
d σ 2 N 2 i=1 εi
where d is the number of days in the event window. To test the significance of abnormal returns based on the market model, a nonparametric rank test following Corrado (1989) is conducted as a robustness check.233 The rank test relaxes the assumption about the normal distribution of abnormal returns. The average normal rank is given by:
L 241 + 0.5 = + 0.5 = 121 , 2 2
(7)
where L is the number of days from t = -220 to t = 20. The abnormal returns ARit from days t = -220 to t = 20 for each announcement event are ranked according to their magnitude. The average abnormal rank on day t across N announcement events is then: N
1 AK t = (K it −121) , with K it = rank(ARit ) and ARit ≥ ARij K it ≥ K ij . N i =1
(8)
Under the null hypothesis the cumulative abnormal rank over the event window is only by chance different from zero. However, if there are significant (positive) abnormal returns in the event window, they will have higher ranks than the average normal return and the rank deviation becomes larger. The test statistic for d days in the event window from t1 to t2 is formally: t2
AK
t
t = 20
1 2 , with σ = AK t . 2 L t =−220 d × σK
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t =t1
2 K
(9)
Additionally, the generalized sign test following Cowan (1992) is applied to determine whether the percentage w of events with positive CARs is significant.234 The normal percentage pˆ of positive returns is defined as:
233 234
See here and following Corrado (1989), pp. 387- 388. See here and following Cowan (1992), pp. 345-346.
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pˆ =
N −21 1 if ε *it > 0 1 1 , with . S S = jt N j =1 200 t =−220 jt 0 otherwise
(10)
The z-test statistics of the generalized sign test is as follows: z=
w − Npˆ . npˆ × (1 − pˆ )
(11)
Differences in CARs of subsamples like varying types of entry, exit and strategic decisions will be tested similar to the test of difference used by Chang (1998). SCARj is the standardized CAR of subsample j.235 The test statistics is formally: z=
SCAR[ t1 ;t 2 ]1 − SCAR[ t1 ;t 2 ] 2 t 2 − t1 +1 t 2 − t1 +1 + N1 N2
, with SCAR j =
CAR[ t1 ;t 2 ] Nj
.
(12)
d 2 2 σεi N j i=1
In a cross-sectional regression with the CARs across the acquisition and divestment announcements as the dependent variable the influence of firm and deal specific characteristics on the size of CARs will be tested by means of an OLS regression.236 A t-statistics with White heteroscedasticity consistent standard errors is used to determine statistical significance of the coefficients of the linear regression model.
3.3
Results of the event study
In the following, the results of the event study will be presented separately for acquisition and exit announcements. The returns to LPE vehicles will be further analyzed in univariate comparisons by the types of entry and exit as well as strategic decisions. Control variables are introduced in a multivariate regression with the CARs as the dependent variable.
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3.3.1 Acquisition announcements The CARs for the whole sample of acquisitions over different event windows are displayed in Table 5. The mean CARs237 around the announcement are significantly positive for the longer event windows [-2;+2], [0;+2] and [-2;+7]. This indicates that some leakage of the information takes place before the announcements and news are slowly incorporated into the market price after the acquisition announcement. Consistent with the t-statistics for the constant mean and the market model, the Corrado rank test and the generalized sign test for the percentage of positive CARs is statistically significant.
235 236 237
See MacKinlay (1997), p. 24. See Campbell/Lo/MacKinlay (1997), pp. 173-174. If not stated otherwise, mean CAR and CAR are used interchangeably in the following.
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Tab ble 5: CARs tto acquisition n announcemeents.
***, ** and * ddenotes significannce at the 1%, 5% % and 10% level respectively r (two-tailed test).
The table preesents the CA ARs over varioous event winndows to 313 acquisition a annnouncementss by LPE entitties. 13 of thee 326 announccements are noot included duue to insufficiient trading daays prior to thhe announcem ment and thus, lack of infor-mation to determine the noormal return. Normal returnns are determ mined using booth the constannt mean and m market model.. Positive perccentage denottes the ratio of observed poositive CARs for the indiviidual events and a the numbeer of observa-tions. Z-stat is i the test stattistic for the peercentage of ppositive CARss using the genneralized signn test.
Figure 5 shhows the CA ARs for thee constant m mean and thee market moodel for thee days t = -220 to t = 20.. While the CARs are positive annd significannt at a 10% % level for the window w [-2;+7], tthe positivee announcem ment effect ceases on thhe eighths dday followiing the annoouncement. This mighht be causedd by new infformation reeleased to thhe market thhat is unrelated to the acquisition event itselff. Appendixx 5 provides a table with h the exact ARs and C CARs as wells as ranks, median returns and ppositive per-centages foor days t = -20 - to t = 200.
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Figure 5: Mean CAR Rs to acquisition announccements.
The graph deepicts the meaan CARs from m day t = -20 to day t = 200 based on thee constant meean and markeet model. Thee CARs displaay a steep increease on the daays surroundinng the event date d (t = 0).
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The positive CAR over the event window [-2;+2] of 0.58% (median of 0.08%) for the market model shows that the market reacts on average positive to the announcement of acquisitions. The findings suggest that LPE entities are expected to create value on the portfolio firm level and also for its investors after costs. However, only slightly more than 50% of all events showed positive CARs and the median CAR is lower than mean CAR. Thus, some events impact the mean CAR more than others and the distribution of CARs is positively skewed. Since some specific type of acquisitions might drive CARs, the sample is partitioned into the identified different ways of entry and the CARs for these entry modes are compared. Because the constant mean and the market model produce similar results as depicted in Figure 5 with respect to CARs, only the market model is chosen for the univariate comparisons due to lower standard deviation in normal returns. Table 6 presents the CARs for distinct entry types for the event windows [-1;+1] and [-2;+2]. CARs are significantly positive with 0.66% for MBOs (Panel A) and 1.50% for public-to-private takeovers (Panel E) in the [-2;+2] window. For the latter, the event window [-5;+2] is additionally included as especially for public targets rumors about a possible takeover might have spread earlier than for private targets. The strongly significant CAR of 3.38% supports this conjecture. Furthermore, the percentage of positive CARs to LPE entities upon the takeover announcement of a public target is higher in all specifications of the event window and indicates that CARs seem not to be driven by only few public-to-private deals.
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Table 7 provides an additional breakdown of the differences in CARs by entry type. Differences between MBOs and MBIs are not clear-cut but depend on the event window chosen. While CARs are higher for MBIs in the window [-1;+1], the difference is neither significant nor does the majority of LPE entities incur positive CARs upon announcement of an MBI. CARs are significantly higher for MBOs by 0.16% in the window [-2;+2], but the difference is economically rather small. Results are more insightful when the sample is divided by the organizational form of the takeover target. CARs to both whole company and secondary BOs are significantly lower than CARs to publicto-private BOs independent of the event window. The results are in line with the previously developed surmise that whole company BOs and secondary LBOs offer fewer opportunities for governance improvements and bargaining about the purchase price. Divisional BOs induce a more positive market reaction than whole company BOs, whereas the difference between divisional and secondary BOs is only significant in window [-1;+1]. Overall, whole company BOs seem to offer the least and public-to-private BOs the most potential for value creation. This first assertion of the univariate comparison is tested in a multivariate regression controlling for firm and deal specific characteristics.
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Tablle 6: CARs too acquisition aannouncements for differrent types of eentry. Window
Mean CAR (%)
Pooled standard deviation (%)
t-stat
Positive percentage (%)
z-stat
No. of observations
[-1;+1] [-2;+2]
0.2165 0.6645
0.2258 0.2915
Panel A: MBO 0.9586 2.2796**
50.6757 54.7297
1.0707 2.0599**
148 148
[-1;+1] [-2;+2]
0.4278 0.5010
0.3665 0.4732
Panel B: MBI 1.1673 1.0589
46.6667 50.9091
0.4288 1.5241*
165 165
[-1;+1] [-2;+2]
0.1364 0.3603
Panel C: Whole company 0.3337 0.4087 0.4308 0.8362
45.6522 54.3478
0.1540 2.2073**
138 138
[-1;+1] [-2;+2]
0.5789 0.7518
Panel D: Divisional buyout 0.4572 1.2662 0.5902 1.2738
48.4536 50.5155
0.8320 1.2408
97 97
[-1;+1] [-2;+2] [-5;+2]
0.8755 1.4948 3.3776
Panel E: Public-to-private 0.5777 1.5154 0.7459 2.0041** 0.9435 3.58***
68.4211 57.8947 78.9474
1.6404* 0.7227 2.5581***
19 19 19
0.1916 0.5056
Panel F: Secondary LBO 0.4055 0.4726 0.5235 0.9658
50.0000 50.0000
0.3194 0.3194
58 58
[-1;+1] [-2;+2]
***, ** and * denotes significance at the 1%, 5% and (two-tailed test). oe n 10% level respectively o-tai i
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nts is dividedd into MBOs aand MBIs (Paanel A and B)) The table preesents the CA ARs when the sample of accquisition even and when it iis divided intoo whole comppany, divisionaal, public-to-pprivate and seccondary BOs (Panel C to F). One portfo-m ded in panels C to F lio firm was acquired by means of a privvatization andd is not includ
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533
Table 7: Differencees in CARs too acquisition announcemen a nts by type of entry. MBO MBI Whole company Divisional Buyout Public-to-private
Divisional Buyout Public-to-private CAR differences (%) in window [-1;+1] 0.2113 -0.4425*** -0.7391*** -0.2966 -
CAR differences (%) in window [-2;+2] -0.1635*** -0.3915* -
MBI Whole company Divisional Buyout Public-to-private
Secondary LBO
-1.1345** -0.743* -
-0.0552 0.3873*** 0.6839**
-0.1453 0.2462 0.9892**
***, ** and * denotes significance at the 1%, 5% and 10% level respectively (two-tailed test).
hows the diffeerences in CA ARs for MBIs over MBOs and for wholee company, divisional, d pubblic-to-privatee The table sh and secondarry BOs.
Table 8 repports the reesults of thee multivariaate setting using u an OL LS regressioon. The CAR Rs over thee window [-2;+2] for eaach observeed acquisitioon announccement are uused as the dependent variable too allow for a dispersed market reacction over tiime. The foollowing genneral regresssion modell with somee variations in the inclusion of expllanatory varriables for eeach model is applied: 5
CAR[ −2;+2],i = constantt +
∑b
j
x entrydummy e yjj,i + b6 x synndicationduummyi
j =1
+ b7 x log g(LPE’s agge)i + b8 x L LPE’s P/B raatioi + b9 x log(target’’s EV)i
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+ b10 x lo og(target’s EV2)i + b11 x log(LPE’’s market caap)i + firm ddummies + ei Model 1 shhows the results when the CARs aare regresseed on the enntry dummiees includingg firm fixedd effects to control for unobservabble and tim me-invariantt LPE entitty specific ccharacteristtics. In linee with the unnivariate ressults, only the t coefficieent on publlic-to-privatte deals is significantlyy positive att the 5% levvel and rem mains signifiicant for alll model speecifications using diffeerent controol variables.. Variables to t control for f reputatioon and learrning are included in M Model 2 andd control vaariables forr size are furrther added d in Models 3 and 4. W When controolling for thee target’s ennterprise vaalue, 43 ob-servations are lost beccause of laccking inform mation abouut the EV. T The coefficieents for the three repu-tation variaables are neegative in Model M 2 to Model M 4. Onnly the coeffficient for the P/B ratiio in Modell 4 is signifi ficantly negative but thhe p-value oof 0.18 for the syndicaation coeffiicient is quiite low andd attributes some s explan natory pow wer to the syyndication dummy. d Heence, the ovverall findinngs suggestt that CARss and reputaation are neegatively related. Furthhermore, thee coefficiennt for the L LPE entity’ss market cappitalization is significanntly negativve and attribbutes to the assumptionn that CARss are higherr for smallerr LPE entities, for whiich informaation asymm metries betw ween the market m and tthe firm aree higher. Whhen controllling for the target’s EV V in Modell 4, the entryy dummy coefficients c are signifi-cantly posiitive for wh hole companny, public-tto-private annd secondarry BOs. Addditionally, the p-valuee for the divvisional BO coefficientt indicates tthat there iss only a 15.3% chance that the paarameter es-timate is not n differentt from zero. The coeffi ficients in Model M 4 for the entry tyypes by orgganizationall form of thee takeover target t suppoort the resuults of the unnivariate coomparisons. Whole com mpany BOss
54
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have the loowest and public-to-pr p rivate BOs the highest coefficiennts, while divisional d B BOs and se-condary BOs range in n between. Whether a portfolio fiirm was bought by meeans of an M MBO or ann MBI cannoot explain th he CARs. The T significcantly positiive CARs fo for MBOs inn the univarriate settingg are not robbust when other o explannatory variabbles are inccluded. Interrestingly, thhe relation bbetween thee target’s EV V and the CAR C appeaars to be noon-linear ass shown in Model 4. T The coefficiient for thee simple targget’s EV is negative (pp value of 00.15) and poositive wheen target’s EV E is squarred (p-valuee of 0.15). This T impliess that CARss are higherr for very sm mall and very large targets but low wer for me-dium-sizedd targets. A discussion on this findding is proviided in secttion 3.5. Ta able 8: Regreession results on CARs to acquisition aannouncemen nts.
