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Barth et al Hedge Funds.Strategies and Risk.doc

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Barth et al Hedge Funds.Strategies and Risk.doc

  1. 1. Hedge Funds: A Global Perspective on Strategies and Risks James R. Barth Auburn University and Milken Institute barthjr@auburn.edu Mark Bertus Auburn University bertumj@auburn.edu Tong Li Milken Institute cli@milkeninstitute Triphon Phumiwasana Milken Institute ephumiwasana@milkeninstitute.org Preliminary Draft Prepared for Joint Meeting of the Shadow Financial Regulatory Committees of Europe, Japan, Latin America and the United States Copenhagen, Denmark September 7-8, 2007
  2. 2. Introduction Unlike hedge funds, mutual funds are widely available to the public and therefore must be registered with the Securities and Exchange Commission. In addition, they are limited in the strategies they can employ. Hedge funds, on the other hand, are set up as limited partnerships and generally not constrained by regulatory limitations on their investment strategies. Indeed, although the word “hedge” refers to the hedging of the value of assets through the use of derivative instruments or the simultaneous use of long positions and short sales, most hedge funds do not involve hedging in this traditional sense. Many, in fact, do just the opposite. In this section, we examine some of the different strategies to determine differences in performance and risk. The impact of hedge funds on global financial stability and the need for greater regulation are important and timely issues, and it is no surprise that economists have tried to address them. But the results of these efforts have been less than successful. For example, in a recent study attempting to quantify the potential impact of hedge funds on systemic risk, Chan, Getmansky, Haas, and Lo (2005, p. 97) state that “we cannot determine the magnitude of current systemic risk with any degree of accuracy.” Similarly, Garbaravicius and Dierick (2005, p. 55) conclude, “It is very difficult to provide any conclusive evidence on the impact of hedge funds on financial markets. ...” Timothy Geithner (Geithner, p. 8), president of the Federal Reserve Bank of New York, gave a lecture in Hong Kong in September 2006, and addressed the issue of hedge fund regulation. “Clearly, capital supervision and market discipline remain the key tools for limiting systemic risk,” he said. “The emergence of new market participants such as leverage institutions does not change that.” In addition, Danielsson, Taylor, and Zigrand (2005, pp. 26–27) argue that while there exists a “… need for a credible resolution mechanism to deal with the default of systemically important hedge fund(s) … the procedural issues and related incentive effects [to do so] are complex …[and] … require further consideration in order to provide the correct incentives for the various parties.” Given the conclusions of these efforts, we have decided not to try to expand upon this line of enquiry here. Instead, we provide a comprehensive examination of some important aspects of the global hedge fund industry. This examination is based on a dataset assembled by HedgeFund.net that starts with eight hedge funds with $57 million 2
  3. 3. in assets in 1980 and grows to 7,144 funds with $1,232 billion in assets as of May 2007. We use this dataset to examine differences among hedge funds over time and by the strategies they employ. We pay particular attention to changes in the performance and risk of funds over time, and to the impact of various strategies on these differences. We also use regression analyses to examine the associations between a fund’s strategy and its associations between abnormal market movements. I. An Overview of the Hedge Fund Industry A. Growth and Size The recent flurry of news stories about hedge funds might lead some to think that such funds are relatively new. But Fung and Hsieh (1999) report that the first hedge fund was actually formed in 1949. It employed a long/short equity strategy and operated on the basis of leverage, two characteristics of many hedge funds today. They add that this first hedge fund remained fairly obscure until a magazine article in 1966 touted its high returns relative to those of mutual funds. The number of hedge funds subsequently grew fairly rapidly for a few years but fell back into obscurity due to losses suffered in several downturns in the equity market. The industry rebounded once again in 1986, when another magazine article reported that a newly established hedge fund had earned an extraordinary return in its first few months of existence. Today, there is roughly $1.232 trillion of assets under management in Hedge Funds globally (see Table 1). Moreover, in terms of the regional distribution of these assets, 51% are managed by Hedge Funds in the United States, while 41% and 8% are managed by Hedge Funds in Europe and the rest of the world respectively. While the magnitude of capital invested in hedge funds seems quite large, relative to levels of global GDP, banking assets, stock market capitalization, bond markets, derivative markets and Mutual Funds, these funds are minute. More specifically, assets under management by Hedge Funds are roughly 2, 1.5, 2, 1.7, 1.8 and 5 percent of the size of these other financial markets respectively. Looking at industry growth, the number of hedge funds has been increasing exponentially. Tables 2, 3 and 4 (see also Figures 1, 2, and 3) show the dramatic increase in the numbers, assets, and returns, for the industry for the last seventeen years. With the 3
