Portfolio Decisions for Faith-Based Investors: The Case of Shariah-Compliant and Ethical Equities 9783110611854, 9783110612189, 9783110612745

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Zaheer Anwer Portfolio Decisions for Faith-Based Investors

De Gruyter Studies in Islamic Economics, Finance and Business

Edited by Abbas Mirakhor and Idris Samawi Hamid

Volume 8

Zaheer Anwer

Portfolio Decisions for Faith-Based Investors The Case of Shariah-Compliant and Ethical Equities

Author Zaheer Anwer Associate Professor School of Business and Economics University of Management and Technology Lahore, Pakistan

ISBN 978-3-11-061185-4 e-ISBN (PDF) 978-3-11-061218-9 e-ISBN (EPUB) 978-3-11-061274-5 ISSN 2567-2533 Library of Congress Control Number: 2020949260 Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http://dnb.dnb.de. © 2021 Walter de Gruyter GmbH, Berlin/Boston Cover image: nnnnae/iStock/Getty Images Plus Typesetting: Integra Software Services Pvt. Ltd. Printing and binding: CPI books GmbH, Leck www.degruyter.com

Contents 1

Why Faith-Based Investing?

2

Screening Methodologies and their Implications

3

Comparative Performance of Faith-Based Portfolios 14 3.1 What Explains SRI Performance? 14 3.2 Comparative Performance of Faith-Based and Conventional Portfolios: Theoretical Underpinnings 15 3.3 Empirical Evidence of Comparative Performance 17

4

Screening and Dividend Payout Behaviour 22 4.1 The Disciplinary Role of Debt 23 4.2 Governance as Substitute of Debt for Minimizing Agency Conflict 25 4.3 Governance and Dividend Policy 26 4.4 Governance, Dividends and Idiosyncratic Risk 29

5

The Model 30 5.1 Data and Methodology 5.2 Results and Discussions

33 52

Summing up the Final Thoughts

88

6

References List of Figures List of Tables Index

107

95 103 105

1 8

1 Why Faith-Based Investing? Investment decisions are not only governed by factors like investors’ anticipation of future economic, geo-political and social changes, risk aversion, investment alternatives as well as preference regarding the timing of consumption1 but also religion or belief system. In recent years, a notable increase in this kind of investment decision making is observed and it has become a class of investments in its own right and plays an important role in selection of portfolios2–4. The religiosity and/or ethical practices prompt investors to discard so-called sin stocks and limit their investment horizons to permissible investment alternatives. This kind of faith-based investing (both the Shariah compliant and social responsible) can be divided in two branches namely Islamic finance and socially responsible investing (SRI). Islamic finance is an example of such a belief system that is governed by Islamic Shariah rules. For the Shariah-screened portfolios, the selection of class of assets and the securities in each selected class is subjected to Shariah requirements. Islamic law prohibits charging interest on loans, gambling and trade of impermissible items like liquor, pork, pornography etc. and also imposes restrictions on capital structure of the business entity5. The history of SRI or ethical investing is much older and dates back to the start of twentieth century6. The ethical investors are motivated by social, environmental, and ethical considerations in their investment decisions. They apply a set of investment screens to include or exclude assets based on ecological, social, corporate governance or ethical criteria7. The growing importance of faith-based investments can be judged by mammoth increase in the overall industry size. Islamic finance industry has observed a double digit compound annual growth rate (CAGR) of 17% between 2009 and 2013 and the size of industry is still expanding both in terms of numbers and geographical locations8. In the similar manner, the volume of assets acquired through socially responsible investing strategies stood at 8.72 Trillion USD in 2016 and the number is expected to further increase in coming years9. There is potential for further growth for this faith-based investments since religious or ethical values are becoming a matter of concern to most investors even if they have to earn lower risk-adjusted returns compared to returns on conventional investments with similar risk7. Several factors can be held responsible for the proliferation of these investment styles. To begin with, Bollen10 points out the presence of a multi-attribute utility function for faith-based investors that is not only dependent on the standard riskreward optimization paradigm but also takes into account a set of personal and societal values. In addition, another likely reason for growth in faith-based investment styles is the recent reporting of accounting and environmental scandals in business ethics literature11. Therefore, this kind of investment serves dual purpose by combining financial goals of investors with their moral and social concerns12. Moreover, the growth drivers of Islamic finance, over the last few decades, are oil https://doi.org/10.1515/9783110612189-001

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1 Why Faith-Based Investing?

money, growing Muslim population and increased awareness about investing and financing based on Shariah requirements13. In order to make the investment compliant to the principles of faith-based investing, the investment managers and index providers employ qualitative and quantitative filters so as to screen the investment universe and discard the stocks that do not meet the prescribed criteria. Ethical screening procedure is twofold: it excludes investment in industries like tobacco, alcohol, gambling, weapons, pornography, abortion, workforce exploitation, activities not friendly to environment, human rights violations and genetic engineering whereas it promotes investments in industries with better labour protection, environment friendliness, corporate governance, human rights, biotechnology and shareholder activism7. Various mutual funds and equity indices follow these screen methodologies to formulate their so called socially responsible portfolios. To perform Islamic Screening, Dow Jones and other vendors employ two criteria namely ‘line-of-business screens’ and ‘financial ratio screens’ while deciding investment universe14. These screens are subsequently used to constitute various Shariah indices. These Shariah screening results are endorsed by a board of highly renowned independent Shariah scholars. The first criterion is qualitative and stipulates exclusion of impermissible businesses like interest (riba), pork, activities involving extreme risk taking (gharar), gambling (maysir), weapons and defense, pornography etc. The second filter excludes the companies having 1) revenues in excess of 5% from the impermissible business activities 2) total debt and/or monetary assets accounting for 33% or more of market capitalization (24-month average) 3) account receivable more than 33% of their total assets/ market value of equity (24-month average) and 4) cash to market value of equity (24-month average) higher than 33%. This screening can affect portfolio formation in multiple ways that, in turn, influences the risk-return profile as well as dividend policy decisions of the firms: To begin with, due to qualitative and quantitative screening, the investment universe for these two special classes of investors is restricted limiting the fund managers’ ability to exploit superior information as well as an opportunity to invest in winning markets15 and consequently may constrain on diversification opportunities that will lead to the persistent presence of idiosyncratic risk in these portfolios. It should be noted, however, there is evidence of unsystematic risk even in well diversified portfolios16–18. To explain this issue, Merton19 presents investor recognition hypothesis that states that since it is costly for investors to obtain information regarding all the securities in the market, they construct their portfolios from securities on which they have information and are familiar. As they hold underdiversified portfolios, they require compensation for idiosyncratic risk of the securities. Faith based investors face similar situation and need to acquire the information regarding the permissible securities. Consequently, their portfolios may also be under-diversified due to at least two reasons: they are unable to bear this information cost required for search adequate number of acceptable securities or even

1 Why Faith-Based Investing?

3

when they can spend on information acquisition, the securities within available universe are insufficient to achieve the desired portfolio diversification. Still, there are possibilities that even after screening, the portfolio is well diversified and the level of idiosyncratic risk is not different from the market. Finally, although market portfolio is believed to be devoid of idiosyncratic risk, the evidence postulates that this can only be the case in frictionless markets and since, in reality, markets are not frictionless, even market portfolios possess idiosyncratic risk18,20. Evidently, present evidence on under-diversification issue for faith based portfolios is inconclusive and there is no firm conclusion on the presence of idiosyncratic risk in screened portfolios as well as market portfolio. It is therefore worthwhile to ascertain whether faith based and socially responsible portfolios are different from market portfolios in terms of idiosyncratic risk. At present, there is no documented evidence and this study addresses the gap on this issue. Moving Further, possible under-diversification and presence of idiosyncratic risk could affect the relative performance of these investments. There can be various possible theoretical arguments favouring this proposition: Firstly, the universe of stocks selection of faith based portfolios is restricted and there is a possibility that investors forgo many attractive investment opportunities due to religious or ethical restrictions. In a CAPM world, these investors are at a disadvantage owing to the fact that they cannot optimally diversify their portfolios due to restriction on certain business activities and the high correlation within the permissible stocks21. They also need to bear cost for searching and monitoring securities that could negatively affect their returns22. There is inconclusive evidence of performance of these portfolios and studies like Cortez, Silva23, Saeed and Hassan24, and Lean, Ang25 show that holders of faith based portfolios are not at disadvantage, whereas Al-Khazali, Lean26, Kamil, Alhabshi27, Merdad, Kabir Hassan28 and Boo, Ee29 documented that these portfolios underperform the benchmark. An important reason of this underperformance is lack of diversification opportunities for such investors30,31. Secondly, in addition to under-diversification possibly due to negative screening, the outcomes of financial screening may also influence the performance of Shariah compliant firms32 in the following ways: 1. The first ratio i.e. Debt/Market Equity ratio has a significant impact on stock returns for any firm. This ratio represents a firm’s financial structure and a high debt to equity ratio implies that the firm uses debt financing assertively. Since debt is a cheaper source of capital, the high debt firms can start more value enhancing projects as compared to the firms with low debt. On the other hand, higher debt ratio increases the financial risk and the returns are more volatile for the highly leveraged firm. Therefore, the final impact of screening, made upon the basis of debt/equity ratio, on firm’s performance and volatility remain ambiguous. 2. The second ratio i.e. Receivables/Market Equity reveals the proportion of firms’ receivables with respect to its market value. The receivables are instrumental in

4

3.

1 Why Faith-Based Investing?

shaping a firm’s capability to develop long-term relationship with its clients and build strong business networks. The high value of account receivables indicates that the firm has effective sales network and loyal customers and the firms having high receivables may have sustainable sales network. However, the high amount of receivables can also be alarming if a significant portion comprises of toxic assets. Therefore, the final impact of this ratio on the firm’s performance and risk is also vague. The third financial ratio i.e. Cash/Market Equity is related to the amount of cash and marketable securities available to the firm. If the amount of this asset is low, it indicates that the firm is unable to start positive net present value projects owing to its inability to make large capital expenditures. This lack of investable funds has long term implications for the future performance. However, the firms having high amount of cash are inflicted by severe agency problem owing to opportunistic behaviour of managers33,34. Therefore, the firms with high cash may underperform in the long run. Hence, the impact of the third ratio on firm performance is also inconclusive.

Thirdly, another strand of literature argues that Islamic investments offer lower returns as they are lesser risky due to avoidance of high leverage35,36. Interestingly, Arouri, Ben Ameur37 assert that Islamic indices bear high risk due to under-diversification and therefore offer high returns. It is important to note that existing evidence is not only inconclusive but also focused mostly on equity indices and investment funds only. Fourthly, the similar results for conventional and SRI can be explained with the help of mainstreaming argument presented by Erragragui and Lagoarde-Segot38 who point to the double process of upstreaming ‘ethical stocks’ into conventional indices and portfolios, and ‘down streaming’ of conventional stocks into ethical indices and portfolios. It is expected that due to this double process the rates of return of both kinds of portfolios/indices should be similar. Therefore, it is evident that the research on the performance of faith-based portfolios is inconclusive. Moreover, most of the studies were conducted for mutual funds but not firm level analysis. If Jensen’s alpha is calculated at portfolio level instead of index or fund level, it is possible to use different variables like firm size, price-to-book ratio, market risk, momentum etc. to define stock returns. Furthermore, the funds are subjected to fund managers’ biases and there may be a substantial role of judgement in their strategy. Similarly, indices that follow a passive strategy might not be a good proxy for measurement of portfolio performance. The abnormal return measured at portfolio level (comprising of Shariah compliant and SRI firms) would be more reliable as it will weigh distinct attributes of securities that are not taken into the account at index or fund level. Therefore, research focusing on firm level analysis is required to observe the risk-adjusted performance of faith-based and socially responsible portfolios.

1 Why Faith-Based Investing?

5

Finally, the faith-based firms are expected to be better governed and hence they may adopt different payout policies from conventional firms. It is important to shed some light on this issue: The recent empirical literature suggests that the two most important channels for disciplining managers and reducing agency cost i.e. high debt and good governance hold inverse relationship39. More formally, in addressing agency issues, high debt and good governance are substitutes and the low debt firms are better governed40. Shariah compliant firms are low debt and in line with this argument, are expected to be better governed. Additionally, these firms are deemed to be better governed owing to their higher transparency and better quality of financial reporting. It is worthwhile at this point to list some important institutional factors that determine the linkage between Shariah compliance and quality of financial reporting41. Firstly, Islamic law stipulates that the business activities should be carried out in a transparent manner42. Hence, Shariah compliance, at least principally, provides investors with reliable and relevant information that can be subsequently used to make well informed investment decisions43. Secondly, the business activities of Islamic financial institutions are screened by a Shariah board that serves as an additional layer of inspection and improves governance. Finally, Shariah-compliant firms also face greater scrutiny from external institutions as well as investors to ensure that their business conduct is within Shariah principles. Therefore, teachings of Islamic law, Shariah boards and stricter external monitoring define the linkage between Shariah compliance and better financial reporting. We further assert that, in addition to Shariah firms, SRI firms are also better governed as they do not hold so called ‘sin’ stocks. Our argument is based on Hong and Kacperczyk44 who show that sin stocks have lower governance quality due to at least two reasons. Firstly, these stocks are neglected by institutional investors and hence their monitoring mechanism is weak. Secondly, the sell-side analysts ignore these firms that results in lower analyst coverage, poor visibility and lesser developed governance structure. Consequently, the faith-based firms are expected to have better governance. If the governance structure of these firms, in turn, is better, there is a possibility that they adopt payout policies different from conventional firms. Now we are set to review the literature on governance-payout relationship as documented in contemporary studies. The literature on payout and governance presents two divergent views. The substitute hypothesis indicates that good governance discourages dividend payout because firms with good governance will hold excess cash and invest in growth projects while in the firms with weak governance, managers are disciplined to distribute excess cash to shareholders instead of using it in wasteful projects45–47. Conversely, the complements hypothesis asserts that good governance encourages dividend payments as good managers would distribute excess cash to shareholders through payout or repurchases whereas selfmotivated managers would be constrained by strong governance to hold cash for

6

1 Why Faith-Based Investing?

investment in the projects offering long term benefits to the organization48–51. Accordingly, in line with our previous argument, it is probable that the relationship of governance and dividend payout assumes a different shape for faith-based portfolios as compared to their conventional counterparts, possibly due to their different corporate governance levels. Our motivation of different dividend payout strategies for faith-based portfolios is based on another strand of literature which argues that the governance and dividend payout can either be substitutes or complements depending upon the level of idiosyncratic risk. If the firm faces high idiosyncratic risk, there are chances of underinvestment and good governance in this case would discourage payout to boost investments while the firms with low idiosyncratic risk would be tempted to overinvest and good governance would encourage payout to reduce overinvestment52–54. Evidently, if faith based portfolios have different idiosyncratic risks, the relationship of governance and payout might be different for such portfolios. We therefore contend that it is probable that governance-payout linkage can be different for faith based stocks owing to better corporate governance and possibly different levels of idiosyncratic risk. There is no documented evidence on this subject and this study addresses this gap. In the light of above discussion, it is evident that Shariah and socially responsible investors bear the cost for their belief system in the form of under-diversification and additional monitoring cost. The contemporary literature argues that asset allocation explains more than 90% of returns over time55 and when portfolios are subject to specific screening, asset allocation decisions are not independent. As a result, the investors may be unable to achieve a higher efficient frontier and they have to be content with sub-optimal portfolios owing to investment constraints imposed by the screening filters. They also need to incur cost on continuous screening of the stocks due to the possible changes in line of business of some of the firms or changes in their capital structure that fail to fulfil the screening requirements. Therefore, apparently these investors face unique challenges as compared to the ordinary investors and their risk/return profile might differ. However, it is also probable that even after screening, there are adequate stocks within the screened universe for offering diversification benefits. Also, the monitoring cost may be minimal and does not affect the returns. This is an important empirical issue of whether these special investment styles are in reality cost ineffective and disadvantaged compared to normal portfolios of similar risk. It is obvious that many clichés are attached to faith based investments without empirical evidence. At present, there is no evidence documented on whether screened portfolios are in reality under-diversified and offer lesser investment opportunities. The existing studies (like Ashraf and Khawaja56 and el Alaoui, Bacha57) discuss only systematic risk of these portfolios. Although one argument suggests that screening results in shifting the mean-variance efficient frontier (MVEF) to the right as

1 Why Faith-Based Investing?

7

advanced by Johnson and Neave58, the counter argument posits that screened portfolios avoid very risky firms (having a higher probability of financial distress and bankruptcy) and therefore, their total risk would be lower than the market pulling the MVEF back to the left59. Similarly, one argument suggests that negative screening enhances portfolio risk and results in under-diversification60, the counter argument indicates that screening reduces systematic risk and hence the total risk for screened portfolios will be low61. In line with these conflicting arguments, it is probable that there are still enough diversification opportunities available within the investment universe that can help investors choose the efficient frontier of their choice and does not restrict investment decisions. Furthermore, their idiosyncratic risk can be higher than market portfolio due to possible under-diversification or lower due to ‘shunned stock hypothesis’ and we are not aware of the exact situation. Moreover, there is no evidence whether risk adjusted comparative performance (firm level) of these portfolios is better or worse than the market. Finally, better governance and unique idiosyncratic risk of faith based portfolios may or may not result in changing the relationship of governance and dividend policy for faith based stocks. At present, these questions are unanswered and it is desirable at this stage to know the answers to clear doubts regarding this investment style and help investors in forming more informed decisions. These questions are not of merely academic in nature but have many practical implications for the investment industry.