Dummy = +1 if MBI and = -1 if MBO Whole company
Divisional BO
Public-to-Private
Secondary LBO
Model 1 b/se/p -0.0012 0.0019 (0.5223) 0.0008 0.0013 (0.5307) 0.0028 0.004 (0.4888) 0.0164 0.0062 (0.0146)** 0.0029 0.0037 (0.4467)
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
CAR[-2;+2] Model 2 Model 3 b/se/p b/se/p -0.0013 0.0015 0.0021 0.0023 (0.5586) (0.5193) 0.0006 0.0032 0.0012 0.003 (0.6097) (0.2939) 0.0027 0.0052 0.0041 0.0048 (0.5099) (0.2874) 0.0147 0.0199 0.0056 0.0056 (0.0152)** (0.0015)*** 0.0022 0.009 0.0036 0.0042 (0.5497) (0.0421)** -0.0058 -0.0076 0.0047 0.0061 (0.2313) (0.226) -0.0212 -0.0099 0.0263 0.0214 (0.4277) (0.6484) -0.0045 -0.0038 0.003 0.0022 (0.1423) (0.1009) -0.0045 0.0056 (0.4353)
log (target's EV2)
log (LPE's market cap)
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constant
Firm fixed effects Observations R2
0.0031 0.0013 (0.0205)** yes 313 0.0064
0.0347 0.0312 (0.2769) yes 313 0.0213
-0.0287 0.0133 (0.0407)** 0.0968 0.0418 (0.0289)** yes 270 0.0568
Model 4 b/se/p 0.0011 0.0024 (0.653) 0.0093 0.0054 (0.0957)* 0.0115 0.0078 (0.1528) 0.0255 0.0059 (0.0002)*** 0.0146 0.0058 (0.0175)** -0.0083 0.006 (0.1785) -0.0101 0.0218 (0.6468) -0.0037 0.0021 (0.0921)* -0.8547 0.5721 (0.1477) 0.4251 0.2867 (0.1506) -0.0281 0.0133 (0.0444)** 0.0898 0.041 (0.0382)** yes 270 0.0606
CAR[-1;+1] Model 5 b/se/p 0.0013 0.0021 (0.5245) 0.0209 0.004 (0)*** 0.024 0.0056 (0.0002)*** 0.0293 0.0077 (0.0008)*** 0.0243 0.0043 (0)*** -0.0089 0.0045 (0.056)* -0.0178 0.023 (0.4475) -0.0031 0.0014 (0.0356)** -1.1053 0.5035 (0.0376)** 0.5538 0.2526 (0.0379)** -0.0204 0.0065 (0.0041)*** 0.0529 0.0346 (0.1395) yes 270 0.0654
***, ** and * deenotes significancce at the 1%, 5% and 10% level respectively (two-ttailed test).
The table shoows the coeffficient estimates (b), robust standard erroors (se) and p--values (p) of explanatory vvariables. Thee CAR for eveent i in the winndow [-2;+2] is used as thee dependent vaariable througghout models 1 to 4 and thee CAR [-1;+1]] in Model 5. A dummy varriable that equuals 1 if the BO O was a privattization is om mitted.
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ARs over thhe window [[-1;+1] as a Model 5 of Table 8 allso provides the regresssion resultss for the CA robustness check. Coeefficients reemain nearlly the same and many of them beccome even significant.. The overalll fit of the model to explain e the vvariation inn CARs as m measured by the R2, hoowever, re-mains limiited independent of thhe model. A Appendix 6 provides tthe results for further robustnesss checks. Cooefficients of o the explaanatory variables channge only sligghtly whenn firm fixedd effects aree not includeed and when n year, porttfolio firm’ss industry seector or couuntry dumm mies are usedd. The R2 iss even lowerr when inclu uding these dummies innstead of firrm dummiees. Considerring the firm m dummies,, 6 of the 266 firm fixed d effects aree significantt. These sixx firms accoount for 28.3% of all acquisitions.. Among theem are “HgC Capital Truust plc” and “Dunedin E Enterprise Investment Trust T plc”. IInteresting-ly, these arre two of th he three pubblic funds llisted in thee UK. The other four firms f only account forr 6.1% of the sample. A correlationn matrix forr different variables v cann be found in i Appendixx 7.
3.3.2 Exit announ ncements After a LP PE entity accquired a poortfolio com mpany, the L LPE entity rreports eithher only the total valuee of all the firms f in the portfolio orr provides iinvestors wiith a rough estimate foor each com mpany’s val-ue, which often relies on historical cost orr expected multiples. H Hence, the uncertaintyy about thee portfolio fiirm’s value resolves onnly upon exxiting the invvestment, w when a finall valuation ttakes place.. Table 9 ouutlines the market’s m reacction in term ms of CARss to those exxit announccements. Table 9: CAR Rs to exit ann nouncementss. Window
Mean CAR Pooled standard (%) deviation (%)
[0] [-1;+1] [-2;+2] [ 0;+2] [-2;+7]
0.352 0.7453 0.4548 0.5654 0.1065
0.1945 0.3369 0.435 0.3369 0.6151
[0] [-1;+1] [-2;+2] [ 0;+2] [-2;+7]
0.3803 0.7179 0.4746 0.5646 0.0642
0.1812 0.3139 0.4053 0.3139 0.5731
t-stat
Median CAR Corrado rank Positive (%) t-stat percentage (%) Constant mean model 1.8094* 0.0253 1.6621* 50.8108 2.212** 0.0363 2.3758** 52.973 1.0455 -0.1846 0.7162 49.1892 1.6781* -0.0174 1.5712 51.8919 0.1732 -0.6512 -0.5633 50.2703
2.0983** 2.2869** 1.1711 1.7985* 0.1119
Market model 0.0179 2.2197** 0.1011 3.2423*** -0.1211 1.912* 0.0213 2.3062** -0.6193 0.6955
50.2703 53.5135 48.6486 51.3514 49.7297
z-stat
No. of observations
1.4104* 2.0008** 0.9675 1.7056** 1.2627
185 185 185 185 185
1.1171 2.002** 0.6747 1.4121* 0.9696
185 185 185 185 185
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***, ** and * ddenotes significannce at the 1%, 5% % and 10% level rrespectively (twoo-tailed test).
The table preesents the CA ARs over vario ous event winndows to 185 exit announccements by LP PE entities. N Normal returnss are determined using both h the constant mean and maarket model. Positive P percenntage denotes the ratio of oobserved posi-tive CARs foor the individu ual events and d the number of o observationns. Z-stat is thhe test statisticc for the percenntage of posi-tive CARs ussing the generralized sign teest.
Similar to the resultss for acquissition annouuncements, CARs are significanttly positive for certainn specificatioons of the event e window. The m market’s reacction is lesss dispersed over time and the re-turns are significantly s y different from zero on the annnouncementt day itself for both thhe constantt mean moddel with 0.35% and thee market moodel with a CAR of 0.38%. The percentage of positivee returns, hoowever, is only o significcant for the constant m mean model and the CA ARs are positive on thee announcem ment day itsself only foor few moree than half oof the obseervations. CARs in the window [-56
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1;+1] are significantly s y positive att the 5% levvel and thiss result is coonfirmed byy the Corraddo rank testt and the geeneralized sign test forr the percenntage of possitive returnns. The devvelopment oof the CAR R from day t = -20 to t = +20 can be b seen in Fiigure 6. Apppendix 8 prrovides a tabble with thee exact ARss and CARs as wells ass ranks, meddian returnss and positivve percentagges for dayss t = -20 to t = 20. Thee R around the announceement day shhows that thhe market rreacts on avverage posi-steep increease in CAR tive to exiit announceements and that there are thus m more successsful than unnsuccessfull exits. No-netheless, the deviatio on between the mean aand mediann CARs as w well as the percentage of positivee CARs flucctuating aro ound 50% suggests thhat some evvents have a greater iimpact on CARs thann others. Theerefore, the sample is divided d into different caategories too conduct unnivariate comparisons. Figu ure 6: Mean CARs to exitt announcemeents.
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The graph deepicts the meaan CARs from m day t = -20 to day t = 200 based on thee constant meean and markeet model. Thee CARs displaay an increasee on the days surrounding tthe event datee from t = -1 to t = -2. Thhe market pricce of the LPE E securities, hoowever, graduually decreasess again after thhe announcem ment.
The categoories are baased on the type of exiit, the holdiing period aand the straategic decisions imple-mented in the portfoliio companies during thhe holding period. Oncce again, thhe market m model is ap-plied to deetermine thee normal retturns due too higher varriance reducction. The reesults of thee univariatee event studiies over varrious event windows aare shown in i Table 10. First, the sample is ddivided intoo the identiffied exit chaannels. Thee CARs forr announcem ment of IPO Os are highh comparedd to all oth-ertype of exits e but aree not significant due to a low numbber of obserrvations andd hence, a hhigh pooledd standard deeviation. The event window [-5 5;+2] for IP POs is incluuded to eliccit whether informationn about a poossible IPO O has been sppread in thee market priior to the annnouncemennt, which m might be the case if com mmunicationn with potenntial investo ors took placce prior to tthe announcement. Thhe insignificcant CAR foor this win-dow, howeever, does not n support the t leakage of informattion in the rrun-up of thhe announceement.
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T Table 10: CA ARs to exit an nnouncementss for differen nt types of exiit. Window
Mean CAR (%)
Pooled standard deviation (%) 2.1366 2.7584 3.4891
t-stat
Positive percentage (%)
Panel A: IPO 0.8477 0.7860 -0.0875
[-1;+1] [-2;+2] [-5;+2]
1.8112 2.168 -0.3054
[-1;+1] [-2;+2]
1.2198 1.4823
[-1;+1] [-2;+2]
0.3718 -0.2647
Panel C: Secondary LBO 0.5295 0.7022 0.6835 -0.3872
[-1;+1] [-2;+2]
-1.9753 -4.5213
Panel D: Insolvency 1.7323 -1.1402 2.2364 -2.0217**
z-stat
No. of observations
60 60 60
0.4293 0.4293 0.4293
5 5 5
59.2233 56.3107
2.7574*** 2.164**
103 103
50 40.625
0.6383 -0.8665
64 64
23.0769 23.0769
-1.8807** -1.8807**
13 13
[-1;+1] [-2;+2]
Panel E: Holding period = 5.57 years (fourth quartile) 1.2972 0.5892 2.2018** 51.3514 0.8671 0.7606 1.1400 51.3514
0.6897 0.6897
37 37
[-1;+1] [-2;+2]
1.3962 1.0681
Panel G: Refocusing 0.996 1.4017 1.2859 0.8307
65.3846 57.6923
1.9104** 1.1242
26 26
[-1;+1] [-2;+2]
0.8263 0.5676
Panel H: Organic growth 0.5184 1.5939 0.6693 0.8480
59.3023 55.814
2.2464** 1.5984*
86 86
[-1;+1] [-2;+2]
0.8745 0.2911
Panel I: Transactional growth 0.5929 1.4749 53.1915 0.7654 0.3803 48.9362
0.7711 0.1869
47 47
Panel B: Trade sale 0.3887 3.1382*** 0.5018 2.9539***
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***, ** and * deenotes significancce at the 1%, 5% and 10% level reespectively (two-ttailed test).