  4. 4. exception of a decline in the number of funds during the first six months of 2006, from Jan 1990 to May 2007, Hedge Funds grew in number at an average annual rate of 26 percent. Additionally, total assets grew at an average annual rate of 38 percent, while the average monthly returns and standard deviations have steadily dampened. Not all funds that entered the industry during this time period remained alive until the ending date, of course. In fact, as of June 2006, 3,100 funds with $257 billion had exited the industry. Today, despite these exits, 7,144 funds remain. B. Differences in Size, Domicile, Location, and Age of Funds Although there has been growth in both the number and assets of hedge funds, asset growth has exceeded their growth in number. As a result, as table 2 shows, the average size of hedge funds has increased by more than 500 percent from 1990 to May 2007, from $34 million to $172 million. This occurred despite the fact that the average size of exiting funds is greater than the average size of entering funds. This difference reflects the fact that the age of exiting funds is greater than that of the newly entering funds. Not surprisingly, the average age of a fund has increased since 1980. As of June 2006, the typical fund had been in existence 5.3 years. Tables 5 and 6 provide information on the domiciles of hedge funds and the locations of the funds’ assets. Table 5 provides this information based upon the number of funds, while table 6 does the same for assets. Of the 7,144 funds as of May 2007 49 percent, or 3,528, are domiciled in the United States, and of these about half have their assets in the United States, with nearly all the remaining assets invested globally. Europe is second to the United States in terms of the number of domiciled funds, accounting for approximately 35 percent, or 2,483, of the total number of funds; of these only about 19 percent have their assets invested in Europe. The majority of the funds, 67 percent, have invested their assets globally. However, 76 percent of the funds with 75 percent of total fund assets still have their investments in U.S. dollar-denominated assets, regardless of where the assets are located. Table 6 also shows that the funds domiciled in the United States account for the largest amount of assets, $632 billion, with Europe second at $471 billion. Together they account for slightly less than 90 percent of the $1,226 billion in total fund assets. For 4
  5. 5. funds domiciled in the United States, 47 percent are U.S.-allocated and 48 percent are invested globally, while for Europe 24 percent are allocated within the continent and 63 percent globally. European-domiciled funds invest more assets in Asia, in terms of absolute amount and as a share of their total assets, than do funds domiciled in the United States. C. Hedge Fund Strategies Hedge fund performance and risk understandably attract the most investor attention. Tables 2, 3, and 4 show the average monthly return and volatility, as measured by standard deviation, of hedge funds from 1990 to May 2007. For all funds the average monthly returns range from a high of 2.39 percent in 1999 to a low of 0.3 percent in 2002. Separating the hedge funds into traditional and fund of funds returns the average monthly returns range from a high of 2.54 and 3.67 percent in 1999 to a low of 0.35 percent in 2002 and -0.16 percent in 1994 respectively. Hedge funds come not only in a variety of sizes, asset locations, and domiciles, but also in a variety of strategies. Our dataset lists 36 strategies for hedge funds and these strategies are defined in table 7. Table 8 illustrates the relative importance of each strategy based on the share of that strategy in the total number of hedge funds and on the share of that strategy in the total assets of hedge funds. The two most common strategies employed are the fund of funds and the long-short equity, with 24 percent of all funds employing the former and 21 percent of all funds employing the latter. The funds employing these two strategies also account for 25 percent and 17 percent of the total assets of funds, respectively. In terms of concentration, 65 percent of all funds invested 65 percent of all assets in one of four trading strategies; fund of funds, Long/short equity, CTA/Managed futures, and Multi-strategy. Over the last decade the number of funds following these strategies grew at an average rate of 19 percent and the assets grew by 40 percent. Moreover, hedge funds in these four trading strategies earned an average monthly rate of return of 1 percent while experiencing a volatility level of 1.93 percent. In general, Table 8 shows that the average growth in all hedge funds and assets across all strategies for the last ten years was roughly 18 and 38 percent respectively. 5