2 Screening Methodologies and their Implications There can be three main components of religiosity namely 1) a salvation motive (that is influenced by the idea of after-life utility) 2) a consumption-of-religious-experience motive (that seeks utility from going to church and taking part in religious and nonreligious activities with fellow church members) and 3) a social-pressure motive (that refers to obtaining utility from belonging to a club62). Therefore, it can be inferred that when a religious or socially responsible investor accepts lesser rates of return in line with his beliefs, he is ready to accept the opportunity cost of piety. Following a this line of arguments, it can be inferred that there are three groups that seek to invest in Islamic finance63. The first in line are the people motivated by economic incentives. The second group comprises those who are keen to observe moral values but they do not observe any religion in particular. The third group is primarily motivated by religious principles. In order to account for the ethical beliefs of such investors, the process of negative screening had been introduced in order to discard the sectors like Tobacco, Alcohol, Gambling, Weapons, Pornography, abortion, workforce exploitation, activities not friendly to environment, human rights violations6. In the periods after 1970s, the fund managers and index providers started applying positive screening as well. This screening, known as Environmental, Social and Governance (ESG) Screening, promotes investments in industries with better labour protection, environment friendliness, corporate governance, human rights, biotechnology and shareholder activism. Presently, various mutual funds and equity indices follow these screen methodologies to formulate their so called socially responsible portfolios. The investor interested in Islamic equity investment can only choose those companies that are Shari’ah compliant companies and the viable investment channels for them are publicly offered portfolio comprising unit trusts, mutual funds and Exchange Traded Funds14,64. The prominent service providers like S&P Dow Jones, FTSE and MSCI launched various such indices to capture this growing market. The determination of Shari’ah compliance is made by Shari’ah boards of these funds/indices. Interestingly, to ensure the Shari’ah compliance, each board has set different rules in order to screen equities. The main reason for this divergence of opinion is the absence of such guidelines from the main sources of Islamic jurisprudence i.e., the Quran, the Hadith and the Ijmaa. Shariah boards derive Shariah screening principles. Shariah scholars, therefore, use the principles of analogy (Qiyas) and use the past rulings of a similar nature to derive new rulings. As Qiyas is more of a personal interpretation (instead of a uniform ruling), there are possibilities of divergence of opinions among Shariah scholars on the issues settled upon the basis of Qiyas. As a result, there are multiple versions of Shariah screening standards that differ significantly on the issue of quantitative screening. There are many differences in degree of conservativeness of these screening criteria that https://doi.org/10.1515/9783110612189-002

2 Screening Methodologies and their Implications

9

leads to confusion among the investing community. Moreover, the existence of different screening criteria could affect the performances differently. There are two levels of screenings i.e. qualitative and quantitative screenings. The qualitative screenings is almost uniform and exclude shares of all such companies that are involved in business dealing with financial transactions involving interest, gambling, intoxicants, pork and/or excessive risk taking. Quantitative screening is used to further screen companies having a portion of revenue from non-permissible activities such as borrowing or lending money on interest and/or have a high debt/receivables/cash above a certain threshold. This screening is made by using different financial ratios and the calculation of these ratios is quite controversial within the Muslim community. Some criteria use the market value of equity (MVE) as a divisor for the calculation of leverage and liquidity ratios while others use the book value of total assets (BVTA) to calculate financial ratios. More specifically, when the financial ratios are calculated trailing market value of equity, the portfolios require very frequent rebalancing. On the other hand, when book value of equity is used to calculate these ratios, the rebalancing requirement considerably reduces. It should be kept in consideration, while discussing Shariah screening methodology that these ratios are arbitrary and scholars have allowed their use in view of the need of time (Darurah). Accordingly, comparatively recent literature suggests that it would be more appropriate to include the ESG criteria in forming ethical/Shariah portfolios in order to ensure conscious effort from managers to run business in a transparent and socially responsible manner. The firms voluntarily involved in corporate social responsibility initiatives improve their reporting standards and they are lesser likely to manipulate their earnings41. However, the membership of Shariah index does not influence the ethical conduct of a firm owing mainly due to the reason that this member ship does not act as a proxy for religion. In other words, this membership only certifies that the firm is not involved in any unethical activity or its capital structure does not violate Shariah rulings. This can be a mere coincidence that the firms become part of such indices, especially when only negative screening criteria are used. The merging of ESG criteria with Shariah screening will also pave the way for the entry of institutional investors in Islamic finance sector that, at present, is a big challenge for this emerging industry65. The emergence of SRI funds due to public aversion from social evils, wars, racism and undesired business activities and Islamic finance owing to religious beliefs has important implications for modern portfolio theory. The SRI strategy integrates ethical, social and environmental considerations through applying investment screens7 whereas Islamic finance divides business transactions in permissible (halal) and forbidden (haram) activities66. This investment screening shrinks the investable universe for portfolio formation and may result in under-diversification of portfolio due to the presence of idiosyncratic risk. It is necessary, in order to elaborate this

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issue, to refresh the basic concepts related to diversification and optimal portfolio selection: Markowitz asserts that all investors are risk averse and attempt to achieve a portfolio having optimal risk-return trade-off67. For any given two portfolios offering the same expected return, investors will prefer the portfolio with lower risk. Hence, an investor will assume increased risk only when it would be compensated by higher expected return. In the similar manner, an investor who needs higher expected returns has to accept higher risk. Consequently, the exact risk return trade-off will be the same for all investors but due to individual risk aversion characteristics, different investors would evaluate this trade-off differently. Therefore, a rational investor will not invest in a given portfolio if another portfolio exists having higher expected return for the same risk. In this model, portfolio return is equal to the weighted average of the constituent assets’ returns and portfolio variance is a function of the correlations of the component assets. Portfolio risk can be expressed as σ2p =

X i

w2i σ2i +

XX i

wi wi σi σj ρij

(2:1)

j≠i

The portfolio risk can be reduced by holding combinations of assets that are not perfectly positively correlated. More formally, they can reduce their asset specific risk exposure by holding multiple assets thereby creating a diversified portfolio of assets. The diversification can result in the same portfolio expected return with reduced risk. In equation 2.1, if all the asset pairs ‘i j’ are uncorrelated (having zero correlations), the portfolio’s return variance would be minimum whereas if all the asset pairs ‘i j’ are perfectly positively correlated having correlations equal to ‘1’, the portfolio’s variance would be maximum. Moving further, the risk-return opportunities that are available to the investors can be summarized in the form of minimum-variance frontier of risky assets32. The optimal opportunity set on this frontier is known as Markowitz efficient frontier. The portfolios having lower number of assets are generally not a part of this efficient frontier. However, there may be cases when some customers face additional constraints in shape of prohibition on short positions. In such scenarios, it is probable that single assets may be, in and of themselves, efficient risky portfolios. For example, the asset with the highest expected return will be a frontier portfolio as, in the absence of the opportunity of short sales, the only possible way of obtaining that rate of return is to hold the single asset as the entire risky portfolio. It is important to bring the capital asset pricing model (CAPM) in the picture now as it is rated as ‘centrepiece of modern financial economics’ and capable of predicting relationship between risk and of asset and its expected return. CAPM asserts that investors will hold a portfolio of risky assets that will mimic the market portfolio (M) including all the assets traded in the market. This portfolio will be market capitalization weighted and would be on efficient frontier. The risk premium on market

2 Screening Methodologies and their Implications

11

portfolio will be proportional to average level of risk aversion of investors. This portfolio will be fully diversified and its variance will be equal to systematic risk. CAPM offers expected return-beta relationship that has the power to explain excess return offered by assets. This relationship can be defined as Eðri Þ = rf + β½EðrM − rf Þ In this equation, the excess return on assets is the sum of two factors: the risk free return and the product of beta and market risk premium. However, in reality, the investors do not hold market portfolio but a well-diversified portfolio is expected to be highly correlated with market portfolio and in various cases, the beta of such a portfolio relative to market will be a useful risk metric. However, even the so called diversified portfolios are not free from idiosyncratic risk as the markets are not frictionless18. In this respect, there is a well-documented literature on under-diversification myth that blames personal preferences of investors, in addition to investment constraints, for the failure to achieve portfolio diversification. To begin with, it is argued that the idea that investors have homogenous expectations and their estimates are identical is flawed68. The uncertainty and risk are related to the difference of opinions and the conflicting views of investors regarding securities that can increase idiosyncratic risk. In a short sale constrained market, the returns can be lower even for the high risk securities owing to the disagreement among investors regarding the outcomes of investment decisions. For example, there may be optimism about a security within a certain group of investors whereas the others may hold pessimistic views about it. Therefore, the securities can be overvalued in such markets as the pessimists are not allowed to short the stocks. In such situations, the idiosyncratic risk emerges as a proxy for divergence in opinions as the investors are unable to hold a market portfolio. Moving further, the investors may face other constraints on holding all securities (as CAPM suggests) such as the financial inability, divergence of opinions or the frictions in the market (in shape of regulations, transaction charges, investment constraints, imperfect divisibility of shares etc.) and therefore, the available market portfolio becomes less diversified compared to the actual market portfolio69. This difference of opinion may be the result of the incomplete information available to investors and/or the capital constraints that they face leading them to choose the familiar stocks and resultantly, their portfolios do not achieve diversification19. The basic intuition behind this argument is that it is not plausible for investors to track every security in the market as it is a costly affair to acquire relevant information. These under-diversified investors require compensation for securities’ idiosyncratic volatility. If Merton’s intuition is correct, not only idiosyncratic volatility is priced in the cross-section of returns but it is also priced conditionally depending upon the visibility of each stock16. There can be other factors like income, age, sophistication (both general and financial), risk appetite and behavioural biases like

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over-confidence and familiarity with the degree of diversification that can force the investors to choose under-diversified portfolios70. There are various empirical studies that validate these findings. Boehme, Danielsen71 provide empirical evidence of Miller’s model and relate mispricing of firm to both pessimism and restrictions on short sale. They further show that during their sample period 1988–2002, only those portfolios of firms were overvalued that possessed both short-sale constraints and dispersion of beliefs and presence of merely one of these factors did not result in overvaluation. Mertzanis and Mertzanis72, Lee, Wang73, Li, Lin74 and Gulati, Bose75 validate Miller’s hypothesis for stock markets of Greece, Korea, China and India respectively. These studies highlight that although short selling increases volatility, it results in persistent profitability and increased liquidity and short sellers exploit short run price reversals with the help of their information processing ability to earn higher profits. We have reported these studies to emphasize that constraints on short selling may result in inefficient markets and under-diversification. The presence of idiosyncratic risk has prompted the researchers to investigate how it is priced in the market. The conventional knowledge stipulates that the higher risk should be compensated with higher returns and one group of researchers has found that stocks with high idiosyncratic risk yield higher returns. Spiegel and Wang76 found that expected stock returns increased with the level of idiosyncratic risk and its explanatory power with respect to returns was very high. Their sample included monthly stock returns for US market for the period 1962–2003. Fu17 also found similar results for their sample of US companies for the period 1962–2003. On the other hand, Ang, Hodrick20 found that stocks with past high idiosyncratic volatility had low average returns. Their sample covered the period 1963–2000 for US market. Their findings were further validated by Ang, Hodrick18 who observed that this pattern was valid for 23 developed economies including G-7 countries as well for a sample period 1963–2003. In this respect, Cao and Han77 found that average stock returns monotonically decreased (increased) with idiosyncratic risk in case of relatively overvalued (undervalued) stocks. However, for the stocks that could neither are categorized as neither undervalued nor overvalued, the returns were unrelated to idiosyncratic risk. In the light of above review, it is evident that the screening methodologies exert constraints on portfolio formation and may result in extra cost to the investors as they would be forced to accept higher risk. In reality, therefore, these faith based investors, constrained by their ethical and religious beliefs to avoid certain industries/investments may be holding under-diversified portfolios. These portfolios, resultantly, would possess higher idiosyncratic risk, in addition to the systematic risk, due to lack of diversification. Furthermore, the existing literature supports the proposition that faith based investors may be holding under-diversified portfolios as they have ethical constraints

2 Screening Methodologies and their Implications

13

on selection of stocks in comparison to the ordinary investors. However, to date, there is no documented evidence to suggest under-diversification due to ethical or religious beliefs. This study addresses this issue by estimating the idiosyncratic risk for faith based stocks at portfolio level. Furthermore, the idiosyncratic risk is also calculated at the stock level as well and averages are reported for portfolio level as well as with respect to industrial sectors and it is hoped that this information can be an important contribution to contemporary literature.

3 Comparative Performance of Faith-Based Portfolios As faith-based investors face idiosyncratic risk, they require extra compensation for bearing this additional risk. It is also probable that they pay a price in shape of same expected return against higher risk. The existing literature offers different insights regarding risk adjusted performance of SRI and Shariah portfolios. In this regard, SRI is much older and established as compared to Shariah investments and therefore considerable knowledge is available on competitive performance of SRI funds.

3.1 What Explains SRI Performance? There can be two kinds of SRI investors namely values driven who primarily seek solace in fulfilment of their social objectives and ready to bear cost of their beliefs and profit seeking ordinary investors looking for superior returns78. Their behaviours and possible anomalies attached to them can be explained with the help of following two hypotheses: 1) The shunned-stock hypothesis states that socially controversial stocks should have superior returns owing to the fact that value-driven investors shun and accordingly push their prices below those of responsible stocks. The empirical evidence of this hypothesis was provided by Hong and Kacperczyk44 for US (1926–2006), Salaber79 for European market (1975–2006) and Fabozzi, Ma80 for a cross country sample of 21 countries (1970–2007). 2) Salaber2 assessed the impact of religious preferences of investors on expected stock returns for the period 1981–2006. Their sample included 12 European countries and they considered European settings ideal owing to highest Alcohol consumption rate and huge presence of Christian population in these countries. They observed that religious preferences significantly affected share prices of sin stocks. They also observed that sin stocks were deliberately ignored by investors in Protestant countries and these investors required higher premium to invest in sin stocks. Conversely, in Catholic countries, sin stocks offered no premium. 3) The errors-in-expectations hypothesis forecasts higher risk-adjusted returns for socially responsible stocks owing to the reason that the market would be slow to recognize the positive impact of strong corporate governance practices on companies’ expected future cash flows. So, the stocks having higher environmental and ratings outperform companies that have low scores for a specific periods and achieve abnormal returns. The studies like Derwall, Guenster81 for US (1995–2003) and Kempf and Osthoff 82 for US (1992–2004) validated this hypothesis. However, Galema, Plantinga83 for US (1992–2006) and Edmans84 for

https://doi.org/10.1515/9783110612189-003

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US (1984–2006) did not find any significant empirical evidence supporting this hypothesis, but documented that SRI is capable of affecting performance in the long run and ensures superior long-horizon returns.

3.2 Comparative Performance of Faith-Based and Conventional Portfolios: Theoretical Underpinnings The existing literature offers three different hypotheses to explain the performance of screened portfolios in comparison to the conventional investments namely the underperformance hypothesis, the outperformance hypothesis and no difference hypothesis85. The underperformance hypothesis takes the inspiration from modern portfolio theory and states that ethical or Shariah screening results in shrinkage of the investment universe and hence it produces a lesser efficient mean–variance efficient frontier. Furthermore, the fund managers are left with significantly lower number of securities to invest and the opportunities of profiting from stock selection are reduced. This situation limits the stock selection ability of Shariah and ethical fund/ portfolio managers and leaves them in a position inferior to their competitors. It becomes a daunting task for them to match the returns of their funds/portfolios, for a given level of total risk, with the competitors that are not constrained by investment screens. The situation worsens when the market sentiment shifts towards the sectors that are excluded and fund managers of faith-based portfolios cannot benefit from this opportunity. Shariah law also puts restrictions on investment strategies like speculative trading, leveraged-trading, short selling and margin trading and fund managers cannot earn profits by exploiting these strategies even if they are skilled enough to do so. Another issue faced by faith-based investors is the financial cost they bear for the selection of stocks in pursuit of their values. Consequently, the fund managers charge high management fees to perform selection as well as purification services by excluding the returns (mostly in shape of interest or dividends from subsidiaries involved in prohibited activities) from non-halal sources. Finally, the faith-based portfolios may exhibit higher agency costs than conventional investment vehicles owing to the multiple objectives of these entities. In contrast to a traditional fund manager whose prime focus is on the sole target i.e. profitability, the performance of a faith-based fund managers is assessed additionally upon the basis of non-financial indicators i.e. stock screening. This additional exercise can potentially distract managers from their key role i.e. generating returns for the investors. Therefore, in line with these arguments, there is a possibility that faith based portfolios underperform as compared to the conventional portfolios. On the other hand, the outperformance hypothesis postulates that the ethical funds have the tendency to outperform their conventional counterparts in the long run as it is only in the short run that the capital markets undervalue corporate

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social responsibility86. There are several arguments in favour of this hypothesis. Firstly, the SRI approach requires assessment of the environmental, social and governance profile of the companies. In this endeavour, the fund managers are capable of identifying various risks that are not captured by the eyes of traditional fund managers. The profit-above-all-focused strategy is short sighted and prone to ignore vital risk indicators and embrace avoidable risks. SRI firms are better governed and capable of forecasting these risks in a much more effective manner. Secondly, SRIs restrain from investment in the sectors that are, generally, not viewed favourably by people. Therefore, the ethical standards can become a source of competitive advantage for the firms in the markets with well-informed consumers87. The Shariah compliant firms stay away from excess risk taking, gambling and leverage. These practices can, admittedly, increase the profits but on the flip side, they result in manifold increase in the portfolio risk that can lead to huge losses. Thirdly, the effective screening can result in sound social and environmental performance that can produce positive impact on the reputation of the firm and increase the firm’s profitability. Fourthly, the faith-based investors are more loyal as compared to the ordinary investors and they do not divest their holdings merely due to the short term return reversals or unfavourable market conditions88. Accordingly, the customer loyalty can produce cost efficiencies due to reduced turnover and saving of transaction costs. Farooq and Zaheer89 observed somewhat similar behaviour as they pointed out that the customers of Islamic banks made lesser deposit withdrawals during financial panics as compared to the conventional bank depositors that, in their view, was an outcome of religious branding. As a result, the SRI portfolios may outperform the conventional portfolios. The outperformance hypothesis is expected to be more meaningful for Shariah compliant firms during crisis periods. To begin with, the presence of low amounts of debt on balance sheet of Shariah compliant firms makes them relatively immune from the credit crunch. The leverage effect increase volatility of earnings and resultantly, the stock prices drop more sharply during market downturns. Moving further, the Shariah restrictions on speculative trading practices and complex financial instruments like derivatives proved useful for Islamic equity funds during global financial crisis. Finally, the profit/loss sharing principle of economic transactions advocated by Islamic finance requires the entities to provide maintain high level of disclosure and transparency in the reporting of financial information. This practice enables the analysts to price the Shariah firms more appropriately and there is lesser likelihood for these firms to be mispriced in normal circumstances. Therefore, the share prices for these firms are expected to be more stable during the crisis. The convergence or no difference hypothesis argues that SRIs/Shariah firms perform similarly to conventional investment vehicles and the screening does not affect performance. There can be several justifications for this hypothesis to hold. Firstly, there is a possibility that majority of the funds discard unethical investment due to its poor prospects and invest in the ethical firms having expected positive future

3.3 Empirical Evidence of Comparative Performance

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cash flows7. The trend of conventional funds adopting ethical practices is increasing due to the investors’ recognition of ethical values and many of the conventional funds are practically indistinguishable from SRI funds90. Secondly, the possible unwillingness of ethical investors to sacrifice returns in pursuit of their social or moral values may prompt the fund managers to soften their screening criteria and widen their investment universe. In this scenario, they will be able to shape investment strategies in line with conventional managers and their returns would converge with conventional funds. This practice however is very rare and cannot sustain in the long run. Besides, the Shariah funds cannot adopt this practice because their screening exercise and other activities are monitored by Shariah supervisory board that ensures the compliance of funds’ activities with Shariah rulings. Finally, in line with efficient market hypothesis67, the funds cannot outperform the market purely upon the basis of available public information. The ethical screening is mostly public information and the conventional fund managers can also utilize this information to follow SRI strategy, if they desire to do so or mandated by the investors. Consequently, unless the screening information is obtained after incurring information costs, it cannot produce superior returns for SRI portfolios/funds. Therefore, these arguments suggest that the performance of faith-based portfolios may not be different from their conventional counterparts.