The table preesents the CA ARs when thee sample of exxit events is divided d categoories based onn exit type (Panel A to D),, holding periood (Panel E annd F) and straategic decisionns (Panel G too I). Informatiion about the holding periood was availa-ble for 148 events and aboout the strategiic decisions foor 160 events out of the 1855 events.
The annouuncement of o trade salee exits gennerates significantly poositive CAR Rs independdent of thee event wind dow and th he percentagge of positiive CARs to t the singlle announcements is aadditionallyy significantt. In contrasst, CARs too secondary LBOs are not significcantly differrent from zero and thee announcem ment of an insolvent poortfolio com mpany leads to significaantly negatiive CARs of -4.52% inn the window w [-2;+2]. The T differennces in CAR Rs betweenn the exit chhannels are presented inn Table 11.. 58
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Insolvenciees generate significantlly lower CA ARs than alll other typees of exits, which w provides supportt for the theoory that insolvencies arre on averagge not expeected based on prior repports of the LPE entityy and that dooubt is cast on the LPE E entity’s skkills. Furtheermore, tradde sales seem m to be preeferred overr secondary LBOs by the t capital market m as inndicated byy the signifiicantly highher CARs, w whereas thee difference between CA ARs to IPO Os and trade sales is neither large nnor significaant. In a seconnd step, the sample waas divided iinto the exiit events off the 25% portfolio p firrm with thee shortest (P Panel E) and d the 25% portfolio p firm ms with thee longest hoolding periood (Panel F)). However,, the differennces in CAR Rs depend on o the speciification of the event w window and the length oof the hold-ing period does not ap ppear to reveal informaation about tthe success of the invesstment. Third, the CARs to exit e announccements weere determinned accordiing to the sstrategic deccisions thatt were madee during thee holding peeriod. Whilee the percenntage of possitive CARss to the exitt announce-ments of portfolio p firm ms that folllowed a reffocusing strrategy is siggnificant, thhe CARs to refocusingg are not siggnificantly higher h than for other sstrategies. Hence, H it caannot be cooncluded froom the uni-variate com mparisons th hat any of thhe strategies has a greaater influencce on exit suuccess. Ta able 11: Diffeerences in CA ARs to exit an nnouncementts by type of exit e Trade sale
Short holding Organic growth period CAR differences (%) in window [-1;+1] 1.4394 3.7865** 0.848*** 3.1951*** 2.3471*** 0.0777** 0.5699 -
Secondary LBO
IPO Trade sale Secondary LBO Long holding period Refocusing Organic growth
0.5914
IPO Trade sale Secondary LBO Long holding period Refocusing Organic growth
0.6857 -
Insolvency
Transactional growth
0.5217 -0.0482
CAR differences (%) in window [-2;+2] 2.4327 6.6893*** 1.747*** 6.0036*** 4.2566*** -0.8255 0.5005 -
0.7770 0.2765
***, ** and * dennotes significance at the 1%, 5% aand 10% level resspectively (two-taailed test).
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Rs for differennt exit channells, holding perriods and strattegic decisions. The table shoows the differrences in CAR
In a multivvariate OLS S regressionn, the findinngs of the univariate u ccomparisonss are tested for robust-ness by coontrolling fo or deal and firm speciffic characterristics. The general moodel for thee regressionn can be writtten as: 4
CAR[ −2;+2],i = constantt +
b
j
x exitdummy e dicationdum mmyi j,ii + b5 x synd
j =1
+ b6 x log g(LPE’s agge)i + b7 x L LPE’s P/B raatioi + b8 x log(target’’s EV)i
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+ b9 x log(target’s EV2)i + b10 x log(LPE’s market cap)i + b11 holdingperiodi
+
14
b
j
x strategydummyj,i + b15 x totalstrategicdecisions +firm dummies + ei
j =12
The CARs in the window [-2;+2] are used as the dependent variable, as some exit variables, for example IPOs and insolvencies, display a more dispersed market reaction. The regression results are provided in Table 12. Model 3 shows that when controlling for reputation as well as for target’s and LPE entity’s size, only the coefficients for the target’s EV and for the LPE entities’s age are significant. However, p-values around 0.15 for other coefficients can still be regarded as low considering the rather small sample size of events. The results suggest that exits via an IPO with a coefficient of 3.3% are preferred over trade sales with a coefficient of 1.6%. In Model 4, the holding period is included but since it fails to explain the CARs and reduces the number of observations, it is dropped in follow-on regressions. In Model 5, the squared target’s EV is introduced. Interestingly, the explanatory of the IPO dummy decreases thereupon and the coefficient for target’s EV turns negative. The significantly negative coefficient for age gives support for the negative relation between CARs and reputation. Although not significant, the positive coefficient for the LPE entity’s market capitalization might indicate that larger LPE entities have more exit success. The coefficient is positive despite the counteractive effect of expected lower information asymmetries for larger LPE entities and a reduced signaling effect of transactions. Model 6 is a variant of Model 5 with the insolvency dummy variable as the omitted variable instead of the secondary LBO dummy variable. The coefficients denote an ordering of exit preferences with IPOs as the first, trade sales the second and secondary LBOs the third most preferred type of exit. Strategic decisions on the other hand, as presented in Model 7, cannot explain CARs and thus, exit success.
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Robustness checks are shown in Model 8 using the CARs[-1;1] as the dependent variable and in Appendix 9. A correlation matrix is provided in Appendix 10. The results are mostly robust to the use of year, country and industry dummies instead of firm dummies. It is noteworthy that the IPO dummy variables looses significance when year dummies are included, which potentially signals that IPOs are only preferred when market conditions are favorable. Four firm fixed effect coefficients are significant and these four firms only account for 2.7% of all exit events so that firmspecific effects should be of minor importance.
60
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Table 12: Regression R results on CAR Rs to exit ann nouncements
Insolvency
Model 1 b/se/p
Model 2 b/se/p
Model 3 b/se/p
CAR[-2;+2] Model 4 b/se/p
Model 5 b/se/p
-0.0526 0.031 (0.104)
-0.0558 0.0332 (0.1067)
-0.0516 0.0342 (0.146)
-0.0655 0.0423 (0.1355)
-0.0522 0.0364 (0.166)
Secondary LBO
Trade sale
IPO
0.0154 0.0105 (0.1569) 0.0409 0.0165 (0.0214)**
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
0.0141 0.0101 (0.1783) 0.0377 0.021 (0.0868)* -0.0071 0.0045 (0.1321) -0.0144 0.0207 (0.4919) 0.0067 0.0092 (0.4687)
log(target's EV)
0.0161 0.0108 (0.1501) 0.033 0.0227 (0.1594) -0.0057 0.0058 (0.3394) -0.0353 0.0192 (0.0784)* 0.0018 0.0074 (0.8059) 0.0116 0.0041 (0.0101)**
0.0246 0.0138 (0.0892)* 0.0431 0.028 (0.1372) -0.0014 0.0077 (0.8536) -0.0394 0.0296 (0.196) 0.0043 0.0091 (0.637) 0.0107 0.0056 (0.0703)*
0.0181 0.0126 (0.1644)
0.0168 0.0099 (0.1054) 0.0021 0.0026 (0.4315)
log (target's EV2)
log (LPE's market cap)
Holding period
0.0151 0.0101 (0.1496) 0.029 0.0225 (0.2108) -0.0069 0.0064 (0.289) -0.0366 0.0184 (0.0586)* 0.0017 0.0066 (0.8021) -1.8911 1.1232 (0.1064) 0.952 0.5614 (0.104) 0.0213 0.0147 (0.1606)
Model 6 b/se/p
0.0522 0.0364 (0.166) 0.0672 0.0379 (0.0896)* 0.0812 0.0351 (0.0302)** -0.0069 0.0064 (0.289) -0.0366 0.0184 (0.0586)* 0.0017 0.0066 (0.8021) -1.8911 1.1232 (0.1064) 0.952 0.5614 (0.104) 0.0213 0.0147 (0.1606)
-0.0056 0.0047 (0.2472) -0.0407 0.0209 (0.0642)* -0.0015 0.0081 (0.851) -2.0796 1.3474 (0.137) 1.0463 0.6736 (0.1346) 0.0269 0.0192 (0.174)
0.0037 0.0068 (0.5876) 0.0129 0.0159 (0.4241) -0.0041 0.007 (0.5639) -0.057 0.0295 (0.0663)* -0.0058 0.0053 (0.2884) -0.5572 0.9281 (0.5544) 0.2819 0.4628 (0.5487) 0.0266 0.024 (0.2798)
-0.0824 0.0513 (0.1222) yes 165 0.1406
0.0001 0.0124 (0.9909) -0.0095 0.0102 (0.3634) 0.0028 0.0082 (0.7337) -0.0295 0.0327 (0.3778) yes 145 0.056
0.0078 0.0332 (0.8169) yes 165 0.0682
Transactional growth
Total strategic decisions
Firm fixed effects Observations R2
-0.0016 0.0062 (0.8007) yes 185 0.0819
0.0128 0.0266 (0.6344) yes 179 0.0967
-0.0232 0.0293 (0.4373) yes 165 0.1234
-0.0286 0.03 (0.3495) yes 135 0.1633
-0.0302 0.0328 (0.3669) yes 165 0.1406
CAR[-1;+1] Model 8 b/se/p -0.0187 0.0305 (0.546)
Refocusing
constant
Model 7 b/se/p
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* ***, ** and * dennotes significancee at the 1%, 5% aand 10% level respectively (two-taailed test).
The table shoows the coeffficient estimates (b), robust standard erroors (se) and p--values (p) of explanatory vvariables. Thee CAR for eveent i in the win ndow [-2;+2] is used as thee dependent vaariable througghout models 1 to 7 and thee CAR [-1;+1]] in Model 8. A dummy varriable that equ uals 1 if the exxit was a seconndary LBO is omitted in Model M 1 to 6 annd Model 8. A dummy variaable that equals 1 if the exitt was an insolvvency is omittted in Model 77.