  6. 6. Hedge funds following the asset based lending strategy experienced the largest growth in numbers, 40 percent, and assets, 108 percent. In terms of individual performances, hedge funds using the fixed income arbitrage strategy earned the highest average return, 2.71 percent, and faced the greatest risk, 10.5 percent. As of May 2007, funds of funds constitute the largest group of existing funds, both in terms of number and assets; these are followed by long/short equity funds. In contrast, long/short equity funds, event-driven funds, and market-neutral funds make up the largest groups of graveyard funds. Looking at the total assets and numbers of entering and exiting hedge funds according to strategy, funds of funds with multi-strategies account for 25 percent of total entering funds and 21 percent of entering-funds assets. They also account for 23 percent of total exiting funds and 26 percent of exiting-funds assets. Figure 4 shows the risk-return tradeoffs for hedge funds grouped on the basis of strategy. The figure indicates a significantly positive relationship on average between return and risk. Still, some of the strategies employed by funds have underperformed, in terms of generating a return that compensates for the associated risk. This is the case for several strategies when examining the tradeoffs both for the most recent five-year period and the past year, but especially so in the latter case. D. Management Fees The management fees of hedge funds attract a great deal of attention, not only from potential investors but also from the financial press. Managers of such funds rely on these fees and performance incentives for their income, above and beyond the returns they receive on their own investments in the funds. Currently, funds with only 5 percent of total assets set such fees at 0.75 percent or less. Funds accounting for 55 percent of total assets, however, set fees at 1.25 percent or higher. Funds with just 2 percent of the assets, which are those at the low and high extremes, set fees at less than 0.25 percent and greater than 2.25 percent, respectively. Over time, the shares of total assets reflecting different management fees have shifted into the higher categories, but with substantial variation across the different ranges of fees. 6
  7. 7. There is significant variation in the number of entering and exiting hedge funds and their asset concentrations, based on strategy distribution and management fees. Funds with 7 percent of total assets of entering hedge funds set management fees at 0.75 percent or less. Funds accounting for 89 percent of total assets of entering funds charge a management fee higher than 0.75 percent, but no greater than 2.25 percent. Funds that account for 91 percent of exiting funds have a management fee between 0.75 percent and 2.25 percent. Only 3 percent exiting funds set the management fee at less than 0.25 percent or higher than 2.25 percent, which are the low and high extremes for management fees, respectively. The performance incentives of hedge funds clearly attract the most attention. The reason is 60 percent of all hedge funds charged incentives of 15 percent or higher. The hedge funds charging these fees, moreover, accounted for 56 percent of total assets. We detect a binomial distribution of incentive fees in the following sense: Most funds with the most assets either charge less than 10 percent or between 15 percent and 20 percent. There is roughly a 30 percent to 50 percent split, in terms of both number and assets, for funds charging 10 percent or less and those charging between 15 percent and 20 percent, respectively. The performance incentives, moreover, have tended to drift upward since the early 1980s, despite the tremendous increase in the number and assets of hedge funds. Looking at the numbers of entering and exiting hedge funds and their asset allocations, based on strategy distribution and management incentives, fifty-eight percent of all entering funds, which represent 59 percent of total assets, set the incentive fee at 15 percent to 20 percent in 2006. That fee range also corresponds to 64 percent of all exiting funds, which represent 48 percent in assets. Funds that account for 30 percent of total assets of exiting funds have an incentive fee of less than or equal to 5 percent. E. Lockup Periods When investors initially put their money into hedge funds, they cannot freely cash out at any time thereafter. Instead, they are required to remain in the fund over a specified period of time before any withdrawals may take place. The required minimum time period is the initial lockup period. Nearly 50 percent of funds as of June 2006 have a 7