3.3 Empirical Evidence of Comparative Performance Although there is lack of consensus on the SRI performance, various studies have documented the comparative performance of SRI and conventional funds for US and other markets and found conflicting results. The first group of studies finds no significant difference in the performance between SRI funds and conventional funds. For example, Bauer, Derwall11 showed that there was no significant difference in the performance of these two asset classes during the period 1994–2003. They also could not find any difference in investment style exposure of ethical and conventional funds mangers. They used Jensen’s alpha using CAPM and factor models as measures of risk adjusted performance. Renneboog, Ter Horst86 found that, for their global sample of 17 countries, SRI funds significantly underperformed in comparison to their benchmark but their alphas were not significantly different from conventional mutual funds. Their sample included 440 SRI and 16,036 non-SRI mutual funds and they covered the period 1991–2003. However, the second group found that SRIs out performed conventional investment vehicles. In this respect, Cortez, Silva23 observed that SRI funds performed better than conventional funds during the period 1996–2007. They investigated the performance of 88 European SRI Funds from developed economies using Jensen’s Alpha as a measure of performance.

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Nofsinger and Varma90 investigated the performance of SRI equity funds in US during and after the crisis for a sample of 240 US SRI funds for the period 2000–2011. They estimated alphas using three different models for crisis and noncrisis periods and found that overall, alphas for SRI and conventional funds were not different from each other. However, in crisis period, SRIs outperformed conventional funds whereas in non-crisis period, conventional funds performed better. The outperformance in crisis periods was mainly owing to the mutual funds that focused on shareholder advocacy and environmental, social, and governance (ESG) issues. SRI funds that focused on sin stocks or other screening criteria and funds that were driven by faith or religious principles did not outperform in crisis periods. They concluded that it was positive screening (looking for the desirable attributes) as compared to negative screening (looking for the absence of undesirable characteristics) that was associated with positive alphas during meltdown economy. Lean, Ang25 assessed the performance of 500 European and 248 North American mutual funds for the period 2001–2011 and found that SRI funds outperformed conventional funds in both the markets. Furthermore, North American funds performed better than European funds. To explore a different dimension, El Ghoul and Karoui91 examined the impact of corporate social responsibility on fund performance for a sample of 2,168 US mutual funds for the period 2003–2011. They found that corporate social responsibility negatively affects performance. Still, it is instrumental in attracting social responsible investors who derive utility from non-financial attributes. The performance analysis of Shariah compliant mutual funds/indices is also depicted in contemporary studies. The empirical studies comparing performance of Shariah compliant equity indices and mutual funds with their SRI and conventional counterparts suffer from a serious limitation due to the difference in screening criteria used by various index providers affect the performance of different indices even when the stocks are selected from the same universe14,56. Keeping in view this limitation, we provide a brief overview of existing empirical literature on performance comparison of Shariah portfolios with SRI and conventional portfolios. Hussein and Omran92 investigated the behaviour of Islamic indices for the period 1996–2013 during both bullish and bearish markets and found that Islamic funds yielded significant abnormal returns in bull markets but they could not perform well during bearish markets and the returns were negative. Al-Khazali, Lean26 used stochastic dominance (SD) analysis to examine whether Islamic stock indexes outperformed conventional stock indexes. Their sample included nine Dow Jones Islamic indices and nine Dow Jones conventional indices. They found that in the periods of 1996–2012 as well as 2001–2006, all conventional indices stochastically dominated Islamic indexes in almost all markets. Nevertheless, the European, US and global Islamic stock indexes dominated conventional ones during the period 2007–2012. Most importantly, the results indicate that Islamic indices outperformed their conventional counterparts during global financial crisis. It appears that Islamic

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investing performance is better than conventional investing during periods of market turmoil. Abdelsalam, Fethi93 compared the performance of SRI and Islamic mutual funds using two stage analyses. In the first stage, the performance was analysed using partial frontier methods and they used quantile regression in the second stage. Their sample included 138 Islamic funds and 636 SRI funds for the period 2001–2011. In the first stage analysis, they found that the average efficiency of SRI funds was slightly as compared to Islamic funds. However, the differences were not found to be statistically significant in the second stage except for some quantiles of the distribution of efficiencies. Ho, Abd Rahman94 evaluated how Islamic indices behaved during and after crisis periods. They found that most Islamic and conventional indices underperformed relative to the benchmark for the sample period 2000–2011. Islamic indices outperformed conventional indices during crises periods (Dotcom bubble and global financial crisis) whereas in the post crisis periods, there was no significant difference in the performance of both. Ashraf and Mohammad95 used monthly price dataset of 12 world and regional Islamic Equity Indices (IEIs) and their conventional counterparts for the period 2002–2012. They found that IEIs, on average, exhibited lower volatility as compared with their benchmark index during the sample period. Their finding suggested that IEIs might offer hedging opportunities during downturn of the capital markets. Hammoudeh, Mensi96 assessed whether global Shariah indices like DJIM are dependent on conventional markets for the period 1999–2013. They observed that Shariah compliance rules were not restrictive enough to make global indices different from conventional indices. In a firm level analysis, Merdad, Kabir Hassan28 found a negative relationship between Saudi Islamic firms and average stock returns that they termed as ‘negative Islamic-effect.’ Mohammad and Ashraf97 examined the determinants of return performance of Islamic equity indices for the period 2002–2013 and found that indices from developed markets outperformed the indices from emerging markets for the sample period. They also argue that Shariah screening helps the investors in avoiding companies in distress and choosing companies with growth orientation and positive momentum. Finally, majority of funds possess negative market timing ability that may be due to the conservatism of fund managers. Moreover, due to Shariah prohibitions, these funds cannot avail leverage or engage in high risk strategies. Nainggolan, How85 used a sample of 387 Islamic equity funds and 220 conventional equity funds from 32 countries for the period 1984–2010 to compare the performance of Islamic and conventional mutual funds. They chose Jensen’s alpha as their measure for fund performance. For their full sample, Islamic funds underperformed as compared to conventional funds. Moreover, they observed lower exposure of Islamic funds to market factor. They also observed that these funds invested

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in large capitalization and growth stocks. They also found that Islamic equity funds outperformed conventional funds during the crisis period. They also found a negative relationship between stock screening and portfolio performance implying that there is a cost associated with stock screening. Charfeddine, Najah98 used daily data of 6 indices for the period 2004–2011 to investigate the long term relationship between SRI, Islamic and conventional indices. They found no long term relationship between Islamic and conventional funds while such relationship existed for SRI indices and conventional indices. El-Masry, de Mingo-López99 evaluated the comparative performance of Islamic mutual funds for the period 2006–2013 for MENA region. They observed that the relative performance of Islamic and conventional funds seemed to be affected by geographical context in which the investment was made. Islamic funds performed, on average, slightly worse than conventional funds for MENA region, while they performed slightly better in case Gulf Cooperation Council (GCC) countries. They also found that Islamic funds remained more stable in times of distress. Erragragui and Revelli100 tested, for a sample of 238 US firms for the period 2007–2011, how the integration of social performance measures (represented by KLD social ratings) in Islamic portfolios affects portfolio performance. For these self-composed Islamic portfolios with varying ESG scores, they found no adverse effects on returns owing to the application of ESG screens on Shariah-compliant stocks. They observed that portfolios with good ESG records manifested substantially higher performance. However, the strategy of exclusion of firms with community and human rights controversies was associated with negative performance. Erragragui and Lagoarde-Segot38 compared the performance of conventional, SRI, and Islamic stock market indices from five developed markets (including US, UK, Japan, Canada and Australia) and three emerging markets (Brazil, India and South Africa) for the period 2008–2014. They observed no difference in performance of ethical and conventional indices that they relate to the mainstreaming process. Al-Khazali, Leduc101 tested for efficiency of Islamic indices for the period 1997–2012 for different markets of Europe, Japan, UK and US. They found conventional indices to be more efficient as compared to their Islamic counterparts. However, Islamic indices improved their efficiency in a considerable manner during the sample period. Ashraf and Khawaja56 compared the performance of market-weighted Shariahcompliant portfolios (SCPs) with conventional benchmark portfolios (CBPs) from the USA, Canada, Europe, the GCC, and Japan for the period 2003–2013. They constructed portfolios upon the basis of different Shariah screening criteria. They found negative Jensen’s alpha showing that Shariah portfolios performed below the market. Their results also revealed that SCPs were, generally, less risky than CBPs. Ashraf, Felixson102 found that Shariah screening does affect the portfolio performance regardless of the screening approach used and hence there was a sacrifice cost involved. Their objective was to examine if difference in screening methods

3.3 Empirical Evidence of Comparative Performance

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influenced the return performance of Islamic Equity Portfolios (IEPs). Their sample consisted of USA, Europe and Japan for the period 2000–2013. They divided their sample into three sub-periods i.e. pre-crisis; 2003–2007, Crisis; 2007–2009 and Post-crisis; 2009–2013) in order to investigate whether the choice of different time periods influences the factors affecting portfolio returns. The IEPs, in general, display lower returns and lower risk as compared to the market portfolio. However, the results were different during the sub periods: For the crisis period, IEPs showed higher risk-adjusted returns than the market portfolio implying that screening is beneficial for the investors during financial crisis. Abdelsalam, Duygun103 assessed the performance persistence of Islamic funds for the period 2000–2013 and observed that their performance was different from SRI funds. They found that Islamic funds were more resilient during the crisis period. They also observed that performance persistence was stronger during shorter time horizons. Boo, Ee29 performed an evaluation of Islamic equity funds belonging to a highly established and heterogeneous Islamic finance market i.e. Malaysia. Their sample period from 1996–2013 allowed to explore various performance traits of these funds during three major crises namely Asian financial crisis, Tech bubble and Global financial crisis. They found no significant evidence of superior performance of Islamic funds in comparison to conventional funds during first two crises. However, they significant outperformed conventional funds during global financial crisis. They further argue that this performance is not a result of any chance factor and is attributable to their better risk management and characteristics of portfolio holdings. Umar104 shows that, in the short run, Islamic equities are more desirable for neutral investors. Nonetheless, for the long run benefits, they need to invest in conventional stocks. Moreover, the faith-based investor incurs welfare losses by discarding conventional equities from their portfolios. Ahmed and Farooq32 examined the performance of Shariah index versus conventional index for the period 2003–2013 for MENA region. They found that the Shari’ah compliant portfolio outperformed the conventional one although both indices showed increase in vulnerability to the market after the financial crisis. The above review reveals that there is visibly a dearth of firm level analysis of performance of Shariah and SRI portfolios owing mainly to the non-availability of data of Shariah compliant as well as SRI stocks. there is a need to conduct a firm level performance analysis of SRI and Shariah portfolios by following value weighted as well as equally weighted portfolio strategy and compare them with market representative portfolio. Moreover, the pre-crisis and post crisis performance can reveal various insights in this respect.

4 Screening and Dividend Payout Behaviour It had remained a key challenge for financial economists to devise an optimal dividend policy that can, simultaneously, ensure maximization of shareholders’ wealth and utility for investors and it is due to this reason that payout policy is among widely debated issues in corporate finance105. Most of the theories related to dividend policy literature in pre Miller and Modigliani106 period argued that higher dividends were associated with high value of the firm. This view was inspired from dividend discount models that said that the value of the firm was the sum of discounted dividends. Gordon107, however, took a different stand and asserted that investors required rate of return ‘r’ will increase with the retention of earnings as well as investments. He observed that even though the retention and increase in investment would result in higher dividends in future, this increase in dividends will be offset by greater uncertainty attached to the investments. Miller and Modigliani106 identified the weaknesses of this view and introduced a more rigorous framework to analyse payout policy. In their opinion, firm’s investment policy plays key role in explaining its payout behaviour. If investment policy remains unchanged, the firms’ value will not be affected by change in mix of retained earnings and dividends. In other words, their framework deemed dividends irrelevant. Their seminal work paved the way for further research and development of theoretical models. For example, the later studies suggest that in addition to providing compensation to the investors, dividend payout policy is an important signal for investors108,109 and also addresses excess cash flow problem110,111. The payout policy is equally important from the view of faith-based investors due to various reasons. The existing literature explains that the capital structure plays an important role in selection of appropriate tools for minimizing agency conflicts. The firms can use either debt as a mechanism to address agency conflicts111,112 or governance40 to ensure effective monitoring of managers. As already stated, Shariah stocks have constraints on debt and their capital structure can be different from the conventional stocks. Moreover, the growing awareness regarding the evils of debt113 may also prompt SRIs to keep lower debt. In this backdrop, these faithbased firms cannot use debt as a disciplinary tool. Therefore, in order to substitute debt, they need to improve their governance levels in order to protect shareholders. In both the cases, dividend payout plays an important role. Another important issue that is specific for Shariah portfolios is that the investors cannot keep debt based securities in their portfolios. Ordinary investors who need regular payout from their investments to fulfil their daily needs usually keep a certain portion of debt based securities (paying periodic coupons) or dividend paying stocks for this purpose. Shariah compliant investors cannot keep debt based securities in their portfolios and dividends are their only source of payout (assuming that they do not intend to sell the stocks merely to meet household needs and instead https://doi.org/10.1515/9783110612189-004

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they wish to keep them for their preferred investment period). The regular dividend payout is thus essential for such investors as an important source of income. Moreover, as literature suggests, faith-based portfolios are expected to have a higher idiosyncratic risk (in line with the argument presented by Merton19 and Malkiel and Xu69) for which they may need risk adjusted returns, at least, at par with the ordinary investors. This possibly higher firm-specific risk should be compensated by growth in size and profitability and in case the firm is not growing, the faith-based investors may not be able to earn capital gains on their investments and a big source of investment returns will be compromised. Therefore, the retention of profits for utilizing growth opportunities is equally important for such faith-based investors. In this scenario, an optimal dividend policy (having objective of keeping balance between payout and retention to ensure long run benefit of the investors) becomes more important for these investors and the corporate governance structure of the firms has to be effective in order to materialize the desired outcomes of dividend policy. In view of these arguments, it can be observed that the dividend policy decisions for faith-based firms may be different from conventional firms owing to the difference in capital structure as well as usage of different devices for reduction of agency conflicts. Some issues require detailed explanation to build understanding of this difference.

4.1 The Disciplinary Role of Debt The contemporary knowledge states that debt can play an important role in mitigating agency risk and argues that the high debt levels force managers to act in the organizational interest due to various reasons: Firstly, the debt invokes the threat of bankruptcy in the event of non-payment of principle and interest. The managers seek continuity and stability of operations in order to keep on enjoying salaries and perks. The bankruptcy would lead to the loss of their jobs and an uncertain future. Therefore, Grossman and Hart112 portray debt as the strongest bonding device available to the shareholders to regulate managers’ behaviour. They indicate an ‘incentive problem’ in the fragmented organizations and posit that managers apparently have no incentive (except their personal objectives like empire building or increasing personal wealth) to work for maximization of shareholders’ wealth. The shareholders can overcome this problem by offering performance related incentives to the managers or incorporating such clauses in the organization charter that can facilitate takeovers. These bonding mechanisms would constrain managers to work towards value maximization. However, another more powerful channel that can discipline managers more effectively is the threat of bankruptcy that can deprive managers of their jobs and benefits. Therefore, the debt emerges as a very powerful device to discipline managers’ conduct. The issuance of

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debt also increases the market value of the firm because investors know that the managers of levered firms are constrained and hence they put a high valuation on such firm. Managers also have incentives to increase the market value of the firm as their pay raises are mostly attached to the higher market value and the higher market value of firm makes it lesser attractive target for takeover. Besides, the higher market value can enable managers to issue new debt and equity. The higher amount of capital, in turn, would expand their empire and increase their perquisites. The managers, therefore, would put their best efforts to maximize profits in order to increase market value, avoid bankruptcy and to save their perquisites. Debt issuance is a pre-commitment, unlike dividends, and brings managers incentives in line with shareholders. More formally, debt aligns managers’ incentives with the shareholders’ incentives and constrains them to work for profit maximization. Secondly, the organizations can use debt to maintain growing dividends and spend free cash flow on debt servicing. To explain this phenomenon, Jensen111 argues that, in a bid to expand their empire and resources under their control, managers prefer to initiate financing projects instead of distributing excess cash to the shareholders. This strategy may not be in the best interest of shareholders especially when these projects are expected to yield returns lower than cost of capital. As a result, there arises a need to regulate their self-motivated behaviour. He identifies that forces like product market competition, internal control and regulatory oversight can discipline managers but their effectiveness, over the years, has become questionable. He observes that payment of regular dividends instead of wasting resources on inefficient ventures is the best device of addressing agency conflict. These dividends are required to be kept at the same level or increased because the dividend cuts are followed by adverse response from capital markets that may lead to significant reductions in share prices. It is, nonetheless, not possible to distribute these growing dividends solely from the earnings as markets are volatile and organizations cannot guarantee smooth earnings. In this scenario, debt enters into the picture and managers can fulfil the promise of paying ‘permanent’ dividends by relying on debt instead of putting their bet on future cash flows for the payment of dividends. Therefore, debt can be utilized as an effective tool for regulating managers’ behaviour as it reduces the level of free cash flow available to the self- motivated managers. Additionally, the high amount of debt makes organization more efficient as, unlike dividends, the distribution to lenders in shape of interest and principal is mandatory and the inability to service debt may cause bankruptcy and loss of empire for the managers. This control function of debt is more meaningful for the large and seasoned companies having high book-to-market ratios as these firms generate high amount of free cash flow and they are more exposed to the agency risk. It is easier for these firms to start ‘below the cost of capital’ projects and regular dividends through debt creation discipline the managerial conduct at these firms. The growing firms with no free cash flow, on the other hand, exhibit lesser agency problem. These firms approach financial markets to fulfil their capital requirements for expansion projects. The capital providers assess the management and

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proposed projects extensively before extending capital and provide funding only when they consider the projects feasible for investment. Hence, due to reduced information asymmetry between providers and users of capital and strong monitoring by capital markets, there is lesser probability that these firms start wasteful projects. In line with these arguments, Stulz114 asserts that, owing to information asymmetry, managers are better aware of the outcomes of projects as compared to the shareholders. It is at their discretion to approve or reject any project upon the basis of superior information they have. When they exercise this discretion, agency costs arise mainly due to two reasons: there can either be overinvestment cost when managers spend too much or, in some circumstances, there may be an underinvestment cost when managers are unable to start a useful project due to the lack of credibility. In this scenario, maintaining smooth dividends by issuing debt can help in addressing overinvestment problem because management would be bound to use free cash flow for the repayment of debt instead of spending in empire building projects. However, this practice would result in worsening underinvestment problem because the firm would be unable to invest in positive NPV projects due to shortage of available resources. Similarly, the underinvestment problem can be managed by issuing equity as it would increase the investable funds but this issue would exacerbate overinvestment problem. Therefore, the debt and equity offerings, when taken into the account individually, decrease one source of agency cost and increase the other. This situation points to a unique underinvestment/overinvestment problem and the solution can be found in the capital structure of the firm. The firms with high growth prospects would be required to maintain low debt and invest free cash flows in expansion projects while seasoned firms should opt to issue higher debt and use free cash flows to service debt. Hence, the financing policy matters for mitigation of agency risk. Moving further, Zwiebel115 suggests that instead of a stagnant financing mix, a dynamic capital structure would be more effective in curbing manager-shareholder conflict. In this structure, managers are not fully entrenched and voluntarily choose debt to restrict their empire building activities. This capital structure would change periodically in line with the needs of organization and allow these partially entrenched managers to achieve a balance between empire building desires and organizational efficiency by choosing debt and maintaining smooth dividends. This structure does not require any discipliner in shape of creditors, market forces or raiders to meet its objectives.