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3.4 Discussion
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The analysis of the capital market’s reaction to acquisition and exit announcements in general revealed on average positive CARs to LPE entities. Thus, the findings support the two hypotheses derived in section 2.5. First, positive CARs to acquisition announcements substantiate the theory that LPE entities absorb bidder-specific returns through the generation of value on the portfolio firm level and that they are able to buy portfolio companies at a discount. The profits generated through governance, operational and financial skills are translated into returns to investors as indicated by the positive CARs. Second, CARs to exit announcements signal that the final value generated through an investment into a portfolio firm can only be determined upon the divestment. The on average positive CARs to exits indicate that there are more successful than unsuccessful exits. However, the CARs upon transaction announcements in general do not exceed 1% and are economically rather small. On the one hand, the small market for LPE might be less efficient than the market for other asset classes and the available information are not fully incorporated into the market price, which is crucial for the use of the event study method.238 Furthermore, the surprise effect of a transaction might be limited. Since it is the business model of a LPE entity to invest into and divest companies, the CAR might only represent the transaction’s divergence from market expectations.239 On the other hand, the low CARs are in line with the rather low returns that just about compensate the investor for systematic risk as measured by the Fama-French three factor alphas and it implies that PE does add only little value on top of the required compensation for risk. However, it has additionally to be taken into account that CARs are not equal for different types of entry and exit decisions. Hence, different investment strategies are characterized with distinct potential for wealth generation. Within the acquisition events, a first distinction was made between MBOs and MBIs but no evidence was found for the superiority of either of the two entry ways. In contrast, the announcement of a public firm takeover triggers a more positive reaction than whole company, secondary or divisional BOs. Surprisingly, public-to-private deals were the least common type of takeover in the sample period. A possible explanation for this finding is that not only the reduction in agency costs through greater concentrated ownership and incentive alignment are important to enhance investor returns but also the opportunity to invest in undervalued targets that are not closely followed by equity market analysts. Such opportunities should be scarce in markets that are efficient most of the time but if existent can generate substantial returns reflected in the positive CARs. Support is provided in the multivariate regression Model 8 in Appendix 6, in which the explanatory power of the public-to-private dummy variables decreases, when year dummies are included. Moreover, the conjecture is in line with the finding of Guo et al. (2011), who observe insignificant operating performance increases in public-to-private deals, but large returns to the PE firm suggesting that PE firms indeed identify undervalued targets to delist them.240 The positive CARs to the acquisitions of public targets are interesting from another perspective. Many previous studies find negative CARs to corporate acquirers that announce the acquisition of a public target.241 One explanation is that LPE acquirers are different from strategic corporate acquirers in the sense that 238 239 240 241
See Cumming/Siegel/Wright (2007), p. 445. See Fuller/Netter/Stegemoller (2002), p. 1767. See Guo/Hotchkiss/Song (2011), pp. 503-507. See for example Fuller/Netter/Stegemoller (2002), p. 1779. Moeller/Schlingemann/Stulz (2005), pp. 771-772.
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managers of LPE entities are more selective when choosing targets and takeover premia are lower.242 Empire building is not an option as portfolio companies will be divested in the medium term and acquisitions do not take place to gamble for the resurrection of an underperforming acquiring company but because it is the business model of the LPE entity.243 While divisional and secondary BOs have about the same impact on CARs, whole company BOs have the least impact on CARs. A lower value creation capacity might be the underlying reason. As argued earlier bargaining is difficult when the selling party is better informed. Often whole company BOs result from a family owner’s need for succession planning rather than from turnaround needs.244 If companies are well run prior to the BO, they will be priced accordingly and it might be difficult to increase performance on top of current profitability figures. Nonetheless, the hypothesis that agency costs may not be reduced much further in whole company BOs can, at least for the smaller German sample, not be inferred. Different from what was expected, secondary BOs do not seem to perform as bad as whole company BOs. At the same time, IPOs and trade sales are preferred to exits via a secondary BO. This can stem from the selling PE firm’s need to dispose the portfolio company when an IPO or a trade sale is not possible. It sells the asset to another PE firm thereby accepting a lower transaction price. The favorable purchase price for the buying LPE entity then translates into a more positive CAR upon acquisition and a lower CAR for the selling party upon exit. Although the need to divest a portfolio firm is less pronounced in LPE due to its infinite life, the LPE entity might wish to sell the portfolio firm for other reasons such as a shortage of cash to make new investments. Since differences in CARs upon whole company, secondary and divisional BOs are not large, further evidence is needed whether there indeed exists are pecking order of entries. The IRRs to investments into portfolio companies exited via either an IPO, trade sale or secondary LBO found in Nikoskelainen and Wright (2007) hint at a possible pecking order of exits and the finding is confirmed in the study of Müller and Vasconcelos (2010), who analyze CARs to the different type of exit announcements.245 The univariate comparisons of CARs to distinct exit channels support the theory that IPOs might be preferred to trade sales and that trade sales are preferred to secondary LBOs. However, the sample of exit events consists only of five IPOs and generalizations cannot be made. Furthermore, the IPO dummy variable lost in explanatory power when controlling for size but also when including year dummies in the multivariate setting. Hence, an additional exit channel, the IPO, exists especially for larger portfolio companies during favorable market conditions. The IPO might not by itself be preferred but rather an existent additional exit channel is favored because it increases the negotiating power of the LPE entity vis-à-vis a potential corporate or other PE acquirer. In spite of higher costs the preparation of multiple exit opportunities, so called “dual-track” or “multi-track” exits, can significantly impact the exit success as more pressure can be exerted on interested parties to buy the portfolio company at a higher price.246 Instead of an exit, the LPE entity can further improve its negotiating position by indicating the possibility of a dividend
242 243 244
245 246
See Bargeron et al. (2008), p. 390. See Schneider/Spalt (2011), p. 28. For the smaller sample of German BO transactions, 34.1% of all whole company BOs were driven by the need of family succession planning. See Nikoskelainen/Wright (2007), p. 522. Müller/Vasconcelos (2010), p. 30. See Povaly (2006), p. 183.
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recapitalization to provide an attractive return to investors.247 The importance of multi-track exits cannot be neglected as recently seen in the sales process of “Kabel BW” by EQT, within which options for an IPO, for a secondary LBO and for continuance in the portfolio were held by EQT until the very final decision was made.248 Unfortunately, CapitalIQ does not provide information whether multi-track exits were available for the LPE entity but it would be of interest how they influence the CARs to exit announcements. Whether a single exit channel is more successful than another on a standalone basis or whether the number of simultaneous exit options determines exit success cannot finally be settled. It is noteworthy that the announcement of an insolvent portfolio company triggers a significantly negative CAR in spite of the negative correlation between holding period and the insolvency dummy variable (see Appendix 10). Although LPE entities appear to dispose poorly performing companies early and do not waste additional resources on the turnaround, the market does not recognize the announcement as a positive signal. In contrast, the reaction is potentially negative because the capital market did not expect that the portfolio company was unprofitable or because doubt is cast on the ability of the LPE entity to select portfolio companies that will not go bankrupt.
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Concerning the strategic decisions made, it was conjectured that organic growth might be the most appropriate strategy due to the high debt levels imposed on the portfolio companies and potentially less risky and less complex organic growth plans. Organic growth was also the most often applied strategy but neither organic growth nor transactional growth or refocusing can explain higher CARs and thus, exit success. Instead, the best strategy might be very much dependent on the characteristics of the underlying portfolio company and individually determined on a case-by-case basis. Hence, the investment and exit success is rather dependent on the suitability of the selected strategy for the portfolio company. Overall, information on the applied value drivers was drawn from the LPE entity’s annual reports. Therefore, they are self-reported and rely on the assumption that LPE entities actually report about the measures that were taken in the portfolio firms. This should mostly be the case for the greater strategic decisions but less for governance, financial or operative measures, which is why only the strategic decisions were implemented in the event study. Reputation and the extent to which the market has already learned about the LPE entities’ capabilities are negatively related to CARs. The market’s reaction to transaction announcements is limited for more reputable firms measured by syndication, age and the P/B ratio. Thus, overcoming information asymmetries and signaling deal making skills is especially important for the less reputable firms to adjust their valuation upwards, to increase the investor base and to raise capital in future share increases.249 In line, the significantly negative firm fixed effect for two of the three public funds listed in the UK might be explained by lower information asymmetries in the larger and potentially more sophisticated private equity market of the UK.250
247
248 249 250
In a dividend recapitalization the portfolio company takes up additional debt to pay a special dividend to the PE company. Handelsblatt, March 3, 2011. See Müller/Vasconcelos (2010), p. 19. See Brown/Kräussl (2010), p. 14.
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The target’s EV was eventually included as a control variable in the multivariate regression on the CARs and the results for both acquisition and exit CARs indicated a non-linear relationship. Smaller and larger transactions impact CARs more positively than medium-sized deals, which is in contrast to Nikoskelainen and Wright (2007) who find larger BOs to outperform smaller ones.251 They argue that the debt capacity of small firms is limited as their cash flows are more volatile and more effort has to be spent to achieve the same absolute return as in larger BOs.252 While this might be true, management can afford to acquire a higher stake and is thus more incentivized in smaller firms. Additionally, the smallest firms are also less complex and implementing ideas for growth might be facilitated. The bargaining position of the LPE entity might be better facing a smaller target, whose owners are less experienced in price negotiations.253 It might additionally be easier to find a buyer for smaller firms with a limited product offering. The largest portfolio companies, on the other hand, offer the opportunity to exit via an IPO and might generate higher absolute returns compared to the resources put in use. Achleitner et al. (2010) note that debt capacity and restructuring is more relevant in larger deals, whereas growth is more important in smaller companies.254 Summarizing the arguments, the medium-sized companies would be stuck in between the smallest and largest portfolio firms. However, keeping in mind that the target’s EV was approximated by using the transaction values and historical revenue multiples, findings with respect to the target’s size can be biased.
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The data availability, in general, remained a problem throughout the study although the amount of publicly available information is greater for LPE than for the unlisted counterparts. Profitability measures for the single portfolio companies, such as figures for net income; EBIT or EBITDA upon acquisition, over the investment horizon or upon exit, were only sporadically provided in CapitalIQ and in the annual reports of the LPE entities. Moreover, the data did not allow for an analysis including the debt incurred on the portfolio companies’ level, as neither CapitalIQ nor the annual reports provide information on the capital structure in the portfolio firms.255 Finally, a selection bias due to the relatively small sample size cannot be ruled out. It was beyond the scope of this paper to include more firms since a substantial amount of data had to be hand-collected from annual or news reports. Moreover, incorporating the largest LPE entities in the event study makes it difficult to obtain clean event windows as seen in the case of “3i Group”, for which at least one weekly transaction was recorded in CapitalIQ.
251 252 253 254
255
See Nikoskelainen/Wright (2007), p. 529. See here and following Nikoskelainen/Wright (2007), p. 513. See Fuller/Netter/Stegemoller (2002), p. 1784. See Achleitner et al. (2010), p. 22. The authors distinguish only between small and large firms but not bet-ween small, medium-sized and large firms. They define a small (large) firm to have an EV below (above) €100 million. See Strömberg (2007), p. 3.
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4 Conclusion and outlook The objective of the paper was twofold. First, a detailed description of investment and portfolio management strategies of PE firms was provided including acquisition and exit strategies as well as strategic, operational, financial and governance means. Second, announcement effects on the returns to LPE entities were tested with respect to distinct investment decisions. The empirical analysis revealed that the market expects LPE to generate value for its investors through acquisitions and exits. Considering CARs to acquisition announcements, public-to-private BOs are expected to add more value for investors than all other types of acquisitions. It was conjectured that the outperformance was driven by a better alignment of interests between management and new LPE owners, which hold a concentrated ownership stake. Furthermore, LPE professionals might be more sensitive not to overpay in the takeover process. The finding of positive abnormal returns upon the announcement of the takeover of public targets also contributes to the acquisition literature. LPE provides a remarkable basis to analyze differences between LPE entities and strategic corporate acquirers with regard to manager incentive schemes and to firm characteristics. Thus, a better intuition for the typically negative abnormal returns to corporate acquirers of public targets might be achieved.