  8. 8. lockup period of up to 30 days, with the vast majority of the remaining funds having a lockup period of up to a year. In terms of the distribution of assets by entering and exiting hedge funds, based on lockup periods, the funds representing half the assets of all entering funds have a lockup period longer than one quarter, but no longer than one year. However, this group of funds only represents 30 percent of the assets of exiting funds. Funds with a lockup period up to 30 days account for 22 percent of the exiting funds in terms of assets. The distribution of the assets of funds by lockup period closely parallels that for the number of funds. 49 percent of the assets of all funds are linked to lockup periods of up to 30 days. Only 2 percent are linked to lockup periods exceeding a year. Over time, there has been a shift toward longer lockup periods employed by more funds with more assets. We also examine the lockup periods employed by funds of different sizes and strategies. In general, there is not much of a difference in lockup periods employed by funds of varying sizes and strategies. The lockup period is shortest for the commodity trading adviser funds and longest for the sector funds, with event-driven funds closely behind. In the case of commodity trading adviser funds, 91 percent of the assets are in the funds with a lockup period of 30 days or less; in the case of sector funds, 61 percent of the assets are in the funds with a lockup period of more than 90 days, but less than a year. Since hedge funds require the services of both accounting and brokerage firms, it is informative to examine which firms are most frequently used. Three accounting firms, PriceWaterhouse Coopers, Ernst & Young, and KPMG, are the firms of choice for 54 percent of all hedge funds reporting such information, and that these funds account for 65 percent of total assets. Nearly 40 percent of the funds with 41 percent of total assets do not report information about which brokerage firms are used. Of those that do report this information, Morgan Stanley, Goldman Sachs, and Bear Stearns are the top three firms, jointly servicing about 25 percent of all funds with about 25 percent of total assets. II. Illiquidity Risk and Hedge Fund Returns 8
  9. 9. Currently, one of the greatest challenges in the hedge fund industry is the valuation of funds. Generally, valuation problems arise when a fund is invested in illiquid assets i.e., assets that are not traded frequently, and or, easily bought and sold without major price concessions. Some evidence suggests that fund managers, who in invest in illiquid assets, smooth their returns. That is, given the nature of the compensation contracts and performance measures, managers have an incentive to smooth their returns over time. To manage returns, managers may mark their portfolios to less than their actual value in months with high returns to insure their returns during months with low returns. Alternative explanations for the serial correlation could be due to a linear extrapolation from the most recent transaction price (see Germansky, Lo, and Makarov, 2004). Marking-to-market a fund in this manner will yield a piecewise linear trajectory in fund value, thereby exhibiting smoother returns, lower volatility and serial correlation. If there is a significant presence of liquidity risk in hedge funds, then a simple examination of monthly returns should provide some insight. Tables 11 and 12 illustrate the monthly persistence of positive and negative fund returns over the sample period of January 1991 to June 2007. These tables show that the monthly persistence does exist and it is much greater for positive returns than for the negative returns, which is seemingly consistent to managers smoothing returns. Moreover, the majority of funds with the greatest level of persistence in returns are the fixed income arbitrage funds. Relative to the S&P 500 composite index performance, hedge funds illustrate similar results (see Tables 13 and 14. III. Some Statistical Analyses A. Correlations Across Hedge Fund Strategies and Markets With the rapid growth in hedge funds, regulators along with investors are becoming more concerned with risks these funds may create in the financial system. Recent studies have examined contagion effects between hedge funds in recent years. We do not attempt to provide a comparable study here. Instead our goal is a much more modest one: to exam the relationship between trading strategies and market movements. To investigate the potential hedge funds have to create systemic risk in a financial system, it is necessary to look at how hedge funds interact with one another. Table 9 9