4.2 Governance as Substitute of Debt for Minimizing Agency Conflict The above discussion envisages that a higher debt level ensures lower agency cost. The recent studies extend this argument and explore the role of debt in firms with

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good governance to reduce agency conflict. It has been observed that the firms with good corporate governance do not need to build high debt levels to minimize agency cost. For example, Arping and Sautner39 observe that corporate governance reforms minimize agency conflicts between managers and shareholders by improving the monitoring and controlling mechanism. In the aftermath of these reforms, the companies reduce their debt levels because the value of debt as a disciplining device diminishes due to better governance. Also, Jiraporn, Kim40 argue that the managers are motivated to maintain suboptimal debt levels that are inadequate to maximize shareholders’ wealth and only enhances the private benefits of managers. Good governance ensures that managers maintain optimal debt levels. Their empirical findings reveal that the firms manifesting weaker governance exhibit higher debt levels and there is negative significant relationship between governance quality and leverage. In the similar manner, Hong and Kacperczyk44 argue that SRI firms are better governed as they refrain from socially unacceptable business activities like alcohol, tobacco, adult entertainment and firearms. The companies that deal in these businesses lack public acceptance and owing to this reason, the institutional investors do not invest in these companies and therefore, they lose an important monitoring tool i.e. institutional management. Furthermore, the analysts also offer minimum coverage for these companies resulting in lower visibility for these ‘sin’ stocks. On the contrary, the SRI firms are targeted by institutional investors due to their good reputation. These firms also get adequate coverage from the analysts. These two channels provide better monitoring and hence, SRI firms emerge as better governed equities. It is therefore apparent, in line with these arguments, that faith-based firms need to exercise corporate governance in order to discipline managers and they can use dividends to perform this function.

4.3 Governance and Dividend Policy The existing literature asserts that an effective payout framework is the key to address agency conflict. As Jensen111 posits, managers have incentives to adopt policies that can cause the firms under their control to grow beyond their optimal size as this expansion would result in an increase in managers’ powers, resources under control and compensation. Therefore, self-motivated managers are inclined to use free cash flows for risky expansion projects. On the contrary, the shareholders prefer using free cash flows to pay regular dividends to discipline these managers. Corporate governance is instrumental in designing a dividend policy that can address this agency conflict116. There is, nevertheless, a continuing debate on the payout behaviour that the good governance practices should encourage in order to address agency issues. If governance

4.3 Governance and Dividend Policy

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and payout are deemed as ‘substitutes’, good governance should discourage payout. For example, John and Knyazeva45 noted that firms with better governance had tendency to avoid the costs attached to dividends in order to pursue a more efficient investment policy. They studied this relationship in the event of pre-commitment of dividends by management for a sample of 9,270 firm-year observations for US market for the period 1993–2003. They used two governance indicators namely internal governance (index of 12 governance related characteristics) and external governance (g-index comprising of 24 anti-takeover provisions developed by Gompers, Ishii117) and found that likelihood of dividend payout reduced with good governance. They also found that higher cash flow increased the propensity of payout. Conversely, weak governance is associated principally with dividend pre-commitment (instead of repurchases) as a part of total payout. The good governance firms prefer using excess cash for investment in growth projects or repurchases. In general, dividends were found to be more effective in dealing with agency problem, in the presence of free cash flow, as compared to the other forms of payout owing to their pre commitment attributes. In a relevant study, John, Knyazeva46 observed that firms with weak governance had higher payout ratio and these firms used a combination of dividends and debt rather than debt alone for pre-commitment with external claim holders. They also found that dividends were more effective in addressing agency conflicts as compared to repurchases and even implicit dividend commitments were deemed credible by investors. The dividend cuts by weak governance firm are followed by adverse market reaction. Officer47 supports the substitution hypothesis for dividend initiation as well and showed that managers of a firm with poor investment opportunities (low Q) and abundant resources (high cash flow) are likely to waste available cash and this visible agency problem can be reduced through higher dividends. He used outsider dominated board, takeover defence and institutional ownership as proxies for governance. Caton, Goh118 had similar findings for a large sample of 53,523 US firms listed on different exchanges for the period 1991–2011 as they found that their governance indicator i.e. anti-takeover law index worked as substitute for dividend payout and complement for share repurchase. They asserted that companies having good governance had tendency to manifest higher adjusted operating performance as well as abnormal stock returns (in comparison to weakly governed companies) in first three years after completing a share repurchase program announcement. Finally, Chang, Kang119 found the similar results for a large sample of 31,140 US firms for the period 1995–2009. They used institutional majority as a proxy for corporate governance and demonstrated that higher presence of institutional investors in the firm discourages payout. The opposite view considers governance and dividends as ‘complements’ and maintains that good governance reinforces dividend payout. La Porta, Lopez-deSilanes48 dubbed dividends as an outcome of effective legal protection of shareholders

28

4 Screening and Dividend Payout Behaviour

that gave minority shareholders an opportunity to extract dividends from corporate insiders. Their sample included 4,103 firms located in 33 countries and they manifested that the countries where shareholders had high protection rights, firms had paid higher dividends. Conversely, the poorly protected shareholders may accept any dividends they can get irrespective of investment opportunities that can be presumed as the agency cost arising out of weak legal protection. Mitton49 tested for governance-dividend connection for a sample of 365 firms from 19 countries and showed that firms with stronger corporate governance had higher dividend payouts. They also note that in common law countries, governance complemented payout whereas in civil law countries, governance substituted dividends. Their control variable also had expected signs i.e. profitability and age had a positive sign and growth had negative sign implying that holding all else constant, firms with large size and profits but poor growth opportunities tend to pay higher dividends. They used ratings developed by Credit Lyonnais Securities Asia as governance proxy. Hu and Kumar50 looked at this relationship from the point of view of managerial entrenchment and observed that in case of weak governance, managers were disciplined to pay more dividends. They studied dividend payout as well as total payout behaviour of a sample of 2,081 US firms for the period 1992–2000. Their explanatory variables were related to managerial compensation as well as governance indicators. They found that in general, the higher proportion of fixed emoluments in CEOs salary resulted in higher payout. Nonetheless, the higher stock options and other variable component of their compensation package decreased the payout. The governance related variables including large shareholders and board independence increased the payout ratio and thus dividends complemented the governance. The firms with longer age, high tangible assets and lower investment opportunities paid higher dividends. Jo and Pan120 investigated the relationship between managerial entrenchment and payout and found that there were higher odds of entrenched managers paying dividends. Their sample comprised of large US firms for the period 1990–2003 and they used antitakeover provisions as proxy for entrenchment. Likewise, Petrasek121 exhibited that when the firms from countries having poor shareholder protection cross listed in US exchanges, they increased their payouts by about 9% of earnings. However, if external shareholder protection was already strong in the country of incorporation, no significant change in payout policy was observed. They concluded that transparency and enhanced shareholder protection was instrumental in higher corporate payout. Their sample comprised of 755 foreign firms that cross-listed common shares on overseas exchanges from 1987–2006. Michaely and Roberts51 studied the pattern of dividends of public and private firms for the period 1993–2002 and found that public firms had smoother pattern of dividend payments as compared to private firms due to better governance mechanism of public firms and presence of public capital markets that regulate behaviours

4.4 Governance, Dividends and Idiosyncratic Risk

29

of the listed firms. In a recent study, Liljeblom and Maury122 found the same results for Russian market for the period 1998–2003.

4.4 Governance, Dividends and Idiosyncratic Risk The interplay of idiosyncratic risk with governance and its impact on agency problem is extensively explored in contemporary literature to unravel disappearing dividend puzzle and as Hoberg and Prabhala52 explains that risk explains 40% of this puzzle. They analysed the dividend decisions of US firms from 1963–2004 and found that higher idiosyncratic risk reduces the likelihood of payout. In effect, high idiosyncratic risk leads to underinvestment problem owing to managers’ risk aversion54. The good governance (in shape of strong monitoring by institutional investors), in this scenario, can boost investments or managers may be tempted to enhance investments if they are offered stock options53. Kuo, Philip123 investigated the role of liquidity, risk and catering in explaining dividend policy for a sample of 18 countries (mostly developed markets) for the period from 1989–2011. They found that risk played a significant role in designing of dividend policy. In their final analysis, the propensity to pay dividends cannot be explained without discussing risk. The above review sheds some important insights. Firstly, dividends are an important source of payout and mitigate agency conflicts. Secondly, the firms can use debt to maintain smooth dividends and use free cash flows to service debt instead of spending in wasteful projects. Thirdly, the firms with good governance use low levels of debt and governance substitute debt as a controlling device for regulating managerial behaviour. Fourthly, there is ample evidence available that good governance affects dividend payout but there is disagreement on the nature of this relationship. One view suggests that the good governance substitute payout i.e. in the presence of good managers and/or effective monitoring, the earnings are retained and invested in expansion projects. The opposite view however claims that governance complements payout as in the countries with higher protection for shareholder rights, dividend payout is higher than the countries where such laws are not in place or weak. Moreover, at firm level, entrenched managers pay higher dividends instead of initiating unnecessary or risky projects aimed at increasing personal wealth. Fifthly, there is inverse relationship between idiosyncratic risk and payout. When idiosyncratic risk is high (low), there will be lower (higher) payout. Finally, the relationship between governance and payout can be further explained by the fact that when the idiosyncratic risk is high (low), good governance serves as substitute (complement) and addresses the underinvestment issue (overinvestment), and good governance firms retain (release) cash.

5 The Model We have, so far, deliberated on three important considerations for an investor while deciding on his investment strategy namely idiosyncratic or diversifiable risk, riskadjusted performance and dividend payout. Although a rich collection of studies is available on performance evaluation, there is still a gap on the studies related to idiosyncratic risk, risk-adjusted performance or payout mechanism of faith-based portfolios, using firm level data. At present, a faith-based investor is unaware of the idiosyncratic risk, firm level performance and payout behaviour of such portfolios. In this scenario, it is not viable to design an effective strategy to invest in such stocks. We therefore undertake a comparative study of these faith-based stocks for the US market as our general objective. There are several reasons for choosing US data for this research. For better empirical validity, we need a reasonably large data set to test for the stated research objectives. The data availability is prime reason because vendors like Dow Jones are screening stocks for Shariah compliance and SRI criteria for US market for a considerable period of time. Consequently, it serves as a valid setting for testing our hypotheses regarding faith-based portfolios. We introduce three portfolios of stocks for our research where the first portfolio comprises of Shariah compliant stocks, the second portfolio is comprised of Socially Responsible Investments (SRI) stocks and the third portfolio i.e. market proxy portfolio is composed of market representative stocks. In order to design Shariah and Market proxy portfolios, we have utilized the constituent lists of Dow Jones US Index and Dow Jones Islamic Markets Index-US. This data is not publicly available and we purchased it directly from Dow Jones through the research grant extended by BNP Paribas – INCEIF Centre for Islamic Asset and Wealth Management, Malaysia. We are thankful to them for this gesture. Our purpose is to compare the (possible) variance in idiosyncratic risk, performance and the relationship of governance, dividends payout pattern among the investment classes. We intend to compare the performance of the screened portfolios with the performance of the market portfolio. We are assuming here that market (proxy) portfolio is the investment universe of a neutral investor and setting market portfolio as benchmark would allow assessment on whether value driven investors are at disadvantage as compared to neutral investors. Moreover, this approach would allow the assessment of relative performance of different portfolios without involving any costs of transaction, in line with Ashraf, Felixson102 assuming that the investors follow passive strategies and track a certain index to formulate their portfolios. We have chosen the sample period 2006–2015 as it allows us to perform estimations for a reasonably long period of time. However, this choice has a major limitation as it may lead us to sample selection bias due to possibility of a structural break in the sample period during crisis period. We have made estimations for the sub periods to evaluate the risk-return trade-off for crisis and non-crisis period in order to address this issue. https://doi.org/10.1515/9783110612189-005

5 The Model

31

Our first objective is related to the under-diversification myth and we intend to estimate idiosyncratic risk for both of these portfolios and the market portfolio. The purpose is to ascertain if these screened portfolios have higher or lower idiosyncratic risk as compared to the market portfolio. The idiosyncratic risk for the faithbased portfolios is expected to be different from the market owing to certain reasons. First, there is possible under-diversification due to portfolio screening that may add to their idiosyncratic risk. Nevertheless, the constituent stocks belong to the sectors that are generally perceived to be morally or socially of good reputation and investors in general attach no negative feelings to them. As a result, they should be in a better position to accumulate capital from the market as compared to ‘sin’ stocks and their idiosyncratic risk may be lower. Furthermore, these stocks do not use debt as frequently as other stocks (even if they use, it is capped at certain minimum level) and therefore, they should be more stable and better capable of combating the adverse business cycles due to lesser reliance on leverage. This finding will be crucial in analysing whether these portfolios face higher volatility and bear the brunt of under-diversification or they have no disadvantage of restricted investment horizon. An extension of this objective is related to the ranking of the sectors within the available investment universe according to idiosyncratic volatilities in line with Campbell, Lettau124. This ranking in turn can be helpful in selecting stocks for portfolios. The first research question is: Is there any difference in magnitude of idiosyncratic risk for screened based (both the Shariah and socially responsible) portfolios and market portfolio? The second objective is linked to the assessment of risk-adjusted performance of both these portfolios vis-a-vis market portfolio. The intention is to see if these portfolios are capable of providing better returns than the market. This question is important as faith-based portfolios are not only followed by value driven investors but also profit seekers investing in these portfolios78. It is probable that the restricted investment universe is still capable of providing diversification benefits to these portfolios. In that scenario, these portfolios would not be at any disadvantage and would be able to provide better or at least similar returns to the market portfolio. The performance will be measured using Jensen alpha with three different models namely CAPM one factor model (CAPM), Fama and French125 three factor model (FF-3) and Carhart126 four factor model (CRHT-4) to estimate the expected returns. These three models use different factors to explain expected stock returns and there is ample evidence in existing literature that stock performance cannot be explained solely through ‘Equity Risk Premium’ but Size, Market Capitalization and Momentum also play an important role in defining stock returns. Our intention of using these models simultaneously is to observe how these factors affect the portfolio returns. This approach is also expected to give more robust results and it would be interesting to observe if the calculated returns converge or there are differences. In case the results are different among these three models, we can also identify factors that contribute to the difference in estimates. We will also test if there is a significant difference in

32

5 The Model

alphas of both the screened portfolios. The second research question is as follows: Do the Shariah and SRI portfolios perform (as measured by Jensen’s alpha) better than market portfolio? Is there significant difference between faith-based and Market portfolios? The final objective aims to better address agency issue for faith-based investors and their linkage to firm specific risk, dividend policy and grade of governance mechanism (weak or strong) for screened based stocks. The existing literature holds divergent views regarding the relationship between governance and payout policy. Some studies argue that they are substitutes i.e. good governance discourage payout whereas other studies contend that they are complements i.e. good governance encourages payout. Our motivation stems from the expected higher governance levels of faith-based firms that could affect their dividend payout decision. We are unaware whether governance and dividends are substitutes or complements for faith-based stocks and investigate if the level of idiosyncratic risk has any significant impact on a firm’s propensity to pay dividends. An important question to be answered is whether idiosyncratic risk affects the relationship between governance and dividend payout of the firm. We intend to ascertain the answers while controlling for firm size, profitability, free cash flow and growth potential. Thus, we can formulate a third research question as: Is there any link between the governance and dividend payout preference of Shariah and SRI portfolios? Is there any role of idiosyncratic risk in defining this relationship? The broad objective of this study is to appreciate various aspects of faith-based portfolio management. In order to make the findings more robust and analysis more meaningful we have performed a firm level analysis of three portfolios i.e. Market proxy portfolio, SRI portfolio and Shariah Portfolio. As the existing literature suggests, owing to ethical and religious constraints, the faith-based portfolios may exhibit idiosyncratic risk. In order to know if this is the case, we have estimated idiosyncratic risk at the portfolio level. In addition to this, we have estimated idiosyncratic risk at industry level as well to understand the unsystematic risk for various sectors. Moving further, in order to see the risk adjusted return performance for the portfolios and their sensitivity towards market and other risks, we estimate portfolio alphas and factor sensitivities. The estimations of idiosyncratic risk and alphas are made using CAPM, Fama and French125 Model and Carhart126 Model for a comprehensive analysis. Finally, the linkage of dividend payout, governance and idiosyncratic risk is studied using Fama and Macbeth127 style Logistic regressions and various controls for size, free cash flow, agency conflict etc. are included in line with existing literature. Our motivation is to enlighten an investor about the unsystematic risk, the risk return trade off and dividend payment behaviour of faith-based portfolios. We seek to identify whether an investment made in consideration of the ethical and religious beliefs lead to reduction in value or the investors bear no cost of their beliefs. The empirical framework strives to provide with the required answers.