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The CARs to exit announcements are in line with the results of prior studies that find portfolio companies exited via an IPO or trade sale to achieve higher IRRs throughout the holding period.256 While the event study method does not allow for a direct assessment of the cash flows generated during the investment period, the findings in this paper do suggest that higher exit multiples can be achieved in an IPO or trade sale. The higher exit multiples might be due to a superior quality of these companies and thus, it can be assumed that they have generated higher cash flows also during the holding period. The influence of multi-track exit options on exit prices is an interesting topic for further research. Overall, it has to be noted that the event study approximates the expected value added for investors but not for the portfolio company. Hence, no distinction is made between real value generation on the portfolio company level and value transfer from stakeholders as well as prior owners of the portfolio firm to the investors of the LPE entity through financial arbitrage. Throughout the paper assumptions were made about the extent to which financial arbitrage on the one hand and strategic, operational and governance engineering on the other hand were possible by employing certain investment strategies. For example, value in public-to-private deals might be actually generated on the portfolio firm level through improved governance mechanism or value might be transferred at the expense of prior shareholders by purchasing the public target below fair value. Similarly, in case of strategic refocusing it cannot be ruled out whether divisions were actually disposed due to strategic or rather to financial reasons, i.e. to engage in asset stripping. To arrive at an even better understanding of PE equity and differences between value generation and value transfer, it would certainly be useful for future studies to gain private access to profitability figures or information about the 256
See for example Gottschalg/Phalippou (2009), p. 1761 and Nikoskelainen/Wright (2007), p. 522.
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capital structure of underlying portfolio companies. This additional information can be insightful to further explain returns of LPE securities. It would, for example, be of interest whether the LPE entities that imposed on average the highest leverage on portfolio companies achieved higher returns than other LPE entities. Additionally, one could analyze the impact of the pre-buyout profitability of the portfolio companies on the returns achieved by LPE entities. For the investment strategies presented in this paper, it was not possible to partition the LPE entities in different samples of applied investment strategies and to determine the buy-and-hold returns over time because no investment strategy was consistently pursued but rather different kinds of entry, exit or strategic decisions were chosen throughout the investigated time period. Although the results of the event study suggest that some investment strategies, for example public-to-private deals, IPOs and trade sales, generate more value for investors than others, they are not applied consistently and hence, cannot explain why some PE firms persistently perform better than others.257 Hence, the findings suggest that persistence cannot be attributed to few explanatory variables but that continuous success is rather the result of a more complex interplay between distinct factors.258 For a PE firm, the possibility to draw from a larger pool of hired professionals with a varying skill set might be critical to conform to the complexity of PE and its underlying portfolio companies. Acharya et al. (2010), for example, note that experts with an operational background such as former consultants or managers outperform when applying organic growth strategies, whereas professionals with a finance background are more successful in transactional growth strategies.259 Therefore, information about the professionals within a PE firm and their experience can reveal further meaningful insights in future analyses.
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In summary, LPE entities in spite of the still existent limitations of data availability provide a notable alternative to analyze the characteristics of the PE market and of PE as an asset class. The information provided by LPE entities is more reliable since financial statements are audited and daily share price data allow for the application of traditional risk and return measures such as multifactor models or the event study methodology applied in this paper. Hence, LPE entities draw a more accurate picture of PE and are more transparent. Differences in the fee structures and incentive schemes have to be accounted for when generalizing findings about LPE entities for the overall PE market. However, inferences from LPE to the unlisted PE universe should be mostly correct, as investment and portfolio management strategies are akin. Future research can shed light on the question to what extent the value generation potential of listed and of unlisted private equity diverges.
257 258 259
See Gottschalg/Phalippou (2009), p. 1770. Kaplan/Schoar (2005), p. 1806. See Bergström/Grubb/Jonsson (2007), p. 35. See Acharya/Hahn/Kehoe (2010), p. 5.
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Append dix Appendix 1: Structu ure of a listted privatee equity fun nd (See Beergmann et al. 2010, p.. 57)
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This figuree depicts thee structure of a listed pprivate equiity fund. Itss structure resembles r thhe structuree of an unlissted Limited d Partnershiip. It often hhas an infinnite life, how wever, and ppays divideends insteadd of distributting the cap pital gains of the investm ment to invvestors.
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699
Appendix 2: Structu ure of a listted privatee equity fun nd managerr/firm (See Beergmann et al. 2010, p.. 57)
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The figure below show ws the struccture of a liisted privatee equity funnd managerr, also calledd listed pri-vate equityy firm. The investor buuys shares inn the Generral Partner, who in turnn is responssible for thee fundraisingg and manaagement of various Lim mited Partnnerships. Thhe dividendss are a funcction of thee fee incomee of the Gen neral Partneer and only indirectly of o the returnn generatedd by the porrtfolio com-panies.
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Appendix 3: Overviiew of LPE E entities in ncluded in the study Company Name (ticker)
Country
Industries of Interest
Geographies of Interest
Ratos AB (OM:RATO B)
Sweden
Public Investment Firm
4,421.8 Diversified
Scandinavia
Wendel (ENXTPA:MF)
France
Public Investment Firm
3,480.1 Diversified
France, North America
Eurazeo (ENXTPA:RF)
France
Public Investment Firm
3,112.4 Diversified
Italy, France
Onex Corporation (TSX:OCX)
Canada
Public Investment Firm, additional fund management
2,683.2 Diversified
North America, Latin America
GIMV NV (ENXTBR:GIMB)
Belgium
Public Investment Firm, investments mainly through own balance sheet
947.2 Diversified
Diversified
Electra Private Equity Plc (LSE:ELTA)
United Kingdom
Public Fund
688.4 Diversified
United Kingdom
Compass Diversified Holdings (NYSE:CODI)
USA
Public Investment Firm
609.2 Industrials, Consumer Discretionary
North America, Latin America
GP Investments (BOVESPA:GPIV11)
Brazil
Public Investment Firm, additional fund managament
546.4 Diversified
Latin America
Marfin Investment Group Holdings S.A. (ATSE:MIG)
Greece
Public Investment Firm
539.2 Diversified
Europe
Public Fund
364.4 Diversified
Europe
HgCapital Trust plc (LSE:HGT) United Kingdom
Bure Equity AB (OM:BURE)
Sweden
Public Investment Firm
326.3 Consumer Discretionary Sweden
Deutsche Beteiligungs AG (DB:DBA)
Germany
Public Investment Firm, additional fund management
288.4 Diversified
Diversified
Altamir Amboise SCR (ENXTPA:LTA)
France
Public Investment Firm, coinvests with Apax partners but no fee income
234.0 Diversified
France
Aurelius AG (XTRA:AR4)
Germany
Public Investment Firm
172.7 Diversified
Europe
Dinamia Capital Privado S.A., SCR (CATS:DIN)
Spain
Public Fund
140.1 Diversified
Portugal, Spain
AdCapital AG (DB:ADC)
Germany
Public Investment Firm
133.6 Industrial, Information Technology
Germany
Dunedin Enterprise Investment Trust plc (LSE:DNE)
United Kingdom
Public Fund
105.4 Diversified
United Kingdom
OFI Private Equity Capital (ENXTPA:OPEC)
France
Public Investment Firm
94.7 Diversified
France
Gigaset AG (XTRA:AQU) (Arques)
Germany
Public Investment Firm
90.3 Diversified
Germany
Management & Capitali S.p.A. (BIT:MEC)
Italy
Public Investment Firm
87.2 Diversified
Italy
Public Fund
48.0 Diversified
Germany
Germany
Public Investment Firm
44.8 Industrials
Germany
GCI Industrie AG (XTRA:GCI) Germany
Public Investment Firm
34.8 Diversified
German speaking countries
Public Investment Firm
31.6 Consumer Discretionary; Austria Information Technology
CFC Industriebeteiligungen AG Germany (XTRA:CFC)
Public Investment Firm
16.2 Diversified
Germany
Public Investment Firm
8.05 Information Technology Germany
Heliad Equity Partners GmbH & Germany Co. KGaA (XTRA:HPB) Copyright © 2013. Diplomica Verlag. All rights reserved.
Company Type
Market Capitalization as of 12/31/2010 (in € million)
MBB Industries AG (XTRA:MBB)
Unternehmens Invest AG (WBAG:UIV)
Blue Cap AG (XTRA:B7E)
Austria
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
German speaking countries
71
20.00
50.00
40.00
0.00
0.00
0.00
0.00
40.00
50.00
20.00
0.00
% Insolvency
60.00
0.00
80.00
25.00
0.00
16.67
60.00
0.00
0.00
75.00
64.29
0.00
% Secondary
20.00
50.00
20.00
0.00
35.71
0.00
0.00
75.00
% Trade Sale
33.33
0.00
20.00
25.00
0.00
100.00
0.00
0.00
8.33
0.00
42.86
40.00
66.67
14.29
0.00
100.00
0.00
3.23
% IPO
33.33
14.29
36.84
0.00
21.43
0.00
0.00
100.00
35.48
0.00
50.00
% Transactional growth
33.33
42.86
21.05
25.00
14.29
50.00
0.00
0.00
61.29
31.25
15.38
41.67
% Organic Growth
50.00
0.00
26.32
0.00
11.11
0.00
50.00
0.00
0.00
68.75
23.08
0.00
25.00
50.00
57.14
15.79
17.86
11.11
40.00
0.00
100.00
22.58
0.00
53.85
42.86
80.00
% Refocusing
2.15
42.86
52.63
57.14
55.56
0.00
0.00
0.00
35.48
37.50
7.69
57.14
0.00
34.78
11
2.15
47.37
21.43
22.22
0.00
0.00
0.00
9.68
43.75
30.77
0.00
20.00
% Secondary
5
11
4.70
78.57
0.00
60.00
25.00
0.00
33.33
6.25
53.85
42.86
0.00
13.04
% Public-toprivate
6
4
24
7.83
100.00
20.00
75.00
0.00
15.56
4.00
15.38
42.86
0.00
30.43
% Divisional
7
5
40
4.50
80.00
75.00
100.00
22.22
4.00
10.53
14.29
40.00
21.74
% Whole company
Wendel (ENXTPA:MF)
19
12
23
1.37
25.00
100.00
28.89
16.00
0.00
25.00
60.00
65.22
% MBIs
Eurazeo (ENXTPA:RF)
28
14
7
1.96
0.00
35.56
72.00
31.58
12.50
0.00
34.78
% MBOs
Onex Corporation (TSX:OCX)
9
2
10
0.59
64.44
92.00
57.89
31.25
0.00
6.85
GIMV NV (ENXTBR:GIMB)
5
2
3
14.87
8.00
21.05
31.25
66.67
% of Total Deals
Electra Private Equity Plc (LSE:ELTA)
8
1
76
8.02
78.95
68.75
33.33
0.00
35
Compass Diversified Holdings (NYSE:CODI)
2
31
41
6.26
31.25
100.00
46.15
Total number of Deals
GP Investments (BOVESPA:GPIV11)
45
16
32
4.50
0.00
53.85
12
Marfin Investment Group Holdings S.A. (ATSE:MIG)
25
13
23
3.91
0.00
Number of Exits
HgCapital Trust plc (LSE:HGT)
19
7
20
23.08
23
Bure Equity AB (OM:BURE)
16
5
38.46
Number of Acquisitions
Deutsche Beteiligungs AG (DB:DBA)
15
0.00
Company Name (ticker)
Altamir Amboise SCR (ENXTPA:LTA)
10.53
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Ratos AB (OM:RATO B)
Aurelius AG (XTRA:AR4)
0.00
0.00
36.84
50.00
50.00
52.63
50.00
50.00
0.00
36.84
0.00
0.00
50.00
n/a
63.16
20.00
0.00
44.44
n/a
n/a
6.26
60.00
0.00
5.56
n/a
n/a
0.00
32
0.00
50.00
11.11
n/a
n/a
0.00
100.00
13
10.00
0.00
61.11
n/a
n/a
100.00
0.00
0.00
19
0.00
33.33
44.44
n/a
n/a
0.00
0.00
16.67
75.00
0.00
25.00
0.00
0.00
n/a
n/a
100.00
0.00
83.33
25.00
n/a
0.00
65.00
0.00
0.00
0.00
n/a
0.00
0.00
0.00
0.00
n/a
100.00
10.00
66.67
72.00
0.00
0.00
0.00
100.00
16.67
0.00
n/a
0.00
90.00
33.33
28.00
0.00
0.00
0.00
0.00
33.33
75.00
n/a
0.00
5.87
66.67
100.00
100.00
50.00
0.00
0.00
0.00
100.00
n/a
100.00
30
1.57
0.00
50.00
50.00
50.00
0.00
0.00
0.00
n/a
0.00
10
8
8.41
50.00
100.00
50.00
100.00
0.00
0.00
n/a
0.00
20
2
43
0.39
0.00
50.00
0.00
12.50
0.00
0.00
0.00
6
18
2
0.39
50.00
100.00
87.50
28.57
0.00
0.00
Dunedin Enterprise Investment Trust plc (LSE:DNE)
25
0
2
0.98
0.00
75.00
71.43
0.00
100.00
OFI Private Equity Capital (ENXTPA:OPEC)
2
0
5
0.39
25.00
85.71
100.00
100.00
Gigaset AG (XTRA:AQU) (Arques)
2
1
2
2.74
14.29
100.00
0.00
Management & Capitali S.p.A. (BIT:MEC)
4
1
14
2.15
0.00
0.59
Heliad Equity Partners GmbH & Co. KGaA (XTRA:HPB)
1
6
11
0.59
3
MBB Industries AG (XTRA:MBB)
8
4
3
1
GCI Industrie AG (XTRA:GCI)
7
0
2
Unternehmens Invest AG (WBAG:UIV)
3
AdCapital AG (DB:ADC)
CFC Industriebeteiligungen AG (XTRA:CFC)
Dinamia Capital Privado S.A., SCR (CATS:DIN)
Blue Cap AG (XTRA:B7E)
72
Copyright © 2013. Diplomica Verlag. All rights reserved.