  10. 10. examines the correlation among hedge fund returns by strategies. These correlations show that there is a significant degree of coordination among most trading strategies. As expected, the riskier trading strategies, such as aggressive growth, emerging markets, value, technology sector, and opportunistic are highly positively correlated, and they tend to have moderately positive correlations with all other strategies. It is also interesting to note, that independent of the industry, such healthcare, energy, bonds, or equity, all strategies tend to move in the same direction. The only two trading strategies that do not move systemically with other strategies are the CTA/Managed futures and the Asset Based Lending Strategies. To further investigate the systemic risks of hedge funds, Table 10 compares movements in trading strategies for all hedge funds relative to the other assets categories. The results show that the returns all hedge fund trading strategies are more widely correlated with High yield, S&P GSCI Commodity, and REIT market indexes and are less correlated with the ML Treasury index. Intuitively, the incidence of correlation between these trading strategies and the former indexes as opposed to the latter may be due to the over risk exposure of these markets. It is interesting to note, while the significance level is quite high the levels of correlations between these strategies and market returns are usually moderate to low. In particular, the highest level of correlation with any index for the largest trading strategy, Funds of funds, is 0.53 with the S&P GSCI Commodity index, and the level of correlation with the S&P 500 Composite index is only 0.19. B. Relationship between the Likelihood of an Abnormal Market Movement and Fund Strategy Our dataset allows us to examine the relationship between selected characteristics of a fund and its likelihood abnormal market movements. To a very limited degree, this analysis provides information about the systemic risks of individual fund strategies. It does not, however, provide information about the more important issue of the likelihood of the collapse of several large or many medium-size hedge funds and the costs such a collapse would impose directly and indirectly on economies. Yet this is an important issue. As Schinasi (2006, p. 191) points out, “…the turbulence surrounding the near- 10
  11. 11. collapse of LTCM in the autumn of 1998 posed the risk of systemic consequence for international financial system and seems to have created consequence for real economic activity.” This topic clearly merits further study. The concern with the collapse of LTCM is not with the fund itself, rather it is the potential impact or contagion with other funds and possibly other markets. As the correlation tables illustrate there is a direct association between returns for different classes of hedges funds and the global markets. These simple correlations, however, are not the not the best measure of dependence when a contagious shock is witnessed (see Embrecht, McNeil, and Strautman, 2002). Therefore, to evaluate the possible existence of contagion among the different trading strategies, we draw mainly on the methodology of Eichengreen, Rose, and Wyplosz (1996), and Boyson, Stahel, and Stulz (2006). For our study, we use logit analysis to focus on extreme negative returns, as measured by a negative move in returns of more the two standard deviations, in broad financial markets and hedge funds to study contagion. The results of our bi-variate logit regressions are reported in Table 17. These results show that, in general, when the hedge funds witness extreme movements the broad market indexes typically have a higher probability of witnessing an extreme movement in returns as well. More notably, only the ML treasury index and the ML corporate bond index are the only markets are not seemingly influenced by most trading strategies. In terms of individual strategies, there are some notable relations. For example, the performance of the funds of funds strategy, which has the largest number of hedge funds and assets, is significantly related to downturns in all financial markets. The country-specific strategy intuitively only relates to the performance of the MSCI world and MSCI emerging markets indexes. Lastly, the emerging markets strategy seemingly only relates to the high yield financial markets. IV. Conclusions The hedge fund industry has grown rapidly in recent years, in both number and assets. Such funds represent an important alternative investment vehicle for wealthier and financially sophisticated investors. They also help improve the allocation of resources by seeking out exploitable inefficiencies in firms and markets throughout the world. Hedge 11