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33

5.1 Data and Methodology The sample includes representative Shariah, SRI and market proxy portfolios for United States (US) market from 2006–2015. The Shariah portfolio comprises of constituent stocks of ‘Dow Jones Islamic Market Index US (DJIM-US)’ and market portfolio is represented by ‘Dow Jones United States Index (DJUSI)’. The data comprising of lists of constituent stocks of both the indices is purchased from Dow Jones S&P Indices as this information is not publicly available and provided by BNP Paribas – INCEIF Centre for Islamic Asset and Wealth Management, Malaysia. The motivation behind this selection is that both of them are among oldest such indices and Dow Jones is among reliable vendors. Another advantage is frequent rebalancing by the service provider as the DJIMI-US is rebalanced quarterly whereas DJUSI is rebalanced once a year. Dow Jones finalizes the Shariah screening by applying various qualitative and quantitative criteria is done by Dow Jones is subsequently validated by an independent Shariah supervisory board comprising of eminent scholars to ensure consistency with Shariah law (The details of these Shariah compliance screens are made available in the appendix and the complete screening methodology can be accessed at https://us.spindices.com/index-family/Shariah/all.). These historical lists are vital to our analysis because the firms selected in one period may not be present in the previous or subsequent periods. For one calendar year, only those firms are included in Shariah portfolio that had passed the Shariah screening for all the four quarters of the said year. In order to create our SRI portfolio, we have applied negative screening on DJUSI excluding the stocks of sectors like adult entertainment, alcohol, tobacco, firearms, nuclear weapons, gambling and firearms as proposed by Renneboog, Ter Horst7 who mention that a considerable majority of SRI mutual funds in US applies negative screening only. We did not choose Dow Jones Sustainability Index as our proxy for SRI portfolio owing to the reason that the number of constituent stocks is very low and hence not suitable for comparison with the other two portfolios. In order to select final sample, the nature of estimation technique and data availability had been the major concerns. We list a year-wise summary of constituent stocks data that was received from Dow Jones of the sample portfolios (see Table 5.1). The Dow Jones US index is rebalanced on annual basis and since SRI portfolio is also constructed by applying negative screening criteria to DJUS index, it should also be rebalanced annually. We have therefore used annual lists for our market and SRI portfolios. DJIMUS (our proxy for Shariah portfolio) is rebalanced on quarterly basis and constituents are finalized after applying Shariah screening. We received quarterly data from Dow Jones for the period 2006–2015 and the year-wise number of constituents is reported in columns 4 of Table 5.1. We applied further screening for our final sample and included only those stocks for a specific year that passed Shariah screening for all the four quarters of the said year. As a result,

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5 The Model

Table 5.1: Summary of Constituent Stocks of Sample Portfolios. Year ()          

US

SRI

Shariah (I)

Shariah (F)

() , , , , , , , , , ,

() , , , , , , , , , ,

()          

()          

the final number of stocks is reduced as compared to the original list of constituents as can be observed in column 5. Our motivation in doing so was to make the comparison meaningful because the other two sample portfolios (market and SRI) are rebalanced annually. Another concern was data availability for various variables to be used for empirical estimations. Finally, we contend that by including only those stocks in our sample portfolio that had remained Shariah compliant throughout the year, we provide a Shariah compliant investor with the flexibility to hold the portfolio for a reasonably long period of time. For example, if such investor rebalances the portfolio in every quarter, there may be instances where he would be constrained to offload certain holdings owing to the failure of those stocks in passing Shariah screens for the said period. This strategy will not be preferable for the long horizon investors. Furthermore, even some short horizon investors would not be willing to divest their holdings abruptly. Consequently, the selection of one year period is also in line with portfolio management principles. For the estimation of idiosyncratic risk, Jensen’s Alpha and factor sensitivities, we used daily observations due to its better explaining power of market related information128. For our dividend policy related estimations using Fama and Macbeth127 style logit, we used annual observations and the final sample includes all the stocks within the available universe for which the accounting and governance related information was available. Table 5.2 shows the details of final sample. We retrieved the daily values for holding period returns, market capitalization and stock prices from Centre for Research in Security Prices (CRSP) database. The factor loadings (daily frequency) on market risk, small-minus-big, high-minus-low and momentum are sourced from Wharton research data services (WRDS). The financial information including figures from financial statements is obtained from COMPUSTAT-Capital IQ. The governance indicators are collected from MSCI GMI Ratings available on WRDS.

5.1 Data and Methodology

35

Table 5.2: Final Sample for Estimations. Panel : Estimation of Risk and Performance Measures

Firm-Day Observations

US

SRI

Shariah

,,

,,

,,

US

SRI

Shariah

,

,

,

Panel : Propensity to Pay Dividends, Governance and Risk

Firm-year Observations

In order to understand the risk profile of the sample portfolios and to assess the risk adjusted performance of the portfolios, we have used multifactor models. These models define the excess return of a portfolio as a function of multiple factors. The first in line is Capital Asset Pricing Model (CAPM) developed by Sharpe129 Lintner130. It states that excess return for investor is a function of excess market return and in this model the risk sensitivity represents the systematic risk for the portfolio as shown equation 5.1.   (5:1) Rt − Rf,t = αi + β1 Rm,t − Rf,t + εt Fama and French125 extend CAPM and argue that excess return cannot be explained only with market return. There is probability that small capitalization stocks offer higher return than large capitalization stocks. Similarly, the value stocks may outperform growth stocks. They added these two factors into their model as reflected by equation 5.2.   (5:2) Rt − Rf,t = αi + β1 Rm,t − Rf,t + β2 SMBt + β3 HMLt + εt Finally, Carhart126 argues that there is a tendency in investors to long high performing stocks (winners) and short low performing stocks (losers) and they called this momentum factor. Their model is represented by equation 5.3.   (5:3) Rt − Rf,t = αi + β1 Rm,t − Rf,t + β2 SMBt + β3 HMLt + β4 WMLt + εt The detailed definitions of the variables used in these three models are summarized in Table 5.3. Our main results include the estimations made by using Carhart126 model owing to the reason that this model explains excess returns by taking into consideration more factors as compared to CAPM and Fama and French125 model. However, it can be argued that adding additional factors may not be a proof of better explanatory power of a model. Moreover, there is no final evidence in the existing literature on the relative strength of these three models. We have therefore made estimations using

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5 The Model

Table 5.3: Definitions of Variables for Factor Models. Variable

Description

Rt Rf,t Rm,t Rt − Rf,t

Daily holding period returns Risk free rate ( days T-Bill rate) The return offered by market portfolio Excess return i.e. Holding period return for the investors in excess of risk free rate Market Premium i.e. the return on a market value-weighted equity index in Rm,t − Rf,t excess of one-month T-bill rate. This factor is included to account for the premium offered by market portfolio in excess of risk free rate. SMB (small minus Size Premium i.e. the average return on  small market capitalization big) portfolios minus  large market capitalization portfolios. This factor is included to account for the premium of being a small capitalization stock. HML (high minus Value vs. Growth i.e. the average return on two high book-to-market portfolios low) minus the average return on two low book-to-market portfolios. The high (low) book-to-market represents a value (growth) bias. This factor is added to account for a value return premium. Momentum Prior year effect on current prices i.e. the average return on the two high prior return portfolios minus the average return on the two low prior return portfolios. This factor reflects the premium earned by buying last year’s winner stocks.

CAPM and Fama and French model as well and our intention in doing was to observe if there was any variation in the estimations owing to the difference in predictors. The use of factor models carriers various benefits as well as limitations131. They offer a detailed breakdown of risk and therefore, the analysis of risk exposure using these models is more comprehensive. Additionally, these models use economic logic and they are not limited by purely historical analysis. Hence, they adapt to reflect changing asset characteristics due to change in the economy and individual firms. Furthermore, these models are robust investment tools that have the capacity to withstand outliers. Most importantly, factor models isolate the impact of individual factors and offer segmented analysis to facilitate better informed investment decisions. However, factor models also have some limitations. Firstly, they are capable of predicting a large proportion of risk but do not provide complete explanation. Therefore, their predictive power may be compromised. Also, these models are unable to offer any stock recommendations and investors need to formulate their own strategies. The recent studies like Nofsinger and Varma90, Lean, Ang25, Mohammad and Ashraf 97, Nainggolan, How85 and Ashraf, Felixson102 have used this approach. We have used two portfolio formation strategies to estimate risk-return profile of the portfolios. The first methodology, known as Equally Weighted Portfolio Strategy, gives equal weightage to every stock irrespective of its market capitalization.

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37

This approach results in higher portfolio owing to the reason that as it gives higher representation to small cap stocks that are considered riskier67. The second methodology is called Capitalization Weighted Strategy and it gives representation to stocks with respect to their market size. These portfolios are expected to be lesser volatile due to their higher representation of more seasoned companies. Our rationale behind this approach is to observe the risk return trade off of our portfolios of interest under different portfolio management strategies. In order to address the issue of the possible presence of a structural break in the sample due to global financial crisis, we conducted the out of sample tests by performing portfolio level estimations across three different time periods as reported in Table 5.4. The pre-crisis period ranges from 2006–2007, crisis from 2008–2009 and post crisis period is from 2010–2015. This classification is influenced by US Business Cycle Expansions and Contractions information provided by National bureau of economic research (NBER) which states December 2007 and June 2009 as turning point dates (http://www.nber.org/cycles. html). We have extended crisis period for our sample for further six months owing to the reason that market sentiment takes a bit longer to recognize changes in investment climate. Table 5.4: Description of Sample Period and Out-of-Sample Periods for risk return tradeoff. Sample Period –

Pre-Crisis

Crisis

Post Crisis

–

–

–

The ‘difference of means’ tests are performed using following t-statistic as proposed by Dixon and Massey132: t= 

x− − y− 1=2  ðnx − 1Þs2x + ðny − 1Þs2y 1 nx + ny − 2

nx

+

1 ny

1=2

(5:4)

with a degree of freedom equal to nx + ny − 2. The difference of regression coefficients tests for factor models are performed by using Wald test in line with Clogg, Petkova133. For any two regression coefficients βy and βx , the Chi-Square test statistics would be χ2 = 

βy − βx σ2y βy + σ2x βx

1=2

To estimate idiosyncratic risk at the stock level, various studies like Ang, Hodrick20 and Hoberg and Prabhala52 use factor models. The same approach is applied here to estimate the unsystematic risk at portfolio level. The daily excess stock returns of

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5 The Model

constituent of each portfolio are regressed on the Carhart126 four factors by using Ordinary Least Square (OLS) method. Idiosyncratic risk is the standard deviation of residuals from this regression. We have used both the raw returns as well as market capitalization weighted returns for portfolio level estimation. The risk is measured across three different time periods to see if there is any variation in idiosyncratic risk with respect to global financial crisis. The estimations at portfolio level are also made using CAPM as well as Fama-French models for the purpose of robustness of results. The estimation of idiosyncratic risk is also made at firm level and the similar procedure is adopted. Daily excess stock returns for one calendar year for each firm in the portfolio are regressed on Carhart126 four factors. The standard deviation of residuals from each regression is then calculated. This standard deviation is the idiosyncratic risk for the respective firm for the said year. This firm level estimation is made using only raw returns due to the reason that the regressions of valueweighted firm level returns on four factors yielded zero idiosyncratic risk up to five decimal points and it was redundant to report them. The averages of firm level idiosyncratic risk are reported to highlight the risk at portfolio level as well as industry level. The industry classification is in line with ‘Standard Industrial Classification (SIC)’ codes used by US government agencies. We have also assessed if the mean idiosyncratic risk is significantly different among portfolios at consolidated as well as industry levels. We have used Jensen’s alpha to compare the risk adjusted performance of sample portfolios. As Jensen134 argues, it is capable of measuring performance across different risk levels and various time periods irrespective of economic conditions and market environment. Alpha is intercept term of regression of daily excess returns of constituent stocks on Carhart126 four factors. Our out-of-samples include the estimations across three different time periods as mentioned in Table 5.4. The alphas are also calculated using CAPM and Fama and French125 model using daily returns for the purpose of gaining further insights. The values of Jensen’s alpha are annualized for better interpretation of results. We have also reported slope coefficients estimated through these models in order to analyse the impact of factor sensitivities on the excess returns. The difference of coefficients across factor models are tested using Wald test as mentioned earlier. To estimate propensity to pay dividends of the firms belonging to market, SRI and Shariah portfolios with respect to the governance, idiosyncratic risk and agency problem, we have used Fama and MacBeth127 style logistic regressions whereby one cross-sectional model is estimated per year from 2006–2015 with Newey-West (two lags) adjusted standard errors. We deem it proper to furnish theoretical background of logistic regression method and its linkage with our research objective before moving to the further details. The following discussion has benefitted from Liu135.

5.1 Data and Methodology

39

Our intention is to predict the propensity of a firm to pay dividends which is a binary variable having two outcomes: ( 1 if firm is a dividend payer Payer Indicator = 0 if firm is not a dividend payer This variable predicts the probability that a firm pays dividends. As the dependent variable has only two values, it is not appropriate to use multiple linear regressions to estimate such binary outcome variable because it violates three key assumptions of multiple regressions: 1. Normality: A binary dependent variable violates the assumption of normality as, instead of normal distribution, dichotomous response variable has a Bernoulli distribution. 2. Homoscedasticity: The homoscedasticity assumption suggests that the error variances of the dependent variable are same across each value of the predictors. As binary dependent variables are dichotomous, this assumption is violated. 3. Linearity: Multiple linear regressions assume the linear relationship between response variable and predictors and predicted values fall on the regression line. On the other hand, the relationship of a binary dependent variable and predictors is nonlinear. We need to reiterate here that the purpose of using binary dependent variable is to predict probabilities and therefore the predicted value of such variables will be strictly between ‘0’ and ‘1’. As a result, when the multiple regressions will be used to estimate binary data, the predicted value will not always fall between ‘0’ and ‘1’ as it theoretically should. Some values may be negative and some may be greater than ‘1’. These results are nonsensical owing to the reason that they violate the basic probability theory. Therefore, to estimate the probability of success, a logistic transformation logit (π) is used and such model is termed as logistic regression model. This model, known as multiple logistic model, can be expressed as logit ðπÞ = α + βi Xit

(5:5)

where π is the probability that outcome variable is equal to ‘1’, α is the intercept term and βi represent logit regression coefficients and Xit are dependent variables. We do not estimate dependent variable directly and instead estimate logistic transformation of the probability of success. In equation 5.5, the left hand side represents log (odds) where odds are the ratio of the probability of success to the probability of failure. As logistic model, can be expressed as logit ðπÞ = lnðOddsÞ

(5:6)

40

5 The Model

And we also know that lnðOddsÞ =

π 1−π

(5:7)

Therefore, substituting values in equation 5.5 gives us ln

π = α + βi Xit 1−π

(5:8)

When the probability π varies from ‘0’ to ‘1’, the log odds or logit will vary from negative infinity to positive infinity. More formally, after taking exponentials on both sides, our logistic model to calculate the probability (π) of dividend payment can be written as Probability ðPayer Indicatori = 1jxi Þ =

1 1 + exp ð− βXi Þ

(5:9)

Where Xi represents predictors and β is a vector of coefficients. Moving forward, we introduce Fama Macbeth approach for further clarity of the empirical models. Fama and MacBeth127 method is used for panel data samples and a three step process is followed that can be summarized as under: 1. One cross section regression is run for each firm in the sample and the excess returns are regressed on the risk factors to determine that firm’s beta. For example, if there are ‘n’ firms in the sample, there will be ‘n’ cross sectional regressions in first step. 2. One regression is run for every time period where excess returns are regressed on the firm betas estimated in the first step. If there are ‘t’ time periods, there will be ‘t’ number of regressions. 3. The final regression coefficients will be calculated by taking the arithmetic mean of the regressions coefficients estimated in step 2. Instead of the above procedure, we have used Fama Macbeth method with a modification, in line with existing dividend policy literature. Fama and French136, Hoberg and Prabhala52 and recently Bhattacharya, Li137 estimated propensity to pay dividend by using only stage 2 and 3 of Fama and Macbeth127 method. For a panel dataset of comprising of ‘n’ number of firms and ‘t’ number of years, one cross sectional logistic regression is run for every year in the sample. The final regression coefficients are obtained by taking average of coefficients estimated through each regression. We have preferred the Fama Macbeth style logistic regressions for the following reasons: 1. Our panel is highly unbalanced due to frequent stock screening. It becomes very difficult to estimate logistic regressions for such models due to their failure to converge138.

5.1 Data and Methodology

2.

3.

41

This method is capable of addressing bias in results owing to firm clustering or time clustering. Petersen139 argues that, in general, there can be two common forms of dependence in finance applications. The first case is when residuals of a regression are cross-sectionally correlated. It can be termed as ‘firm effect’ and in this scenario, the observations of a firm in different years are correlated. In the second case, the residuals of a given year are correlated across firms. This can be called ‘time effect’ and in this situation, the observations of various firms are correlated within one time period. It is usual that in panel data sets, there is presence of firm effect and time effect. Fama Macbeth method effectively addresses time effect as one regression is estimated for one time period. Therefore, this approach is instrumental in minimizing time effect. The bias resulting from firm effect is addressed by using Newey West standard errors as they are clustered by firm. Various contemporary studies have used this method for the purpose of estimation. In addition to the seminal works mentioned above, Petersen139 reports that during 2001 to 2004, the 34% of papers that were published in Journal of Finance, the Journal of Financial Economics and the Review of Financial studies and used panel dataset employed Fama Macbeth method for their estimations.