Appendix 4: Breakd down of traansaction characteristtics by LPE E entity
Appendix 5: Abnormal return ns for acquiisition annoouncementts from dayy t=-20 to t= =20
The table displays d thee daily averrage abnorm mal and cum mulative abbnormal retuurns for all acquisitionn events arouund the ann nouncementt date (t=0) based on thhe market m model. Addiitionally, daaily averagee abnormal ranks, r mediian abnormaal returns ass well as thee percentage of positivve abnormall returns aree displayed. Day relative to the Average abnormal announcement return (in %) -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
0.0174 -0.1382 0.0334 -0.1201 -0.05 -0.0886 -0.0092 -0.0425 0.0966 0.1021 0.1194 0.0251 -0.0477 0.0778 0.0943 -0.2403 0.0434 -0.0363 0.0825 0.0166 0.1092 0.2021 0.168 0.0179 -0.2004 0.0724 0.0558 0.1632 -0.0015 -0.1057 -0.0359 0.1203 -0.0748 -0.3652 -0.0476 0.0373 -0.064 -0.0204 0.261 0.0307 -0.0549
t-stat 0.14 -1.08 0.26 -0.94 -0.39 -0.7 -0.07 -0.33 0.76 0.8 0.94 0.2 -0.37 0.61 0.74 -1.89* 0.34 -0.29 0.65 0.13 0.86 1.59 1.32 0.14 -1.57 0.57 0.44 1.28 -0.01 -0.83 -0.28 0.94 -0.59 -2.87*** -0.37 0.29 -0.5 -0.16 2.05** 0.24 -0.43
CAR (in %) 0.0174 -0.1207 -0.0873 -0.2074 -0.2574 -0.346 -0.3552 -0.3976 -0.301 -0.199 -0.0796 -0.0544 -0.1021 -0.0244 0.0699 -0.1704 -0.127 -0.1633 -0.0808 -0.0642 0.0449 0.247 0.415 0.4329 0.2325 0.3049 0.3607 0.5238 0.5223 0.4167 0.3808 0.5011 0.4264 0.0612 0.0136 0.0509 -0.0132 -0.0335 0.2275 0.2582 0.2033
Average Corrado rank Median Abnormal Abnormal Rank t-stat Return (in %) 3.05 -1.66 -0.02 -2.56 1.38 1.31 -2.84 -2.31 1.12 -2.73 1.31 3.99 0.74 3.06 0.57 -4.79 2.30 -2.43 0.52 6.94 3.75 8.96 6.10 -1.58 -6.16 3.80 2.63 4.13 1.55 -0.64 -0.31 4.65 0.03 -8.89 -3.96 -2.11 -1.25 -4.97 5.13 1.23 3.91
0.78 -0.42 0 -0.65 0.35 0.33 -0.73 -0.59 0.29 -0.7 0.34 1.02 0.19 0.78 0.15 -1.22 0.59 -0.62 0.13 1.77* 0.96 2.28** 1.55 -0.4 -1.57 0.97 0.67 1.05 0.39 -0.16 -0.08 1.19 0.01 -2.27** -1.01 -0.54 -0.32 -1.27 1.31 0.31 1
-0.0351 -0.0401 -0.0451 -0.1052 -0.032 -0.0627 -0.0326 -0.0499 -0.0396 -0.1209 -0.0505 -0.0025 -0.0523 -0.0142 -0.0586 -0.0678 -0.0137 -0.0699 -0.0344 0.0183 0.0291 0.079 -0.0166 -0.0702 -0.0843 -0.0296 -0.033 -0.0102 -0.0098 -0.049 -0.0335 0 -0.0328 -0.1395 -0.0654 -0.063 -0.059 -0.0614 0.0024 -0.0347 -0.0362
Positive Percentage (in %) 0.46 0.47 0.46 0.45 0.47 0.45 0.47 0.45 0.47 0.43 0.46 0.5 0.46 0.49 0.46 0.43 0.49 0.44 0.46 0.51 0.51 0.55 0.49 0.43 0.42 0.48 0.47 0.49 0.49 0.45 0.48 0.5 0.48 0.43 0.43 0.45 0.44 0.44 0.51 0.46 0.46
Copyright © 2013. Diplomica Verlag. All rights reserved.
***, ** andd * denotes signifficance at the 1% %, 5% and 10% levvel respectively ((two-tailed test).
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733
Appendix 6: Robustn ness checkss for acquissition annoouncementss Dummy = +1 if MBI and = -1 if MBO Whole company
Divisional BO
Public-to-Private
Secondary LBO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
Deutsche Beteiligungs AG
CAR[-2;+2] Model 6 Model 7 b/se/p b/se/p 0.0006 0.0011 0.0025 0.0029 (0.8194) (0.7056) 0.0066 0.0093 0.0069 0.0133 (0.3378) (0.4851) 0.0119 0.0115 0.0102 0.0136 (0.2412) (0.3996) 0.0223 0.0255 0.01 0.0148 (0.0262)** (0.0862)* 0.0132 0.0146 0.0077 0.0135 (0.0869)* (0.2806) -0.0034 -0.0083 0.0057 0.0069 (0.5593) (0.2281) -0.009 -0.0101 0.0091 0.0234 (0.3244) (0.666) -0.0038 -0.0037 0.003 0.003 (0.2069) (0.2204) -1.0816 -0.8547 0.7484 0.7391 (0.1496) (0.2487) 0.5391 0.4251 0.3745 0.37 (0.1512) (0.2517) 0.0013 -0.0281 0.0062 0.0179 (0.8363) (0.117) omitted
Gigaset AG (Arques)
AdCapital AG
Aurelius AG
Heliad Equity Partners GmbH & Co. KgaA MBB Industries AG
GCI Industries AG
CFC Industriebeteiligungen AG
Blue Cap AG
Ratos AB
Wendel
Eurazeo
Onex Corporation
GIMV NV
Electra Private Equity
Compass Diversified Holding
Marfin Investment Group Holdings S.A.
HGCapitalTrust plc
Bure Equity AB
Copyright © 2013. Diplomica Verlag. All rights reserved.
Altamir Amboise SCR
Dinamia Capital Privado S.A., SCR
Dunedin Enterprise Investment Trust plc
OFI Private Equity
Management & Capitali S.p.A.
Unternehmens Invest AG
GP Investments
constant
Firm fixed effects Observations R2
0.0144 0.015 (0.3384) no 270 0.0335
-0.0066 0.035 (0.8511) -0.026 0.0137 (0.0591)* -0.04 0.0342 (0.2429) -0.0715 0.0271 (0.0089)*** -0.0096 0.0723 (0.8947) -0.0316 0.0223 (0.157) -0.0694 0.0413 (0.0937)* -0.0528 0.055 (0.3385) -0.001 0.0185 (0.9585) 0.0366 0.0296 (0.2168) 0.0331 0.0253 (0.1928) 0.0308 0.0244 (0.2076) 0.002 0.018 (0.9105) 0.0025 0.02 (0.8989) 0.0111 0.0275 (0.686) -0.0078 0.0294 (0.7913) -0.0341 0.0141 (0.016)** -0.003 0.0277 (0.9134) -0.0295 0.0226 (0.193) -0.0038 0.0305 (0.9016) -0.0276 0.0167 (0.0991)* -0.0413 0.033 (0.2121) -0.0307 0.0287 (0.2859) -0.0485 0.0211 (0.0226)** -0.0417 0.0266 (0.119) 0.102 0.0615 (0.0986)* no 270 0.1514
Dummy = +1 if MBI and = -1 if MBO Whole company
Divisional BO
Public-to-Private
Secondary LBO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
constant
Firm fixed effects Observations R2
CAR[-2;+2] Model 8 b/se/p 0.0004 Dummy = +1 if MBI 0.0025 and = -1 if MBO (0.8697) 0.0026 Whole company 0.0103 (0.7989) 0.0054 Divisional BO 0.0122 (0.6589) 0.0147 Public-to-Private 0.0125 (0.2417) 0.0066 Secondary LBO 0.0111 (0.5545) -0.0067 Syndicated deals 0.0061 (0.2767) -0.0127 log(LPE's age) 0.0096 (0.1863) -0.0041 LPE's P/B-ratio 0.0027 (0.126) -1.2824 log(target's EV) 0.8253 (0.1215) 0.6403 log (target's EV2) 0.4129 (0.1223) 0.0044 log (LPE's market cap) 0.0065 (0.4978) omitted Germany
-0.02 0.0108 (0.0659)* -0.0214 0.0098 (0.0303)** -0.0256 0.0098 (0.01)*** 0.0033 0.0129 (0.7995) -0.0138 0.0195 (0.4794) -0.0037 0.0143 (0.7985) 0.0049 0.0137 (0.7192) -0.0063 0.0128 (0.6223) -0.0167 0.0104 (0.1096) -0.0254 0.0108 (0.0202)** -0.0065 0.0144 (0.65) -0.0226 0.0133 (0.0903)* -0.0133 0.0139 (0.3409)
0.0275 0.019 (0.1479) no 270 0.0856
Sweden
France
North America
Belgium
UK
Greece
Spain
Italy
Austria
Brazil
CAR[-2;+2] Model 9 b/se/p -0.0004 0.0026 (0.8714) 0.0025 0.0087 (0.7741) 0.007 0.01 (0.4883) 0.0174 0.0113 (0.1228) 0.0069 0.0088 (0.4352) -0.0053 0.0063 (0.3954) 0 0.0104 (0.9999) -0.0062 0.0034 (0.0727)* -1.2449 0.729 (0.0889)* 0.6189 0.3649 (0.0911)* -0.0043 0.009 (0.6352) omitted
Dummy = +1 if MBI and = -1 if MBO Whole company
Divisional BO
Public-to-Private
Secondary LBO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
Energy
-0.0088 Materials 0.0103 (0.3943) 0.0022 Industrials 0.0107 (0.8341) 0.0207 Consumer Discretionary 0.016 (0.1976) -0.01 Consumer Staples 0.0115 (0.3861) -0.0205 Healthcare 0.0086 (0.0183)** -0.0255 Financials 0.0181 (0.1611) 0.0093 Information Technology 0.0154 (0.5463) -0.0237 Telecommunication Services 0.0116 (0.0424)** -0.0266 Utilities 0.0129 (0.0406)** -0.0374 0.024 (0.12)
constant
Firm fixed effects Observations R2
74
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0.0397 0.0215 (0.0663)* no 270 0.0963
constant
Firm fixed effects Observations R2
CAR[-2;+2] Model 10 b/se/p 0.0019 0.0025 (0.4438) 0.0116 0.0161 (0.4717) 0.0189 0.0164 (0.2481) 0.0282 0.0162 (0.0821)* 0.0201 0.0151 (0.1852) -0.0038 0.0062 (0.5423) -0.0115 0.0087 (0.1879) -0.0041 0.0028 (0.1485) -1.0662 0.7413 (0.1516) 0.5318 0.371 (0.1529) -0.0016 0.0062 (0.7945) omitted
0.0103 0.0162 (0.5247) 0.0292 0.013 (0.0252)** 0.0174 0.0142 (0.2236) 0.0394 0.0156 (0.0122)** 0.0258 0.018 (0.1517) 0.0209 0.0146 (0.1529) 0.01 0.0126 (0.4253) -0.0214 0.0467 (0.6478) 0.0069 0.0176 (0.6939)
-0.0035 0.023 (0.8799) no 270 0.0801
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0.0237 0.6697
0.021 0.7053
-0.0826 0.1367
-0.1351** 0.0147
-0.2687*** 0
0.0946* 0.088
-0.1213** 0.0414
-0.1214** 0.0413
-0.071 0.2011
Divisional BO
Public-to-Private
Secondary LBO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
-0.1129** 0.0416
-0.2360*** 0.0001
-0.2359*** 0.0001
-0.0203 0.7145
-0.1073* 0.0528
-0.0953* 0.0859
-0.4216*** 0
-0.2254*** 0
-0.6072*** 0
1
Whole company
-0.0498 0.3701
0.0233 0.6965
0.0236 0.6926
0.0711 0.2006
-0.1276** 0.0212
0.0391 0.4819
-0.3117*** 0
-0.1667*** 0.0025
1
Divisional BO
0.0785 0.1573
0.2046*** 0.0005
0.2045*** 0.0005
-0.0383 0.491
0.1329** 0.0164
0.0121 0.8278
-0.1157** 0.0367
1
Public-to-Private
0.1547*** 0.0051
0.1509** 0.011
0.1505** 0.0112
-0.0355 0.5232
0.2162*** 0.0001
0.0738 0.1835
1
Secondary LBO
0.0487 0.3811
0.2857*** 0
0.2852*** 0
-0.1074* 0.0526
0.1435*** 0.0095
1
Syndicated deals
0.5134*** 0
0.3809*** 0
0.3807*** 0
-0.1166** 0.0353
1
log(LPE's age)
0.2345*** 0
0.0504 0.3986
0.0506 0.3961
1
LPE's P/B-ratio
0.3998*** 0
1.0000*** 0
1
log(target's EV)
0.3997* 0
1
log (target's EV2)
The first figure in the table is the correlation, the second one the corresponding p-value. ***, ** and * denotes significance at the 1%, 5% and 10% level respectively (two-tailed test).