  12. 12. fund returns have been relatively high over the years, but so too have been the risks. Indeed, the returns for some funds over the time periods examined have not compensated for their risk, compared to other hedge funds employing different strategies. Thus, investors face different risk-return tradeoffs when investing in funds employing different strategies. This, of course, should not a cause for alarm, given the sophistication of investors and lenders putting money into hedge funds. The fundamental cause for concern about hedge funds is the degree to which they pose a systemic risk to the stability of financial markets and economic activity. No one knows the exact magnitude of this risk. Yet to the degree the industry has operated for years without causing serious disruptions in markets and economies, there would appear to be no need for introducing governmental regulation at this time. After all, investors can always show their displeasure by withdrawing their funds. And the banks lending to such funds, as well as the brokerages and accounting firms servicing them, can take appropriate action to impose greater market discipline on funds they suspect are taking on too much risk. The bottom line, in other words, is let investors beware. 12
  13. 13. IV. References Adams, Charles (2005). “Hedge Funds and Financial Market Dynamics: Some Perspectives From the Asian Experience,” Working Paper prepared for Nanyang Technological University, Singapore. Agarwal, Vikas and Narayan Y. Naik (2000). “Multi-Period Performance Persistence Analysis of Hedge Funds,” The Journal of Financial and Quantitative Analysis, Vol. 35, No. 3. (Sept., 2000), pp. 327–342. Agarwal, Vikas and Narayan Y. Naik (2000). “Performance Evaluation of Hedge Funds with Option-based and Buy-and-Hold Strategies,” Working Paper (August 2000) EFA 0373; FA Working Paper No. 300. Available at SSRN: http://ssrn.com/abstract=238708. Agarwal, Vikas and Narayan Y. Naik (2004). “Risks and Portfolio Decisions Involving Hedge Funds,” The Review of Financial studies, Vol. 17, No. 1. 2004. pp. 63–98. Brealey, Richard A. and Evi Kaplanis (2001). “Hedge Funds and Financial Stability: An Analysis of their Factor Exposures,” International Finance ,Vol. 4, No. 2. (2001), pp. 161–187. Brown, Stephen J., William N. Goetzmann, and James M. Park (1998). “Hedge Funds and the Asian Currency Crisis of 1997,” Yale School of Management Working Paper No. F-58 (May 13, 1998). Available at SSRN: http://ssrn.com/abstract=58650. Brown, Stephen J., William N. Goetzmann, and Roger G. Ibbotson (1999). “Offshore Hedge Funds: Survival and Performance,” The Journal of Business ,Vol. 72, No. 1. (Jan. 1999), pp. 91–117. Chan, Nicholas, Mila Getmansky, Shane Haas, and Andrew W. Lo (2005). “Systemic Risk and Hedge Funds,” National Bureau of Economic Research (NBER) Working Paper No. 11200. Danielson, Jon, Ashley Taylor and Jean-Pierre Zigrand (2005). “Highwaymen or Heroes: Should Hedge Funds be Regulated?,” Journal of Financial Stability, Vol. 1, No. 4, pp. 522–543. Donaldson, William H. (2003). “The Long and Short of Hedge Funds: Effects of Strategies for Managing Market Risks,” Working Paper prepared for the Financial Services Subcommittee on Capital Markets, Insurance and Government Sponsored Enterprises, United States House of Representatives. Edwards, Franklin R. and Mustafa O. Caglayan (2000). “Hedge Funds and Commodity Fund Investment Styles in Bull and Bear Markets,” Journal of Portfolio Management, Vol. 27, No. 4, (2001), pp. 97–108. Edwards, Franklin R. (2003). “The Regulations of Hedge Funds: Financial Stability and Investor Protection,” Working Paper prepared for the Conference on Hedge Funds Institute for Law and Finance / Deutsches Aktieninstitute. V. Johann Wolfgang Goethe-Univsersitat Frankfurt, May 22, 2003. Eichengreen, Barry (1999). “The Regulator’s Dilemma: Hedge Funds in the International Financial Architecture,” International Finance, Vol. 2, No. 3. (1999), pp. 411–440. Eichengreen, Barry and Donald Mathieson (1999). “Hedge Funds: What Do We Really Know?” 1999 International Monetary Fund, September 1999. Financial Services Authority of UK (2005). “Hedge Funds: A Discussion of Risk and Regulatory Engagement,” Financial Services Authority of UK, Discussion Paper, June 2005. Fung, William and David A.Hsieh (1999). “A Primer on Hedge Funds,”Journal of Empirical Finance, Vol.6, (1999), pp. 309–331. 13