An important limitation of this method is the possible presence of time-series autocorrelation and we used Newey West (Two Lags) adjusted standard deviation to correct for this issue. We can, therefore, reasonably expect that this method is capable of producing reliable results. We have used three models to predict the firms’ propensity to pay dividends and our intention is to explore the dividend payout behaviour of the firms in relation to their corporate governance structure, idiosyncratic risk and agency constraints. Our first model (equation 5.10) is inspired by seminal work of Fama and French125 and explains the relationship of governance and dividend payment behaviour while controlling for three explanatory variables namely market-to-book assets, asset growth and profitability. It addresses the question how the firm would design its dividend policy in the light of firm’s corporate governance structure, growth opportunities, profitability and size. logit ðPayout Indicatori,t Þ = α + β1 Governance Indexi,t + β2 Market − to − Book Assetsi,t + β3 Asset Growthi,t + β4 Profitabilityi,t + β5 NYSE Percentilei,t

(5:10)

In the second model (equation 5.11), the risk variables are introduced to observe how the risk components may affect the payout behaviour. In this regard, it is meaningful, in line with Hoberg and Prabhala52, to add proxies for unsystematic and systematic risk in the model to observe the full impact. Moreover, two additional variables namely proportion of retained earnings in total equity and equity

42

5 The Model

investments in the business. Hence, this model is capable of predicting payout in an environment where the corporate governance, risk, investment opportunities, profitability, firm size, its past behaviour of retaining income and shareholders’ stake in the business shape the dividend payout policy. logit ðPayout Indicatori,t Þ = α + β1 Governance Indexi,t + β2 Idiosyncratic Riski,t + β3 Systematic Riski,t + β4 Market − to − Book Assetsi,t + β5 Asset Growthi,t + β6 Profitabilityi,t + β7 NYSE Percentilei,t + β8 RE=TEi,t + β9 Equity=Assetsi,t (5:11) In the third model (equation 5.12), we intend to see that in the circumstances that aggravate agency problem, how would the firm design its payout policy. As Jensen111 argues, agency problem is severe for weak governance firms in the presence of free cash flow. Moreover, the financial constraints can result in reduced liquidity and may affect payment behaviour. We have thus included two other variables namely free cash flow and proxy for financial constraints (KZ Index) to account for this situation in line with Bhattacharya, Li137. Hence, this model predicts payout while considering corporate governance, risk, financial constraints, free cash flow, size, profitability, growth opportunities, proportion of shareholders’ investment and retention pattern of the firm. logit ðPayout Indicatori,t Þ = α + β1 Governance Indexi,t + β2 Idiosyncratic Riski,t + β3 Systematic Riski,t + β4 KZ Indexi,t + β5 FCFi,t + β6 Market − to − Book Assetsi,t + β7 Asset Growthi,t + β8 Profitabilityi,t + β9 NYSE Percentilei,t + β10 RE=TEi,t + β11 Equity=Assetsi,t

(5:12)

In summary, three different models are used to study the linkage of payout policy with governance and idiosyncratic risk for the firm for the sample portfolios. These models have theoretical foundations in the existing literature as explained above and intend to address the issue of the expected payout for faith-based investors. It is worth mentioning here that, in dividend policy literature, usually, the stocks belonging to financial sector are not included owing to different regulatory structure of these firms. However, we did not exclude this sector from our market and SRI portfolios to make the comparison between our portfolios of interest more meaningful. In order to understand this argument, we first need to appreciate that financial sector is considered non-Shariah compliant and hence it cannot become a part of Shariah portfolios whereas there is no such restriction on including financial firms in a market portfolio or SRI portfolio. Therefore, the exclusion of financial sector from market and SRI portfolios reduce the universe and brings both these portfolios close to Shariah portfolio (in terms of constituents list) that may distort the

5.1 Data and Methodology

43

comparison. However, we have made the estimations for market and SRI portfolios excluding financial sector and reported in Table 5.36. The main results remain robust to this change as well. We now move on to the specification of variables that constitute the empirical models. The dependent variable is payer indicator which is a binary variable and the independent variables can be divided into four categories namely governance, risk, agency related and other control variables. – Dependent Variable – Payer Indicator: Our dependent variable is a dichotomous variable which is equal to ‘1’ in year t when the firm has a positive dividend per share by the ex-date in fiscal year t (Compustat item # 26) and zero otherwise. It reflects the probability of the event that the firm will pay dividend in the year under review. Our choice of this variable is motivated by two reasons. Firstly, our objective is to observe how governance and risk affect the propensity of faith-based firms to pay dividends and we are not interested in the volume of dividends. Therefore, this variable is a natural choice. Moreover it has been extensively used in dividend policy literature especially after identification of disappearing dividend puzzle by Fama and French136 and studies like Hu and Kumar50, John and Knyazeva45 and Hoberg, Phillips140 are just a few to name. Corporate Governance: Our main estimations are made using Governance Index as proxy for governance and this variable highlights the level of corporate governance within a firm as percentile score for each firm in the given year. This index is constructed in line with John, Knyazeva46 by taking into account board structure, ownership, internal governance committees and corporate audit. These traits are mainly related to the internal governance mechanism of the firm. Existing literature suggests that investor rights are better protected in the firms where outsiders control the firm, board is independent and performs effective monitoring with the assistance of its sub-committees is strong and audit is effective141,142. The detailed definitions of constituents of our Governance Index are listed below. These definitions are obtained from GMI Ratings Database Manuals and available in Manuals section of Wharton Research Data Services (WRDS). The subsequent explanations are from the existing corporate governance literature and some of the studies that are consulted to explain these variables include Jensen and Meckling143, Hu and Kumar50, John and Knyazeva45, Bebchuk, Cohen141 and Hayat and Hassan144. i. The first group of variables, included in Governance Index, is related to the ownership structure of the firm. The underlying idea is that ownership structure and board composition have important implications for the governance standard of the firm. ‘No Insider Control’ is a dummy variable that is equal to 1 if majority of outstanding shares is held by top management and/or directors and 0 otherwise. The underlying idea is that when majority shares are not held by directors, the company is better governed.

44

5 The Model

‘Ownership Diversity’ is a dummy variable that is equal to 1 if ownership category is either ‘Institutions Dominant’ or ‘Widely Held’ or ‘Indexed Stock’ or ‘Mixed Ownership’ and ‘0’ otherwise. The diversity in ownership allows better monitoring and lesser managerial control. ‘Outsiders Majority’ is a dummy variable that is equal to 1 if the ‘Outside’ and ‘Outside-Related’ directors of a board are in majority and 0 otherwise. The ‘outside directors’ are all fully independent directors on a given board while ‘outside related directors’ are all independent directors on a given board having a significant relationship with the company at present or in the past. ‘Outsider Majority Strict’ is a dummy variable that is equal to 1 if the ‘Outside’ directors of a board are in majority and 0 otherwise. When the independent directors who had never been associated with the company are in majority, the board is capable of protecting shareholder rights in a more effective manner. ‘Directors Active CEOs’ is a dummy variable that is equal to 1 if the percentage of directors on a board who are active CEOs of public or private companies is less than 30% of the total number of directors and 0 otherwise. The presence of a large number of directors on board who are serving as CEOs in the other companies can put negative influence on the effectiveness of board owing to the busy schedules of these directors and possible conflicts of interest. ‘Presence of Women Directors’ is a dummy variable that is equal to 1 if any woman director serves on the board and 0 otherwise. The presence of women on board improves the culture and performance of the board. ii. The second set of variables forming our Governance Index deals with the internal monitoring mechanism of the firm that is strengthened by the presence of audit, nomination and governance committees and frequent meetings of board of directors. ‘Business Ethics Code Available’ is a dummy variable that is equal to 1 if the organization has a formal business ethics code in place and 0 otherwise. This code usually is a guiding framework to conduct business responsibly, maintaining trust and credibility with stakeholders. ‘Board Meetings Frequency’ is a dummy variable that is equal to 1 If Board Meetings Frequency is 4 or above in a given year and 0 otherwise. The existing literature suggests that the frequent meetings result in more powerful board of directors. ‘Outsiders Board Members Meetings Frequency’ is a dummy variable that is equal to 1 if the non-executive board members meet separately from the full board and 0 otherwise. These directors can discuss the organizational issues more independently by conducting separate meetings where insiders cannot exercise influence on the proceedings. ‘Audit Committee – Independent’ is a dummy variable that is equal to 1 if the majority of directors who are members of audit committee are independent directors

5.1 Data and Methodology

45

and 0 otherwise. It is evident that independent directors monitor the proceedings of committees more strictly and their presence improves the quality of monitoring. ‘Audit Committee – Fully Independent’ is a dummy variable that is equal to 1 if the Audit Committee comprises wholly of independent directors and 0 otherwise. ‘Compensation Committee – Independent’ is a dummy variable that is equal to 1 if the majority of directors who are members of compensation committee are independent directors and 0 otherwise. The presence of independent directors in this committee can help in efficient allocation of salaries and other benefits for the executives. ‘Compensation Committee – Fully Independent’ is a dummy variable that is equal to 1 if the compensation Committee comprises wholly of independent directors and 0 otherwise. ‘Nomination & Governance Committee – Independent’ is a dummy variable that is equal to 1 if the majority of directors who are members of nomination committee are independent directors and 0 otherwise. ‘Nomination & Governance Committee – Fully Independent’ is a dummy variable that is equal to 1 if the compensation Committee comprises wholly of independent directors and 0 otherwise. ‘Company Compensation Plan Approved’ is a dummy variable that is equal to 1 if equity incentive plans have been approved by shareholders and 0 otherwise. ‘Formal Governance Policy Approved’ is a dummy variable that is equal to 1 if company has formal governance policy in place and it is available in Board Analyst and 0 otherwise. iii. The third group of variables is related to the quality of corporate audit and company’s adherence of financial reporting standards. ‘Auditor Independence’ is a dummy variable that is equal to 1 if auditor is independent and 0 otherwise. Big4Auditors is a dummy variable that is equal to 1 if the external auditor for the firm for the given year, as reported in company’s most recent proxy statement, is among top four audit firms (or their subsidiaries) namely Deloitte & Touche Limited Liability Partnership, Ernst & Young Limited Liability Partnership, KPMG Limited Liability Partnership and PricewaterhouseCoopers Limited Liability Partnership and 0 otherwise. It is expected that these auditors are capable of performing audit better than the other firms and their audit quality improves the transparency. ‘Auditor Opinion’ is a dummy variable that is equal to 1 if Auditor Opinion (Compustat item #20) is Unqualified or unqualified with additional language and 0 otherwise. Evidently, the companies having unaudited accounts or the audited accounts with no opinion or qualified opinion or adverse opinion have not maintained high standards of reporting of financial statements or they are misreporting financial information to deceive the investors and regulators.

46

5 The Model

‘Auditor Opinion- Internal Control’ is a dummy variable that is equal to 1 if Internal Control – Auditor opinion (Compustat item #21) is ‘Effective’ and 0 otherwise. If a company has weak internal controls or it has failed to provide the requisite information regarding internal control mechanism to the auditors, it implies that company has weak procedures and the shareholders’ interests are not safeguarded. In addition to these variables, two important variables were also considered for inclusion in the index namely ‘CEO signed SOX certificate’ and ‘CFO signed SOX certificate’. The CEO and CFO are required to sign a certificate that company has met standards set by Sarbanes-Oxley Act (2002) for certification of the published financials. However, it was observed that there was not a single company whose CEO and CFO had not signed SOX certificate during the sample period. Therefore, these variables were not included in the index. The details of index constituents and methodology are summarized in Table 5.5. The governance scores are converted into percentiles following Gompers, Ishii117 for winsorization. Table 5.5: Governance Index. S.

Variable

Ownership Related Variables  No Insider Control  Ownership Diversity  Outsiders Majority  Outsider Majority Strict  Directors Active CEOs  Presence Of Women Directors Internal Governance Mechanism  Business Ethics Code Available  Board Meetings Frequency  Outsiders Board Members Meetings Frequency  Audit Committee – Independent  Audit Committee – Fully Independent  Compensation Committee – Independent  Compensation Committee – Fully Independent  Nomination & Governance Committee – Independent  Nomination & Governance Committee – Fully Independent  Company Compensation Plan Approved  Formal Governance Policy Approved Audit Quality  Auditor Independence  BigAuditors  Auditor Opinion  Auditor Opinion – Internal Control

Data Source MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI Compustat Compustat

5.1 Data and Methodology

47

For robustness purpose, we have used three other proxies of corporate governance. The first proxy is institutional ownership and our motivation in using this variable is that the contemporary studies postulate that the institutional owners are in a better position to ensure effective monitoring owing to their resources119. The governance structure of the firms where institutional investors are in majority is strong and they use dividend payout as a tool for mitigation of agency conflicts. The second proxy used for robustness purpose is board independence that can be defined as the fraction of independent directors on board. Various studies argue that the presence of independent directors on board results in stronger board which is instrumental in regulating the behaviour of self-motivated managers45,46. The third governance proxy is CEO duality i.e. the instance when firm CEO is also the chairman of the board. Although Jensen145 argues that the board independence diminishes when CEO is also chair of the board, our motivation in using this variable is the opposite view inspired by stewardship theory i.e. a strong CEO who is also chairman may work in the best interests of shareholders by directing the resources to their best possible uses for the benefit of the organization146. It is tempting, thus, to test for the linkage between CEO duality and payout. The governance proxies are calculated using MSCI GMI Ratings database instead of more frequently used ISS RiskMetrics Director and Governance databases owing to the reason that MSCI provides with more coverage for the companies in our sample. Risk Controls: This study has used two controls for risk as proposed by Hoberg and Prabhala52. Idiosyncratic risk is the distinguished risk that a firm faces and it is standard deviation of residuals from a regression of stock’s excess return on Carhart126 factors. Systematic risk is the standard deviation of predicted values from this regression. As argued by Huang, Liu147, the estimates of these factors namely beta, size, book-tomarket ratio and momentum are capable of explaining cross-sectional variation in stock returns. The selection of these two variables is made in order to appreciate the impact of total risk exposure on a firm’s dividend payout decision. In addition to Carhart126 model, we have used CAPM and Fama and French125 model to estimate both risk variables for robustness of results. There are many studies that have used factor models to estimate these risk controls and some examples are Ang, Hodrick18, Fu17 and Hasan and Habib148. Agency Controls: The existing literature posits that the agency problem may be severe when there is excess free cash flow111 or the firm is facing financial constraints149. We have used two variables to add controls for these situations. The first variable is free cash flow (FCF) measure suggested by Lehn and Poulsen150. However, we have not deducted dividend payments in line with Bhattacharya, Li137 due to the reason that our objective is to know how FCF affects payout behaviour. If we deduct dividend payments from FCF measure, it will not remain meaningful anymore. FCF therefore can be defined as

48

5 The Model

Free Cash Flow =

Operating Income − Total income taxes + ΔDeferred taxes − Total interest expenses Total Assets

(5:13) Kadioglu and Yilmaz151 and Samet, Samet152 are among various studies that have used this measure. We have employed KZ Index of Kaplan and Zingales153 as a proxy for financial constraints. They define unconstrained or lesser financially constrained firms as those who hold large amounts of liquid assets and high net worth and exhibit lower difference between cost of external and internal funds. This index measures the intensity of financial constraints faced by a firm and it can be defined as KZ Index = − 1.002ðCF=K Þ − 39.368 ðDiv=K Þ − 1.315 ðCA=K Þ + 3.139LEV + 0.283Q (5:14) The details of this index are reported in Table 5.6. We have used percentile values of this variable for the purpose of winsorization in line with Gompers, Ishii117.

Table 5.6: KZ Index. KZ Index = −1.002(CF/K) − 39.368 (Div/K) − 1.315 (CA/K) + 3.139LEV + 0.283Q where Earnings before extraordinary itemsð18Þ + Depreciation and Amortizationð14Þ lagged property, plant and equipmentð8Þ Dividend Preferredð19Þ + Dividends Commonð21Þ DIV=K = lagged property, plant and equipmentð8Þ Cashð1Þ CA=K = lagged property, plant and equipmentð8Þ Total Debt Lev = Tota Debt + Total Stockholders′ Equityð216Þ CF =K =

where Total Debt = Debt in Current Liabilitiesð34Þ + Long − Term Debt − Totalð9Þ ‘Q’ i.e. Market-to-book ratio of assets can be calculated as Q=

Total Assetsð6Þ − Total Equity ð216Þ + Market Value of Equity Total Assetsð6Þ

where Market value of equity = Closing Stock Price ðFiscalÞ × Shares Outstanding

5.1 Data and Methodology

49

An alternate proxy for financial distress is Piotroski154 F score that uses three criteria i.e. profitability, financial leverage/liquidity and operational efficiency. We argue that KZ Index is a better proxy as it relates operating cash flows, dividends and cash to lagged property plant and equipment and hence provides a better picture of company’s liquidity position in relation to its investment in fixed assets. Additionally, it is extensively used in corporate governance literature like Hong, Kubik155, Cheng, Ioannou156, Carbó‐Valverde, Rodríguez‐Fernández157, Lian158 and Chan, Chou159. Other control variables: The first four variables are related to the dividend life cycle hypothesis which argues that mature firms pay higher dividends owing to their higher profitability levels because, in the initial years of operations, mostly the firms prefer retention of the funds and invest in growth opportunities and, as a result, the firms have to maintain a balance between the payout and retention136,160. In the light of this hypothesis, the firm’s profitability, growth opportunities (in shape of asset growth and market-to-book assets ratio) and firm size are the determinants of its dividend payout decision. The fifth variable is included to control for the financing structure of the company. The final variable i.e. RE/TE controls for the impact of earned equity on dividend payout. 1) Market-to-book ratio of assets reflects whether company is exposed to growth bias or value bias as high market-to-book ratio represents growth bias while low market-to-book is associated with value bias125. This is understandable because many times, the book value of assets does not account for the true value of intangible assets of the company. These assets like brands, patents and copyright are instrumental in growth of the company whereas the companies having high amount of book assets are mostly mature companies and may be categorized as value stocks. Theoretically, growing firms pay lesser dividends and invest more in expansion whereas the mature firms possess lesser avenues of growth and they distribute earnings to investors. This variable is included to see the impact of growth vs value bias on probability of payout. 2) Asset Growth variable is included to observe the influence of growth strategies on payout policy. The firms have choice of investing their earnings in assets or pay dividends and this variable has an important role in explaining propensity to pay dividends. 3) Profitability is also an important factor in deciding payout as the loss making firms are rarely expected to continue payments. Also, this measure partially reflects the stage of dividend life cycle where a firm resides. Our Profitability measure is equal to Earnings before extraordinary items (Compustat item No. 18) plus Deferred income taxes (Compustat item No. 50) plus Interest expense (Compustat item No. 15) scaled by total assets (Compustat item No. 6). Some recent studies161 have used another proxy of profitability namely gross profit/total assets. We contend that this proxy does not tell the whole story as a firm earning high gross profits may end up incurring net loss and

50

5 The Model

unable to pay dividends. When we add control for profitability, we are primarily interested in observing how profitability affects dividend payout. Our Profitability measure is a better proxy because it takes into account the net profit. Evidently, the loss making firms are rarely expected to continue dividend payments. 4) Firm size: NYSE percentile and Book Value of Assets: The firm size is a key element in our model because the propensity to payout is directly affected by firm size. The larger firms are mostly mature and expected to pay higher dividends whereas the smaller firms are mostly in the initial years and they prefer to invest in expansions. We have used two proxies of firm size. NYSE Percentile is the fraction of NYSE firms having market capitalization equal to or smaller than firm ‘i’ in year ‘t’ as a proxy for firm size. This variable is extensively used in existing dividend policy literature as proxy for firm size140. The estimations are also made using log (book value of assets) for robustness purpose. 5) Equity/Assets accounts for the capital structure of the firm. A firms’ capital structure (shareholders’ vs. creditors’ stakes) can affect financing decisions114 and therefore has important implications for the dividend policy decisions. 6) RE/TE reflects the amount of retained equity as a percentage of total equity. This metric is introduced by DeAngelo, DeAngelo162 who posit that the earned/ contributed capital mix is a proxy for the stage of dividend life cycle hypothesis on which a firm resides at time ‘t’. The firms with low RE/TE would be in growth stage while firms with high RE/TE would be seasoned firms. Therefore, this variable also capable of measuring the extent to which a firm is self-financed or relying on the external financing. We have used percentile values of this variable for the purpose of winsorization. In order to check for the robustness of results for earned equity, the alternate proxy used is RA/TA. This variable shows the amount of retained earnings as a percentage of book value of assets instead of total equity. It is appropriate to explain this variable in detail in order to develop the understanding of this variable and to offer the rationale why this control had been added in the basic model. RE/TE shows the proportion of total equity that is composed of retained earnings. In the initial years, the firms usually achieve profitability with great difficulty. Once the firms become profitable, their retentions are mostly used to finance their losses. Therefore, the firms having low RE/TE are mostly in the initial stages of their business as retained earnings grow with the increasing profits and high retentions. On the other hand, the firms with high RE/TE, visibly, are the ones that had accumulated earnings over the course of several years. The high levels of retained earnings make these mature firms self-financed and comparatively lesser reliant on external funding. DeAngelo, DeAngelo162 used this variable to test dividend life cycle hypothesis due to its ability to demonstrate whether the company is self-financed or

5.1 Data and Methodology

51

relying upon the external financing. They argue that this variable is conceptually a better measure of a firm’s dividend life cycle stage as compared to cash because high cash levels may be a result of factors other than profits (for example, new equity offerings or debt). They observe that the propensity to pay dividends increases with the relative amount of RE/TE in their financing structure. In line with this argument, the firms with low level of earned equity (RE/TE) are hardly expected to pay any dividends. In the similar manner, the dividend payments would be higher when retained earnings would be a large fraction of total assets i.e. the higher the RE/TE, the greater the likelihood of dividend payout for the firm. This variable is included in the econometric model to add an additional control for the dividend life cycle stage of the firm to predict the likelihood of dividend payout in line with recent studies like Bhattacharya, Li137. Table 5.7: Description of Independent Variables. Variable

Definition

Sign

Source

Governance Index

Governance ranking based on  governance related variables (Details available in Table .). The data is obtained from MSCI GMI Ratings (Companies).