0.0258 -0.6422
Whole company
Dummy = +1 if MBI and = -1 if MBO Dummy = +1 if MBI 1 and = -1 if MBO
Copyright © 2013. Diplomica Verlag. All rights reserved.
Appen ndix 7: Co orrelation matrix m for vvariables in n the regresssion of CA ARs to acqu uisition an nnouncemen nts
755
Appendix 8: Abnormal return ns for exit aannouncem ments from day t=-20 to t t=20
The table displays d thee daily averrage abnorm mal and cum mulative abbnormal retuurns for all exit eventss around thee announcem ment date (t=0) basedd on the maarket modell. Additionaally, daily aaverage ab-normal rannks, median n abnormal returns as w well as the percentagee of positivee abnormal returns aree displayed. Day relative to the announcement -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Average abnormal return (in %) 0.0263 -0.1399 -0.2187 0.0658 0.195 -0.272 0.3212 0.0887 -0.0102 0.0431 0.0197 0.1087 -0.0033 0.0156 0.0273 -0.2673 -0.2164 0.012 -0.0763 -0.0137 0.3803 0.3513 -0.167 -0.2893 0.0244 -0.0902 -0.0377 -0.0177 0.017 0.0208 -0.2155 -0.3466 0.048 0.0471 0.1307 0.2796 -0.1603 -0.0797 -0.4843 -0.0462 -0.0056
t-stat 0.14 -0.77 -1.21 0.36 1.08 -1.5 1.77* 0.49 -0.06 0.24 0.11 0.6 -0.02 0.09 0.15 -1.48 -1.19 0.07 -0.42 -0.08 2.1** 1.94* -0.92 -1.6 0.13 -0.5 -0.21 -0.1 0.09 0.11 -1.19 -1.91* 0.27 0.26 0.72 1.54 -0.88 -0.44 -2.67*** -0.26 -0.03
CAR (in %) 0.0263 -0.1136 -0.3323 -0.2665 -0.0715 -0.3435 -0.0223 0.0664 0.0562 0.0993 0.1189 0.2276 0.2243 0.2399 0.2672 -0.0001 -0.2166 -0.2046 -0.2808 -0.2946 0.0858 0.4371 0.2701 -0.0192 0.0052 -0.085 -0.1227 -0.1404 -0.1234 -0.1026 -0.3181 -0.6647 -0.6167 -0.5696 -0.4389 -0.1593 -0.3196 -0.3993 -0.8836 -0.9298 -0.9354
Average Corrado rank Median Abnormal Positive Abnormal Rank t-stat Return (in %) Percentage (in %) 0.01 -4.09 -10.12 4.11 -3.13 -0.70 10.81 3.71 -3.29 4.04 1.44 2.34 1.71 4.03 -1.36 -7.28 -4.96 2.20 -2.41 3.83 11.23 13.35 -4.37 -11.01 6.36 0.48 1.83 -9.34 0.50 -3.21 -6.23 -13.45 1.49 0.16 -2.60 4.75 -7.44 -4.97 -1.51 -9.11 -5.71
0 -0.81 -2** 0.81 -0.62 -0.14 2.14** 0.73 -0.65 0.8 0.28 0.46 0.34 0.8 -0.27 -1.44 -0.98 0.44 -0.48 0.76 2.22** 2.64*** -0.86 -2.18** 1.26 0.1 0.36 -1.85* 0.1 -0.63 -1.23 -2.66*** 0.29 0.03 -0.51 0.94 -1.47 -0.98 -0.3 -1.8* -1.13
-0.0423 -0.0814 -0.1376 0.0125 -0.1163 -0.0358 0.0738 -0.0665 -0.0897 -0.0289 -0.0806 -0.0348 0.0512 0.0223 -0.0852 -0.1056 -0.1555 -0.0191 -0.1273 -0.0151 0.0179 0.0984 -0.0949 -0.1791 0.0179 -0.0837 -0.0339 -0.2194 -0.0239 -0.0656 -0.0925 -0.1913 -0.0666 -0.0959 -0.0571 -0.0467 -0.1138 -0.0951 -0.031 -0.1493 -0.1375
Copyright © 2013. Diplomica Verlag. All rights reserved.
* ***, ** and * dennotes significancee at the 1%, 5% aand 10% level resppectively (two-taailed test).
76
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0.47 0.45 0.39 0.50 0.45 0.48 0.53 0.46 0.47 0.49 0.45 0.49 0.51 0.51 0.44 0.44 0.41 0.49 0.43 0.49 0.50 0.55 0.45 0.43 0.51 0.45 0.48 0.41 0.47 0.47 0.45 0.38 0.48 0.45 0.45 0.47 0.40 0.44 0.48 0.40 0.43
Appendix 9: Robusttness check ks for exit announcem ments CAR[-2;+2] Model 9 b/se/p Insolvency
Trade sale
IPO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
-0.0509 0.0267 (0.0591)* 0.0205 0.0087 (0.0197)** 0.0261 0.0241 (0.2809) -0.0045 0.0067 (0.5073) -0.0364 0.0159 (0.0233)** -0.0019 0.006 (0.7485) -1.014 1.1699 (0.3874) 0.5157 0.5846 (0.3791) 0.008 0.0119 (0.5027)
Deutsche Beteiligungs AG
Gigaset AG (Arques)
AdCapital AG
Aurelius AG
MBB Industries AG
GCI Industries AG
CFC Industriebeteiligungen AG
Ratos AB
Wendel
Eurazeo
Onex Corporation
GIMV NV
Electra Private Equity
Compass Diversified Holding
Marfin Investment Group Holdings S.A.
HGCapitalTrust plc
Bure Equity AB
Altamir Amboise SCR
Copyright © 2013. Diplomica Verlag. All rights reserved.