+ = − John, Knyazeva

Alternate Governance Proxies Institutional Ownership

Dummy: Is equal to  when the firm is owned by Institutional investors and ‘’ otherwise. The data is obtained from MSCI GMI Ratings (Companies).

+ = − Chang, Kang

Board Independence

Outside Directors (Related)/Total number of the directors. The data is obtained from MSCI GMI Ratings (Companies).

+ = − Hu and Kumar

CEO Duality

Dummy: Is equal to  if CEO is Chairman of the Board of Directors and ‘’ otherwise. The data is obtained from MSCI GMI Ratings (Companies).

+=−

Risk related Variables Idiosyncratic risk (IR)

The standard deviation of residuals from a regression of firm- – specific daily excess stock returns the Carhart’s four factors.

Systematic Risk

The standard deviation of the predicted value from the above-mentioned regression defining IR.

Hoberg and Prabhala

+=−

Agency related Variables KZ Index

Financial Constraints Index (Details available in Table .).

–

Free Cash Flow

Operating Income () minus total income taxes () plus ΔDeferred taxes () minus total interest expenses () scaled by Total Assets

+ = − Lehn and Poulsen

Kaplan and Zingales

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5 The Model

Table 5.7 (continued) Variable

Definition

Sign

Source

Hoberg and Prabhala Fama and French

Other Control Variables Market-to-book ratio of assets

Market Value of Assets/Book Value of Assets (Details available in Table .).

–

Asset Growth

ΔTotal Assets/Total Assets at year t-

–

Profitability

Earnings before extraordinary items () plus Deferred income taxes () plus Interest expense () all divided by total assets.

+

Firm Size New York Stock Exchange market capitalization percentile + i) NYSE Percentile i.e. the fraction of NYSE firms that have equal or smaller capitalization than reference firm in year t. NYSE percentiles are obtained from Kenneth R. French’s webpage. ii) Total Assets Log (Total Assets) Equity/Assets

The Stockholder’s Equity ()/Total Assets ()

–

RE/TE

Retained Earnings ()/The Stockholder’s Equity ()

+

RE/TA

Retained Earnings ()/Total Assets ()

+

DeAngelo, DeAngelo

5.2 Results and Discussions The idiosyncratic risk calculations for US (market proxy), SRI and Shariah portfolios are presented in Table 5.8. The table shows estimates across different time periods as well as portfolio designing strategies. The Carhart four factor model was applied to generate the estimates. Table 5.8: Portfolio Idiosyncratic Risk. Equally Weighted Portfolio

– Pre-Crisis Crisis Post Crisis

Capitalization Weighted Portfolio

US

SRI

Shariah

US

SRI

Shariah

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

5.2 Results and Discussions

53

The table shows that for equally weighted portfolios, the Shariah portfolio exhibits lowest risk (2.11%) as compared to US and SRI portfolios (2.3% and 2.28% respectively) for the sample period. period. These findings suggest that for the sample period, Shariah portfolio is more suitable for investors with lower risk appetite. In comparison to market and SRI portfolios, Shariah portfolio exhibits slightly higher pre-crisis and post crisis idiosyncratic risk while during global financial crisis, the idiosyncratic risk is significantly lower than the other two portfolios. The apparent argument may be that Shariah portfolio does not include finance industry that was a major victim of the crisis. When portfolios are capitalization weighted, the level of idiosyncratic risk is markedly reduced and approaches to zero for the sample period as well as out of sample tests for all portfolios. The idiosyncratic risk for value weighted Shariah portfolio is slightly higher across all the periods in comparison to the other two portfolios but it is very small. It can be inferred from these results that Shariah compliant portfolio is superior in terms of stand-alone risk in general as well as during crisis period. It is also evident that idiosyncratic risk for SRI portfolio also remains lower than market for the sample and out of sample periods. Therefore, it can be asserted that faithbased investors will be exposed to lower excess unsystematic risk as compared to the other investors if they include their religious or social responsibility beliefs while selecting stocks for portfolio formation. Moreover, the idiosyncratic risk for all three portfolios using capitalization weighted returns is very low but still does not approach zero. These findings are in line with investment area literature that posits markets, in reality, are not frictionless and idiosyncratic risk is present in even well diversified portfolios18,20. These results are further validated when the average idiosyncratic risk (for raw returns) at stock level is analysed at portfolio as well as industry levels as shown Table 5.9 and figure 5.1. Table 5.9: Average Idiosyncratic Risk (Stock Level) – Distribution among Industries. Idiosyncratic Risk (Average)

Portfolio Level Agriculture and Forestry Mining Construction Manufacturing Transportation & Utilities Wholesale Trade Retail Trade

US

SRI

. . . . . . . .

. . . . . . . .

Shariah

Difference in Means US-SRI

US-Shariah SRI-Shariah

. .*** .*** .*** . −. .*** .*** . .*** .*** .*** . . .*** .*** . .*** .*** .*** . −.*** −.*** −.*** . .*** .*** .*** . −.*** .*** .***

54

5 The Model

Table 5.9 (continued) Idiosyncratic Risk (Average)

Finance & Real Estate Services Others

US

SRI

Shariah

. . .

. . .

. . .

Difference in Means US-SRI

US-Shariah SRI-Shariah

.*** −.*** −.*** .*** .*** .*** .* .*** .***

0.0230 0.0210 0.0190 0.0170 0.0150 0.0130 0.0110 0.0090 0.0070

US SRI

ct M io an n uf ac tu Tr rin an g sp or W ta ho tio le n sa le Tr ad Re e ta il Tr ad e Fi na nc e Se rv ic es O th er s

g

tru

in

in

re

ns

tu ul

M Co

A

gr

ic

To ta l

SHARIAH

Figure 5.1: Mean Idiosyncratic Risk (Raw Returns) – Industry Wise (2006–15).

The mean idiosyncratic risk at portfolio level is same across portfolios and there is no significant difference in means for the sample portfolios. Moreover, industry wise distribution reveals that sectors within market and SRI portfolio carry firm-specific risk of the similar magnitude. However, Shariah portfolio significantly differs from these two portfolios and for most of the sectors (excluding transport and finance) it is lower than the other two portfolios. It implies that a Shariah compliant investor would be facing lower idiosyncratic risk for all the sectors (except transport and finance) in comparison to market and SRI portfolios. Furthermore, the mean idiosyncratic risk using capitalization weighted returns approaches to zero at portfolio level and also for the industry sectors. This finding is also in line with existing knowledge67 as well as our portfolio level results. The results for capitalization-weighted returns are not shown here as they may be redundant owing to the reason that they are zero for all the sectors up to four decimal points. It is worth mentioning here that the industry-specific risk is dependent upon the cyclicality of industry67. The table shows that Mining sector has highest idiosyncratic risk. The obvious reason is that this business involves exploration and high

55

5.2 Results and Discussions

investments having uncertain outcomes. In contrast, transportation sector has lowest risk. Furthermore, the retail trade is riskier than wholesale trade that may be an outcome of the volume of the difference in their respective volumes. The construction sector is riskiest after Mining and owing to its significant size, it can be argued that this sector is significantly most volatile among the industrial sectors. It is understandable as our sample covers the period of subprime crisis when on one hand, housing prices sharply reduced and on the other hand, the construction activity virtually halted. It should be noted, however, that the average firm specific risk for Shariah portfolio is lower for construction sector mainly due to the constraints on debt for these firms. Evidently, these Shariah compliant firms are lesser leveraged and therefore their risk is lower. To get further insights and to observe the explanatory power of factor models, CAPM and Fama and French125 models are used to estimate idiosyncratic risk for the sample and out of sample periods. Tables 5.10 and 5.11 show these estimations. It is evident that our main results are robust for both equally weighted as well as capitalization weighted portfolios as the estimation using these two methods are qualitatively similar as the main results. Table 5.10: Idiosyncratic Risk for EW Portfolio using CAPM and FF3. Market Portfolio

– Pre-Crisis Crisis Post Crisis

SRI Portfolio

Shariah Portfolio

CAPM

FF

CAPM

FF

CAPM

FF

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

Table 5.11: Idiosyncratic Risk for Capitalization Weighted Portfolio using CAPM and FF3. Market Portfolio

– Pre-Crisis Crisis Post Crisis

SRI Portfolio

Shariah Portfolio

CAPM

FF

CAPM

FF

CAPM

FF

. . . .

. . . .

. . . .

. . . .

. . . .

. . . .

The above findings suggest that idiosyncratic risk exists in the sample portfolios and its magnitude differs among sample portfolios. We proceed to analyze how different investors are rewarded for the risk they are assuming.

56

5 The Model

The first step in this regard is the review of the mean returns at portfolio levels as well as for various economic sectors to identify the trends and differences in performance. Table 5.12 and figure 5.2 reveal that the portfolio level returns are higher for market and SRI portfolios than Shariah portfolios and there is significant difference between means for the three portfolios. Market and SRI returns are higher for most of the economic sectors as well. Shariah portfolio only offers superior returns for Agriculture, Mining and Wholesale trade segments. The most plausible explanation is that the respective sizes of market and SRI portfolios are much larger as compared to Shariah portfolio. Additionally, in reality, most of the economic sectors are capital intensive and Shariah firms cannot avail debt above a certain threshold. However, in case of agriculture and trade sectors, the market credit is more easily available. Table 5.12: Mean Holding Period Returns (Raw). Difference of Means Tests

Portfolio Agriculture and Forestry Mining Construction Manufacturing Transportation & Utilities Wholesale Trade Retail Trade Finance & Real Estate Services Others

US

SRI

. . . . . . . . . . .

. . . . . . . . . . .

Shariah . . . . . . . . . . .

US-SRI

US-Shariah

SRI-Shariah

.*** .*** . . .*** −.*** .*** .*** .*** .*** .***

.*** . −. −. . .*** −.*** .*** −.*** .*** .***

.*** −. −. −. . .*** −.*** .*** −.*** .*** .***

0.37 0.32 0.27 0.22 0.17

US

0.12

SRI

0.07

Shariah

Ot he rs

ce Se rv ice s

an Fin

ra il T ta

Re

le

Figure 5.2: Mean Holding Period Return (Raw).

de

e ad Tr

tio sa le ho W

an Tr

M

an

uf

sp

ac

or

ta

tu

ct tru ns

Co

n

g

io

rin

n

g in in M

ul ric Ag

Po

rtf

ol

tu r

io

-0.03

e

0.02

57

5.2 Results and Discussions

Table 5.13 and figure 5.3 show that capitalization weighted returns are also higher for market and SRI portfolios in comparison to Shariah portfolio at aggregate level as well as industry level. Shariah portfolio only offers superior returns for Agriculture, Wholesale trade and retail trade sectors. For most of the sectors, the difference is significant among the sample portfolios. As already explained, the reasons can the difference in portfolio size and availability of financing facilities. The above statistics show that in general, market and SRI portfolios are yielding higher holding period returns than Shariah portfolio.

Table 5.13: Mean Holding Period Returns (Capitalization Weighted). Difference of Means Tests SRI Shariah

US . . . . . . . . . . .

Portfolio Agriculture & Forestry Mining Construction Manufacturing Transportation & Utilities Wholesale Trade Retail Trade Finance & Real Estate Services Others

. . . . . . . . . . .

. . . . . . . . . . .

US-SRI

US-Shariah

SRI-Shariah

−.*** .* −.** .*** −.*** −.*** .** .*** −.*** −.*** −.**

.*** −. .*** .*** .*** .*** −.*** .*** .*** −.*** .***

.*** −. .*** .*** .*** .*** −.*** −.*** .*** −.*** .***

0.15 0.13 0.11 0.09 0.07

US

0.05

SRI

0.03

Shariah

Figure 5.3: Mean Holding Period Return (Capitalization Weighted).

Ot he rs

ce Se rv ice s

an

de ra il T

ta

Fin

e ad Tr Re

le sa

W

ho

le

sp Tr

an

uf an M

tio or

ta

tu ac

tru ns Co

n

g rin

n ct

in

io

in

re M

ul tu ric

Ag

Po

rtf

ol

io

-0.01

g

0.01

58

5 The Model

In order to assess the risk-adjusted returns, we have estimated Jensen’s alpha for the portfolios (equally weighted and capitalization weighted) and also reported factor sensitivities to get the complete picture of the sample period and out of sample periods. The results using Carhart Model are reported in Tables 5.14 and 5.15. We observe that for the sample period, when the portfolios are constructed giving equal weights to the constituents, all the three portfolios beat the market and alphas are highly significant. The market proxy portfolio offers the highest returns for the sample period and these returns are significantly higher than SRI and Shariah portfolios. However, there is no significant difference between the alphas of faith-based portfolios. The Shariah portfolio has lowest value of Jensen’s alpha for the full sample. Table 5.14: Estimation of Jensen’s Alpha using equally weighted returns (CRH4). Difference of Alphas tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** (.) .* (.) .*** (.) .*** (.)

.*** (.) . (.) .*** (.) .*** (.)

.*** (.) .** (.) .*** (.) . .

.** (.) .*** (.) −. (.) .** (.)

.** (.) −. . −. (.) .*** (.)

. (.) −.* (.) −. (.) .*** (.)

Table 5.15: Factor Coefficients – Equally Weighted Portfolio (CRH4). Difference of Coefficients Tests US –

SRI

Shariah

.*** .*** .*** (.) (.) (.) Smb .*** .*** .*** (.) (.) (.) Hml .*** .*** −.*** (.) (.) (.) mom −.*** −.*** −.*** (.) (.) (.) Pre-Crisis mkt-rf .*** .*** .*** (.) (.) (.) Smb .*** .*** .*** (.) (.) (.) Hml .*** .*** −.*** mkt-rf

US-SRI

US-Shariah

SRI-Shariah

−.*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) −.*** (.) −.***

−.*** (.) −.*** (.) .*** (.) −.*** (.) .*** (.) −. (.) .***

−. (.) .*** (.) .*** (.) −.*** (.) .*** (.) .** (.) .***

59

5.2 Results and Discussions

Table 5.15 (continued) Difference of Coefficients Tests US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

(.) −.*** (.) mkt-rf .*** (.) Smb .*** (.) Hml .*** (.) mom −.*** (.) mkt-rf .*** (.) Smb .*** (.) Hml .*** (.) mom −.*** (.)

(.) −.*** (.) .*** (.) .*** (.) .*** (.) −.*** (.) .*** (.) .*** (.) .*** (.) −.*** (.)

(.) .*** (.) .*** (.) .*** (.) −.*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) −.*** (.)

(.) −.*** (.) −.*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) −.*** (.) .*** (.) .*** (.)

(.) −.*** (.) −. . .*** (.) .*** (.) −.*** (.) −.*** (.) −.*** (.) .*** (.) .*** (.)

(.) −.*** (.) −. . .*** (.) .*** (.) −.*** (.) −.*** (.) −. (.) .*** (.) .*** (.)

mom Crisis

Post Crisis

The out of sample tests for Jensen’s alpha as reported in Table 5.14 offer interesting insights as in the pre-crisis period, Shariah portfolio offers highest risk adjusted return. Moreover, the sample portfolios perform almost identically during crisis period. It is interesting to note that portfolios offer extremely high returns during crisis period. This finding is not understandle and there is a possibility that Carhart model could not estimate the correct values due to extreme volatility during the said period and abnormal values for factor returns. There is no significant difference in the performance of these portfolios during crisis period. In post crisis period, US and SRI portfolios still beat the market but the after crisis alpha for Shariah portfolio is not significant. Also, there is significant difference among the performance of portfolios in the post crisis period. The Carhart model results for factor sensitivities, as reported in Table 5.15, for equally weighted portfolios show that for the sample period, the three portfolios have significant beta greater than ‘1’ implying that their systematic risk is higher than the market. They are offering positive alphas for the said period implying that the higher-than-market risk is compensated by the higher-than-market risk adjusted return. However, the Shariah portfolio has highest sensitivity with the market. This finding reveals that Shariah investors are accepting lower return against higher market risk and hence they are disadvantaged.

60

5 The Model

The size effect is positive and significant across the sample portfolios suggesting that the sample portfolios predominantly carry small firms and their return is driven by the presence of these firms. Furthermore, the value effect exists for both market proxy and SRI portfolios, which shows that the returns for these portfolios are caused by the presence of high book-to-market stocks. These firms are usually seasoned companies and manifest stable earning patterns. Conversely, the key drivers of returns for Shariah portfolio are growth stocks. Finally, the momentum factor is negative across the portfolios indicating that portfolios do not carry past winners among the constituents and their returns are not guided by momentum strategy. The factor sensitivities for out of sample tests are also in line with our results for sample period. The above findings on equally weighted portfolios suggest that faith-based portfolios beat the market for the sample period and during this time, their performance is significantly different from each other. Furthermore, these portfolios significantly beat the market for the out of sample periods but their performance is not different during the crisis period. We did not compare these results with the existing studies as the indices/mutual funds mostly follow value weighted strategy and the recent studies, like Ashraf, Felixson102 and Ashraf and Khawaja56, assessing comparative portfolios of faith-based portfolios also use capitalization weighted strategy. The results for the capitalization weighted portfolio, reported in Table 5.16 show that the sample portfolios perform below the market. There is marginal but significant difference in the value of alphas among the three portfolios for the sample period. Out of sample tests show that before crisis, the performance of sample portfolios significantly differed. In the crisis and post crisis periods, significant difference is found among the performance of market proxy and SRI portfolios. However, during the same period, there is no significant performance difference among the market proxy portfolio and Shariah portfolios. Similaly, there is no significant difference in performance for SRI and Shariah portfolios during most of the sub samples. Table 5.16: Estimation of Jensen’s Alpha using capitalization weighted returns (CRH4). Difference of Alphas Tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) .** (.) .*** (.) .*** (.)

−.*** (.) −.*** (.) −. (.) . (.)

−.*** (.) −.** (.) −. (.) . (.)

61

5.2 Results and Discussions

We observe that risk-adjusted performance of Shariah portfolio is marginally better than the two other portfolios. The performance difference, although significant but is not substantial. We therefore argue that when capitalization weighted portfolio strategy is followed, there is no notable difference observed in the performance of market and faith-based portfolios. The results for factor sensitivities for capitalization weighted portfolio as shown in Table 5.17 reveal that beta is positive and significant across the three portfolios exhibiting market risk for the portfolios. The beta for Shariah portfolio is marginally higher than market (proxy) portfolio and SRI portfolio. This finding implies that Shariah investors are disadvantaged because they are accepting the same return against higher exposure to market risk. It also appears that size effect exists only for market proxy portfolio and SRI portfolio and their returns are driven by small firms’ returns for the full sample as this effect is not significant for Shariah portfolio in the given period. However, for out of sample tests, this effect exists for all the portfolios. Interestingly, during crisis period, the returns for Shariah portfolio predominantly come from large cap stocks. However, for all the other periods, the sample portfolios earn return from investment in small cap stocks. Table 5.17: Factor Coefficients – Capitalization Weighted Portfolio (CRH4). Difference of Coefficients tests US –

mkt-rf smb hml mom

Pre-Crisis

mkt-rf smb hml mom

Crisis

mkt-rf smb

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** .*** .*** .*** (.) (.) (.) (.) .*** .*** . .*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** .*** −.*** (.) (.) (.) (.) .*** .*** .*** .*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** .*** .** (.) (.) (.) (.) .*** .*** .*** −.*** (.) (.) (.) (.) .*** .*** −.*** .*** (.) (.) (.) (.)

.*** (.) .*** (.) .*** (.) .*** (.) −.*** (.) . (.) .*** (.) .*** (.) −. (.) .*** (.)

−.*** (.) .*** (.) .*** (.) .*** (.) −.*** (.) .** (.) .*** (.) .*** (.) −. (.) .*** (.)

62

5 The Model

Table 5.17 (continued) Difference of Coefficients tests US hml mom Post Crisis

mkt-rf smb hml mom

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

−.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** −.*** −.*** (.) (.) (.) (.) .*** .*** .*** −.*** (.) (.) (.) (.) .*** .*** . .*** (.) (.) (.) (.) .*** . .*** .*** (.) (.) (.) (.) .*** .*** .*** .*** (.) (.) (.) (.)

.*** (.) .*** (.) −.*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) −.*** (.) . (.) .*** (.) .*** (.)

Our results are in line with Managi, Okimoto163 who observed that there was no difference in the performance of conventional and SRI indices and there was no cost of using SRI criteria in making investment decisions. The sample portfolios exhibit value bias indicating that for capitalization weighted portfolio, the returns are driven by investing in firms having high book-to -market assets ratio. However, in post crisis period, the portfolios exhibit growth bias. The momentum effect is negative across the sample showing that all the three portfolios have not adopted the policy of choosing past year winners and shorting past year losers. However, in out of sample tests, we observe positive momentum sensitivity. It can be said that the momentum strategy does generate returns for these portfolios in shorter investment horizons. The CAPM based results for equally weighted portfolio reflect that alphas for all the three portfolios significantly beat market. The results as reported in Table 5.18 show that estimates for sample and out of sample periods are not consistent with Carhart model. They show a higher alpha for the Shariah portfolios for the sample period and pre-crisis periods. It is, however, observed that during and after crisis, Shariah portfolio underperforms as compared to market and SRI portfolios. The results for factor sensitivities (equally weighted portfolio), as reported in Table 5.19, show that Shariah portfolio is lesser sensitive to the other two portfolios for sample and most of out-of-sample periods. Therefore, CAPM suggests that Shariah portfolio offers best risk return trade off followed by market (proxy) portfolio. The results for capitalization weighted portfolio using CAPM highlight that the sample portfolios perform below the market and Shariah portfolio yields highest return. However, it has highest sensitivity with the market. There is not much difference in out of sample tests for the sample portfolios.

63

5.2 Results and Discussions

Table 5.18: Estimation of Jensen’s Alpha using equally weighted returns (CAPM). Difference of Alphas Tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** (.) −.*** (.) .*** (.) .*** (.)

.*** (.) −.*** (.) .*** (.) . (.)

.*** (.) . (.) .*** (.) −. (.)

.*** (.) .*** (.) −.* (.) .*** (.)

−. . −.*** (.) .** (.) .** (.)

−. (.) −.*** (.) .*** (.) . (.)

Table 5.19: Factor Coefficients – Equally Weighted Portfolio using CAPM. Difference of Coefficients Tests

–

mkt-rf

Pre-Crisis

mkt-rf

Crisis

mkt-rf

Post Crisis

mkt-rf

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) .*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

.*** (.) −.** (.) .** (.) −.*** (.)

.*** (.) .*** (.) .*** (.) −.*** (.)

Table 5.20: Estimation of Jensen’s Alpha using capitalization weighted returns (CAPM). Difference of Alphas Tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) .*** (.) .*** (.) .*** (.)

−.*** (.) −.*** (.) −. (.) −. (.)

−.*** (.) −.*** (.) −.** (.) . (.)

64

5 The Model

Table 5.21: Factor Loadings – Capitalization Weighted Portfolio using CAPM. Difference of Coefficients Tests

–

mkt-rf

Pre-Crisis mkt-rf Crisis

mkt-rf

Post Crisis mkt-rf

US

SRI

Shariah

.*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) .*** (.)

US-SRI −.*** (.) −.*** (.) −.*** (.) −.*** (.)

US-Shariah

SRI-Shariah

−.*** (.) .*** (.) −.*** (.) −.*** (.)

−.*** (.) .*** (.) −.*** (.) −.*** (.)

The results of estimations employing Fama French model are not very different from Carhart model results. Table 5.22 shows that, for equally weighted portfolios, all the sample portfolios beat the market. Shariah portfolio has lowest value of alpha and highest sensitivity to market risk implying that Shariah portfolio manifests lowest risk return trade off. The out of sample tests show that Shariah portfolio outperforms the other portfolios only in pre-crisis period. Table 5.22: Estimation of Jensen’s Alpha using equally weighted returns (FF3). Difference of Coefficients Tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** (.) . (.) .*** (.) .*** (.)

.*** (.) . (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) . (.)

.** (.) .*** (.) −. (.) .*** (.)

.* (.) −.*** (.) . (.) .*** (.)

. (.) −.*** (.) . (.) .*** (.)

The results of factor sensitivities as reported in Table 5.23 reveal that the sample portfolios have higher than market risk. The return predominantly comes from investing in small stocks. The market and SRI portfolios are subject to value bias and their returns are earned from seasoned firms while Shariah portfolio holds growth bias as the source of its returns are growth stocks. The results for value weighted portfolio, as reported in table 5.24, are also not very different from Carhart model results as Shariah portfolio has earned Jensen’s alpha equal to the other two portfolios while it has higher than market risk and therefore it is disadvantaged. However, no significant difference is observed during out of sample

65

5.2 Results and Discussions

Table 5.23: Factor Coefficients – Equally Weighted Portfolio using FF3. Difference of Coefficients Tests

–

mkt-rf smb hml

Pre-Crisis

mkt-rf smb hml

Crisis

mkt-rf smb hml

Post Crisis

mkt-rf smb hml

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.) .*** (.)

.*** (.) .*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.** (.) −.** (.) .*** (.) −. . −.** (.) .*** (.) .*** (.) .*** (.) .*** (.) −.*** (.) −.*** (.) .*** (.)

−.** (.) .*** (.) .*** (.) .*** (.) .* (.) .*** (.) .*** (.) .*** (.) .*** (.) −.*** (.) −. (.) .*** (.)

Table 5.24: Estimation of Jensen’s Alpha using capitalization weighted returns (FF3). Difference of Alphas Tests

– Pre-Crisis Crisis Post Crisis

US

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.*** (.) −.*** (.) −.*** (.)

−.*** (.) −.** (.) .*** (.) .*** (.)

−.*** (.) .*** (.) −. (.) . (.)

−.*** (.) .*** (.) −. (.) −. (.)

66

5 The Model

Table 5.25: Factor Coefficients – Capitalization Weighted Portfolio using FF3. Difference of Coefficients Tests US –

mkt-rf smb hml

Pre-Crisis

mkt-rf smb hml

Crisis

mkt-rf smb hml

Post Crisis

mkt-rf smb hml

SRI

Shariah

US-SRI

US-Shariah

SRI-Shariah

.*** .*** .*** −.*** (.) (.) (.) (.) .*** .*** . −.*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** .*** .*** (.) (.) (.) (.) .*** .*** .*** .*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** .*** −.*** (.) (.) (.) (.) .*** . −.*** .*** (.) (.) (.) (.) −.*** −.*** −.*** .*** (.) (.) (.) (.) .*** .*** .*** −.*** (.) (.) (.) (.) .*** .*** −.*** .*** (.) (.) (.) (.) .*** . −.*** .*** (.) (.) (.) (.)

−.*** (.) .** . .*** (.) −.*** . .** . .*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) .*** (.) .*** (.)

−.*** (.) .*** (.) .*** (.) −.*** (.) .* . .*** (.) −.*** (.) .*** (.) .*** (.) −.*** (.) . (.) .*** (.)

periods. The size premium and value/growth premiums are very low but significant for the sample portfolios. For the sample and most of out of sample periods, the portfolios are subject to value bias. We have found that the results estimated by Carhart model and Fama French model are mostly similar. They show that for both equally weighted and value weighted portfolios, the Shariah portfolio is disadvantaged. The CAPM, however, offers different results possibly due to its over-reliance on market risk premium for explaining excess returns. The portfolios beat the market when portfolios are equally weighted. It is also observed that the prime source of return for these portfolios is investment in small cap stocks. However, the high-minus-low factor gives conflicting results with respect to portfolio formation strategy. For equally weighted portfolios, the market (proxy) and SRI portfolios hold value bias while Shariah portfolio holds growth bias. On the other hand, for value weighted portfolios, all the sample portfolios hold growth bias.

5.2 Results and Discussions

67

As the empirical evidence of firm level studies on performance is scarce, it is difficult to relate the findings with existing literature. However, if we compare the findings with the studies on fund performance, our results are consistent with that of Renneboog, Ter Horst86, Ho, Abd Rahman94, Nainggolan, How85 and Boo, Ee29. In order to investigate how governance, risk, agency issues and firm performance measures affect the propensity of a firm to pay dividends. The first step in this regard is to discuss the linkage of dividend payment behaviour with the above mentioned firm specific variables. Table 5.26 shows descriptive statistics for our variables of interest with respect to the dividend payment behaviour of the firms. The overall governance score among the three sample portfolios is not different, though there is a significant distinction between payers and non-payers in terms of corporate governance. The dividend paying firms, in general, exhibit higher levels of corporate governance and experience lower idiosyncratic risk as compared to nonpayers. Furthermore, firms under higher financial constraints do not tend to pay dividends. It can thus be asserted that firms having good governance, low idiosyncratic risk and lower financial constraints tend to pay higher dividends and these results are observed across the sample portfolios. Although in case of market portfolio, payers and non-payers hold similar levels of free cash flows, the picture is different for SRI firms as well as Shariah compliant firms. For SRI firms, non-payers hold higher levels of free cash flow as compared to dividend paying firms which is consistent with classic agency problem. Nonetheless, the Shariah compliant companies holding higher free cash flows have chosen to pay dividends instead of retaining funds. It appears that these companies can be attractive for investors seeking dividends as there appears to be lower agency issues related to excess cash flows. Yet, this argument needs further testing. Our control variables for all the three sample portfolios and the statistics are in line with conventional knowledge. For example, market-to-book assets ratio is higher for non-dividend payers mainly due to the reason that these firms are in growth stage and prefer to invest in new projects instead of distribution. This argument is further strengthened by an increase in the variable asset growth for nonpayers. Moving further, it can be observed that firms experiencing pay dividends are the ones experiencing higher profitability. Firm size is inversely related to dividend payment behaviour as large and well established firms choose to return their profits to the investors in contrast to smaller companies that prefer to retain the cash flows for future growth. The dividend paying firms have higher levels of earned equity and leverage as compared to non-payers which is justifiable because these firms distribute a good amount of their earned cash to shareholders and require funds to run operations and finance their expansions. These statistics lead the way to further explore the impact of very high and very low idiosyncratic risk for payers and non-payers for different firm-related variables for the sample portfolios. For this analysis, firms with extremely low idiosyncratic risk fall in 1st quartile whereas the extremely high idiosyncratic risk firms fall in the

Governance Index Idiosyncratic Risk Systematic Risk KZ Index Free Cash Flow Market-Book-Assets Asset Growth Profitability NYSE Percentile Total Assets RE/TE Equity/Assets N

. . . . . . . . . , . . ,

. . . . . . . . . , . . ,

Total Non-Payer

Difference

. −.*** . .*** . .*** . .*** . −. . .*** . .*** . −.*** . −.*** , −,*** . −.*** . .*** ,

Payer

US Portfolio

Table 5.26: Descriptive Statistics – Payer/Non-Payer Analysis.

. . . . . . . . . , . . ,

. . . . . . . . . , . . ,

Total Non-Payer

Difference

. −.*** . .*** . .*** . .*** . .*** . .*** . .*** . −.*** . −.*** , −,*** . −.*** . .*** ,

Payer

SRI Portfolio

. . . . . . . . . , . . ,

. . . . . . . . . , . . ,

Total Non-Payer

Difference

. −.*** . .*** . .*** . .*** . −.*** . .*** . .*** . −.*** . −.*** , −,*** . −.*** . .*** ,

Payer

Shariah Portfolio

68 5 The Model

5.2 Results and Discussions

69

4th quartile. It is appropriate to analyse the three portfolios separately before looking for any possible differences in their behaviour. In Table 5.27, it can be observed that firms having extremely low levels of idiosyncratic risk are more prone to paying dividends whereas the bulk of firms facing higher unsystematic risk refrain from paying dividends. The governance level for payers is high in case of extremely high as well as extremely low idiosyncratic risk. The firms facing higher risk are experiencing higher asset growth but their profitability levels are lower. Our previous findings are further validated as we notice that dividend paying firms are larger in size and higher in leverage. They also succeed in generating more sales and possess more physical assets. Finally, it can be seen that majority of firms with low idiosyncratic risk tend to avoid paying dividends when they have free cash flow but there is a larger proportion of high idiosyncratic firms that pay dividends. Table 5.27: Interaction of Idiosyncratic Risk and Dividend Payout: US Portfolio. Low IR

Gov. Index Idio Risk Asset Growth Profitability Total Assets Total Debt Sales PPE FCF N

Total

Non-Payer

. . . . , , , , . ,

. . . . , , , , . 

High IR Payer

Difference

Total

. −.*** . . .*** . . .*** . . .*** . , −,*** , , −,** , , −,* , , −,*** , . .*** . , ,

Non-Payer

Payer

Difference

. . −.*** . . .** . . .*** . . −.*** , , −,*** , , −,*** , , −,*** , , −,*** . . −. , ,

Our statistics for SRI and Shariah portfolios, as reported in Tables 5.28 and 5.29, are mostly similar to market portfolio with the exception of free cash flow. As per the findings, majority of SRI firms at extremely low and high levels of idiosyncratic risk avoid dividend payment. On the other hand, Shariah compliant firms facing extremely very high idiosyncratic risk tend to distribute their free cash flows in shape of dividends. The results suggest that the investors having preference for dividends need to look for the companies with higher corporate governance, lower idiosyncratic risk, lower exposure to financial constraints and mature companies with higher size and earned equity. For the faith-based investors, these statistics do not indicate any special disadvantage. Shariah compliant companies seem to be lower in agency problem and the interested investors can hope for dividends.

70

5 The Model

Table 5.28: Interaction of Idiosyncratic Risk and Dividend Payout: SRI Portfolio. Low IR Total

.

Difference −.**

Total .

Non-Payer

Payer

Difference

.

.

. .

. .

. .

.*** .***

. .

. .

. .

. .***

Profitability Total Assets

. ,

. ,

. ,

.*** −,***

. ,

. ,

. ,

−.* −,***

Total Debt

,

,

,

−,**

,

,

,

−,***

Sales PPE

, ,

, ,

, ,

−,* −,***

, ,

, ,

, ,

−,*** −,***

. ,

. 

. ,

.***

. ,

. ,

. ,

.*

FCF N

.

Payer

Idio Risk Asset Growth

Gov. Index

.

Non-Payer

High IR

−.***

Table 5.29: Interaction of Idiosyncratic Risk and Dividend Payout: Shariah Portfolio. Low IR

High IR

Total

Non-Payer

Payer

Difference

Total

Non-Payer

Payer

Difference

. .

. .

. .

−.* .***

. .

. .

. .

−.*** .***

Asset Growth Profitability

. .

. .

. .

.*** −.

. .

. .

. .

.*** −.***

Total Assets Total Debt

, ,

, ,

, ,

−,*** −,***

, 

, 

, 

−,*** −.***

Sales

Gov. Index Idio Risk

,

,

,

−,***

,

,

,

−,***

PPE FCF

, .

, .

, .

−,** −.

, .

 .

, .

−,*** −.***

N

,





,





Nevertheless, these findings are preliminary and further analysis is required for a more valid conclusion. The results based on the Fama Macbeth approach to test for the propensity to pay dividends on set of variables provide further insights on this issue. A correlation analysis is done among the variables before moving to the estimations. We provide pair wise correlation between our variables of interest in Tables 5.30, 5.31 and 5.32 to see if there is any case of multi collinearity in our variables. The upper triangle in these tables reflects pearson’s correlation co-efficients while lower triangle shows spearman correlation co-efficients. The Pearson correlation evaluates

−. (