Dinamia Capital Privado S.A., SCR
Dunedin Enterprise Investment Trust plc
OFI Private Equity
Unternehmens Invest AG
GP Investments
constant
Firm fixed effects Observations R2
-0.0067 0.0256 (0.7943) no 165 0.1605
CAR[-2;+2] Model 11 b/se/p
Model 10 b/se/p -0.0522 0.0314 (0.0991)* 0.0151 0.0098 (0.1259) 0.029 0.0267 (0.279) -0.0069 0.0071 (0.3298) -0.0366 0.0587 (0.5336) 0.0017 0.0094 (0.8584) -1.8911 1.1997 (0.1173) 0.952 0.6002 (0.1151) 0.0213 0.0279 (0.4447) omitted
-0.0248 0.0603 (0.6819) -0.0424 0.0195 (0.0313)** 0.0137 0.071 (0.8473) 0.2716 0.0257 (0)*** -0.1739 0.0364 (0)*** -0.0383 0.0896 (0.6697) -0.0331 0.023 (0.1524) -0.0562 0.0517 (0.2787) -0.0461 0.0389 (0.2372) -0.0379 0.0371 (0.3099) -0.0144 0.0296 (0.6286) -0.0181 0.0284 (0.5235) -0.09 0.076 (0.2385) -0.0438 0.0476 (0.3589) -0.017 0.0217 (0.4347) -0.0253 0.0325 (0.4383) -0.0174 0.0339 (0.6094) -0.0106 0.0442 (0.8112) -0.0253 0.0237 (0.2882) 0.0101 0.0549 (0.8539) -0.0204 0.0289 (0.4811) 0.1197 0.0305 (0.0001)*** -0.0108 0.0858 (0.9) no 165 0.4523
Insolvency
Trade sale
IPO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Firm fixed effects Observations R2
-0.0479 0.029 (0.1012) 0.0241 0.0102 (0.019)** 0.0233 0.0244 (0.3415) -0.0038 0.0067 (0.5713) -0.0397 0.0164 (0.0165)** -0.0009 0.0064 (0.8821) -0.7376 1.2928 (0.5692) 0.3774 0.6457 (0.5598) 0.0064 0.0126 (0.6091) omitted
0.0157 0.0176 (0.3734) -0.0193 0.0129 (0.1386) -0.0163 0.0173 (0.347) -0.016 0.0113 (0.1609) -0.0007 0.0119 (0.9536) 0.0109 0.0196 (0.5778) -0.0113 0.02 (0.5725) 0.019 0.0126 (0.1326) -0.0054 0.0123 (0.6635) 0.0065 0.0135 (0.6301) 0.0012 0.0207 (0.9557) -0.0097 0.0267 (0.7172) 0.018 0.0208 (0.3864)
-0.0027 0.0227 (0.9038) no 165 0.2035
CAR[-2;+2] Model 12 b/se/p Insolvency
Trade sale
IPO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
Germany
Sweden
France
North America
Belgium
UK
Greece
Spain
Austria
Brazil
Firm fixed effects Observations R2
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
-0.0526 0.0286 (0.0676)* 0.0205 0.0089 (0.0233)** 0.0269 0.0254 (0.2913) -0.0043 0.0063 (0.4993) -0.032 0.02 (0.1112) -0.0044 0.0061 (0.4744) -1.2088 1.1838 (0.3089) 0.6125 0.5919 (0.3025) 0.0126 0.0153 (0.4118) omitted
CAR[-2;+2] Model 13 b/se/p
Energy
-0.0537 0.0301 (0.0763)* 0.0218 0.0095 (0.0236)** 0.0326 0.0246 (0.1875) -0.0062 0.0073 (0.3998) -0.0375 0.0162 (0.0221)** -0.0011 0.0062 (0.8544) -1.0037 1.2214 (0.4126) 0.5103 0.6104 (0.4045) 0.0069 0.0126 (0.5835) omitted
-0.0158 Materials 0.0149 (0.2909) Industrials -0.0275 0.0161 (0.0885)* -0.0348 Consumer Discretionary 0.0222 (0.1202) Consumer Staples -0.0019 0.016 (0.9053) Healthcare -0.0122 0.0153 (0.4284) -0.0284 Financials 0.0197 (0.1525) -0.0041 Information Technology 0.0168 (0.8078) -0.0198 Telecommunication Services 0.0268 (0.462) 0.1361 Utilities 0.0155 (0)***
-0.0138 0.015 (0.3609) -0.0027 0.0102 (0.795) 0.0005 0.0116 (0.966) 0.018 0.0146 (0.2185) 0.0062 0.0159 (0.6954) 0.0152 0.015 (0.3149) -0.0028 0.0114 0.8067 0.0142 0.0183 (0.4393) 0.046 0.012 (0.0002)***
-0.008 0.0334 (0.8101) no 165 0.2245
Insolvency
Trade sale
IPO
Syndicated deals
log(LPE's age)
LPE's P/B-ratio
log(target's EV)
log (target's EV2)
log (LPE's market cap)
Firm fixed effects Observations R2
-0.0026 0.0248 (0.9167) no 165 0.1749
777
Holding period Refocusing
Organic growth
Transactional Total strategic growth decisions
Syndicated deals
log(LPE's age)
LPE's P/Bratio
log(target's EV)
EV2)
log (target's
1
1
1
1
1
Insolvency
IPO
-0.1889 0.01 -0.8241*** 0 -0.1915*** 0.009 -0.1885** 0.0232
1
Secondary LBO
Trade sale
-0.1212 0.1003 -0.2984*** 0 0.1205 0.1489 -0.0122 0.8884
Trade sale
Secondary LBO
-0.0439 0.553 -0.0121 0.8851 0.1319* 0.0965
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IPO
Insolvency
-0.0058 0.945 -0.0855 0.2826
1
Holding period
0.0064 0.9363
-0.2030*** 0.01
0.0183 0.8188
0.0308 0.7238
Refocusing
0.0262 0.7425
0.0078 0.9215
-0.0046 0.9543
-0.0495 0.5339
1
Organic growth
-0.1724** 0.0293
-0.0011 0.9893
-0.1353* 0.088
-0.1091 0.1695
0.1027 0.2376
0.2785*** 0.0004
0.0247 0.7561
Transactional growth
1
0.1163 0.1431
0.5094*** 0
-0.0546 0.4925
0.5501*** 0
-0.0692 0.3843
0.3284*** 0
0.1735** 0.0282
0.0943 0.2784
Total strategic decisions
0.3020*** 0.0002
1
-0.1068 0.1549
-0.0805 0.3176
0.0848 0.259
0.0888 0.2706
-0.0327 0.6635
-0.1405* 0.0801
0.015 0.8419
-0.055 0.4953
Syndicated deals
-0.0775 0.3301
1
0.2996*** 0.0003
0.2261*** 0.0023
0.0131 -0.2437*** 0.8598 0.0008
0.052 0.5141
0.0321 0.6646
0.1265 0.1108
0.1695** 0.0321
0.2335*** 0.0014
0.028 0.7256
-0.0321 0.6868
log(LPE's age)
-0.1173 0.1602
1
0.3127*** 0
0.005 0.9465
-0.1471** 0.0457
0.3003*** 0.0002
-0.0856 0.2546
-0.0626 0.3972
-0.0531 0.5203
0.2181*** 0.0056
0.1480** 0.0444
-0.0311 0.7064
0.1393* 0.079
LPE's P/B-ratio
0.0548 0.5278
1
-0.0894 0.2479
0.1606* 0.0504
0.036 0.6422
0.0454 0.5574
0.3000*** 0.0002
0.4202*** 0
-0.0777 0.3156
-0.0525 0.5246
0.0431 0.5828
0.2362*** 0.002
-0.031 0.7073
0.1604* 0.0507
log(target's EV)
0.0541 0.5335
1
-0.0891 0.2493
1.0000*** 0
0.045 0.5616
0.0506 0.5251
0.0365 0.6372
-0.0775 0.3165
0.0207 0.7946
0.4202*** 0
0.2368*** 0.0019
0.0567 0.4763
0.0431 0.5824
log (target's EV2)
0.2640*** 0.0013
0.2401*** 0.0017
-0.2441*** 0.0008
0.2404*** 0.0016
-0.026 0.7249
0.1317* 0.0739
0.0882 0.2323
0.6306*** 0
0.1772** 0.0158
0.0866 0.1945*** 0.2765 0.0091
log (LPE's market cap)
The first figure in the table is the correlation, the second one the corresponding p-value. ***, ** and * denotes significance at the 1%, 5% and 10% level respectively (two-tailed test).
The first figure in the table is the correlation, the second one the corresponding p-value. ***, ** and * denotes significance at the 1%, 5% and 10% level respectively (two-tailed test).
78
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Appendix 10: Correllation matrrix for variaables in thee regression n of CARs to exit announ ncements
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Frederik Bruns Windfall Profit in Portfolio Diversification? An Empirical Analysis of the Potential Benefits of Renewable Energy Investments Diplomica 2013 / 112 Seiten / 39,50 Euro ISBN 978-3-8428-8799-2 EAN 9783842887992
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Modern Portfolio Theory is a theory which was introduced by Markowitz, and which suggests the building of a portfolio with assets that have low or, in the best case, negative correlation. In times of financial crises, however, the positive diversification effect of a portfolio can fail when Traditional Assets are highly correlated. Therefore, many investors search for Alternative Asset classes, such as Renewable Energies, that tend to perform independently from capital market performance. 'Windfall Profit in Portfolio Diversification?' discusses the potential role of Renewable Energy investments in an institutional investor’s portfolio by applying the main concepts from Modern Portfolio Theory. Thereby, the empirical analysis uses a unique data set from one of the largest institutional investors in the field of Renewable Energies, including several wind and solar parks. The study received the Science Award 2012 of the German Alternative Investments Association ('Bundesverband Alternative Investments e.V.').
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Christian Deger Behind the Curve An Analysis of the Investment Behavior of Private Equity Funds Diplomica 2013 / 80 Seiten / 29,50 Euro ISBN 978-3-8428-8910-1 EAN 9783842889101
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In aviation, getting “behind the power curve” usually refers to a situation, in which an aircraft is flying slowly at low altitude and there is not enough power to reestablish a controlled flight. The only option for the pilot to recover from this situation is to nose dive the aircraft in order to regain airspeed. In private equity, especially in the field of leveraged buyouts, fund managers are regularly confronted with a less dangerous, but similar situation. Facing low fund performance or having an overhang of uninvested capital puts fund managers “behind the curve” and requires measures for recovery. This study investigates the behavior of fund managers exposed to this kind of distressed situation by analyzing the effects on both financing structure and pricing of portfolio investments.
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Bernhard Särve PIPE Investments of Private Equity Funds The temptation of public equity investments to private equity firms Diplomica 2013 / 80 Seiten / 29,50 Euro
Copyright © 2013. Diplomica Verlag. All rights reserved.
ISBN 978-3-8428-8911-8 EAN 9783842889118
Usually, private equity firms take control of firms which are privately held, and tend to act hidden. But, in recent years, the rising phenomenon of private investments in publicly listed companies, so-called PIPEs, could be observed. At first, this seems to be inconsistent but, it could become a perfect way to generate good returns. This book gives an overview about the PIPE market, and then focuses on the role of private equity funds. How do they invest in publicly listed firms? And what are their motivations? Is the overall performance of PIPE deals superior to those of traditional private deals? PIPE deals have much in common with typical venture capital deals with regard to the young and high-risk nature of target companies, and the minority ownership position. Surprisingly, buyout funds are relatively more engaged in PIPEs than venture funds are. The author analyzes deal sizes, industry sectors, holding periods, IRRs and multiples of public deals, and comparable private deals with a unique data sample on transaction level. Finally, he discusses other possible motives for private equity firms to engage in these deals: improved liquidity, fast process of deal execution, access to certain markets, avoidance of takeover premiums and the thesis of an escape-strategy for surplus investment money.
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Christina Halder Finanzierung von M&A-Transaktionen Vendor Loans und Earnout-Strukturen Diplomica 2013 / 56 Seiten / 19,50 Euro ISBN 978-3-8428-8913-2 EAN 9783842889132
Copyright © 2013. Diplomica Verlag. All rights reserved.
Im Rahmen der Hochkonjunktur von M&A-Transaktionen beschäftigte sich eine große Anzahl von Experten aus Wissenschaft und Forschung mit den im M&AKontext aufkommenden Fragestellungen. Die vorliegende Untersuchung beschäftigt sich mit dem Thema der Finanzierung von M&A-Transaktionen durch den Verkäufer. Die Zielsetzung besteht darin, die verschiedenen Möglichkeiten der Finanzierung von M&A-Deals durch den Verkäufer darzulegen. Es wird kritisch hinterfragt, welche Chancen eine derartige Lösung für die jeweilige Partei bietet und ob diese Chancen den möglichen Risiken überwiegen. Nach erfolgter Einführung in das Thema wird zunächst ein allgemeiner Überblick zu typischen Finanzierungsinstrumenten im Rahmen einer M&A-Transaktion gegeben. Es folgt eine Erläuterung zu den verschiedenen Möglichkeiten der Finanzierung des Kaufpreises durch den Verkäufer. Abschließend werden die aktuellen Entwicklungen auf dem M&A-Markt, insbesondere hinsichtlich der Finanzierungsstruktur von Transaktionen, beleuchtet, um zu erörtern, ob die Finanzierung durch den Verkäufer unter Annahme einer eingeschränkten, strengen Kreditvergabepolitik der Finanzinstitute zu einer Belebung des Transaktionsmarktes führen kann.
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,
Mihaela Butu Shareholder Activism by Hedge Funds Motivations and Market’s Perceptions of Hedge Fund Interventions Diplomica 2013 / 60 Seiten / 19,50 Euro
Copyright © 2013. Diplomica Verlag. All rights reserved.
ISBN 978-3-8428-8914-9 EAN 9783842889149
In recent years, hedge funds’ successful interventions in some large public companies have revealed their critical role in the corporate governance landscape in the United States and Europe. Due to public opinion, this new form of shareholder activism is accompanied by much polemic. This study examines the nature of hedge fund activism, the types of them, and the market’s perception of interventions in the United States. Starting with a distinction between shareholder activism by traditional institutions, and activism performed by hedge funds, the study elucidates why the latter may be more effective in monitoring management, and reduce agency costs. Analysing the Schedules 13D filed with the U.S. Securities and Exchange Commission, the study provides a classification of activists’ demands into ten distinct categories, arguing that hostile forms of activism are not central for hedge funds, and some more aggressive types of activism are possibly used as a negotiating tool to achieve the activist’s agenda. Using the event study methodology, the author estimates the stock returns around the announcement date. For a better understanding of hedge fund activism, and their demands on target companies, the reader will find two original Schedule 13D filings accompanied by letters to the management. Finally, the paper concludes on a view of the subject through the prism of the 2007/ 2008 financial crisis, outlining some trends in the aftermath of the financial market turmoil.
Listed Private Equity: Investment Strategies and Returns : Investment Strategies and Returns, Diplomica Verlag, 2013. ProQuest Ebook Central,