  14. 14. Fung, William and David A. Hsieh (2000). “Measuring the Market Impact of Hedge Funds,” Journal of Empirical Finance, Vol. 7, (2000), pp. 1–36. Fung, William, David A. Hsieh, and Konstantinos Tsatsaronis (2000). “Do Hedge Funds Disrupt Emerging Markets?” Brookings-Wharton Papers on Financial Services: 2000. Garbaravicius, Tomas and Frank Dierick (2005). “Hedge Funds and Their Implications for Financial Stability,” European Central Bank, Occasional Paper Series No. 34, August 2005. Geithner, Timothy F. (2006). “Hedge Funds and Derivatives and Their Implications for the Financial System,” Speech, Federal Reserve Bank of New York, September 15, 2006, http://www.ny.frb.org/newsevents/speeches/2006/gei060914.html Getmansky, Mila (2005). “The Life Cycle of Hedge Funds: Fund Flows, Size and Performance,” Working Paper, January 2, 2005, http://ssrn.com/abstract=676742. Greenspan, Alan (2005). Remarks by Chairman Alan Greenspan, “Risk Transfer and Financial Stability,” the Federal Reserve Bank of Chicago’s Forty-first Annual Conference on Bank Structure, Chicago, Illinois, May 5, 2005. Kaminsky, Graciela L., Richard K. Lyons, and Sergio L. Schmukler (2001). “Mutual Fund Investment in Emerging Markets: An Overview,” The World Bank Economic Review, Vol. 15, No. 2. (2001), pp. 315–340. Kat, Harry (2003). “10 Things That Investors Should Know About Hedge Funds,” The Journal of Wealth Management, Spring 2003, pp. 72–81. Kim, Woochan and Shang-Jin Wei (2002). “Foreign Portfolio Investors Before and During A Crisis,” Journal of International Economics, Vol. 56, (2002), pp. 77–96. Lhabitant, Francois L. (2004). “Hedge Funds Investing: A Quantitative Look Inside the Black Box,” working paper, EDHEC Risk and Asset Management Research Center, EDHEC Business School, April 2004. Liang, Bing (2000). “Hedge Funds: The Living and the Dead,” The Journal of Financial and Quantitative Analysis, Vol. 35, No. 3. (Sept., 2000), pp. 309–326. Lo, Andrew (2001). “Risk Management For Hedge Funds: Introduction and Overview,” Financial Analysts Journal, Vol. 57, No. 6, (November/December 2001). Lumpkin, Stephen and Hans J. Blommestein (1999). “Hedge Funds, Highly Leveraged Investment Strategies and Financial Markets,” Financial Market Trends, No. 73. (June 1999), pp. 27–50. Malkiel, Burton G. and Atanu Saha (2005). “Hedge Funds: Risk and Return,” Financial Analyst Journal, Vol. 61, No. 6. (2005), pp. 80–88. Merrick Jr., John J., Narayan Y. Naik, and Pradeep K. Yadav (2002). “Strategic Trading Behavior and Price Distortion in a Manipulated Market: Anatomy of a Squeeze,” Journal of Financial Economics, Vol. 77, No. 1, (2005), pp. 171–218. Napoli Jr., Michael J. (2004). “The Rationale for Hedge Fund Investments, Hedge Fund Styles and Asset Allocation Issues,” working paper, Hedge Funds Group, Wilshire Research, April 26, 2004. Napoli Jr., Michael J. (2004). “The Risks of Hedge Fund Investments,” working paper, Hedge Funds Group, Wilshire Research, October 26, 2004. Post, Mitchell A. and Kimberlee Millar (1998). “U.S. Emerging Market Equity Funds and the 1997 Crisis in Asian Financial Markets,” Perspective, Investment Company Institute, Vol. 4, No. 2. (June 1998). 14
  15. 15. Schinasi, Garry J. (2005), “Safeguarding Financial Stability: Theory and Practice,” Washington D.C.: International Monetary Fund, 2005. Ubide, Angel (2006). “Demystifying Hedge Funds,” IMF, Vol. 43, No. 2. (June 2006). Yam, Joseph CK (1999). “Capital Flows, Hedge Funds and Market Failure: A Hong Kong Perspective,” Working Paper prepared for Reserve Bank of Australia 1999 Conference, “Capital Flows and the International System,” August 9–10, 1999. 15
  16. 16. Table 1: Global, U.S. and Europe Financial System, 2006 US$ Billions World U.S. Europe Rest of the World GDP 48,144 13,245 16,055 18,844 Bank Assets 77,436 13,898 35,541 27,997 Stock Market Capitalization 54,195 19,426 15,461 19,308 Bond Outstanding 68,147 26,736 24,612 16,799 Currency Derivatives (Notional Amount) 257 169 3 85 Interest Rate Derivatives (Notional Amount) 62,652 37,921 20,562 4,169 Mutual Funds 21,765 10,414 7,734 3,617 Hedge Funds 1,138 579 468 91 Sources: IMF, Emerging Market Fact Book 2007, the Bank for International Settlements, ICI . 16
  17. 17. Figure 1: Numbers, Assets and Returns of All Hedge Funds, January 1980 to May 2007 Numbers 10,000 8,000 6,000 4,000 2,000 0 81 82 85 88 92 99 04 80 83 84 86 87 89 90 91 93 94 95 96 97 98 00 01 02 03 05 06 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja US$ Billions Assets 1,400 1,200 1,000 800 600 400 200 0 84 93 00 02 80 81 82 83 85 86 87 88 89 90 91 92 94 95 96 97 98 99 01 03 04 05 06 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Average Monthly Returns Percent 15 10 5 0 -5 -10 -15 82 83 85 86 88 89 92 06 80 81 84 87 90 91 93 94 95 96 97 98 99 00 01 02 03 04 05 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Table 2: Numbers, Assets, Standard Deviation of Assets, Returns, Standard Deviation of Returns Across and Across Funds of All Hedge Funds, 1990 to May 2007 May 199 199 199 199 199 199 2007 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 0 1 2 3 4 5 , YTD 1,15 1,57 2,10 2,82 3,37 3,99 4,83 5,70 6,75 7,39 7,29 7,14 Number 146 218 312 437 587 842 8 2 6 6 6 7 7 5 1 3 5 4 Total Fund Assets (US$ 1,13 1,23 5 8 10 17 20 26 37 61 81 144 176 247 293 518 717 884 Billions) 8 2 Average Fund Assets 34 35 31 40 34 31 32 39 38 51 52 62 61 91 106 120 156 172 (US$ Millions) Standard Deviation of Fund Assets (US$ 146 127 121 124 142 119 103 111 125 224 192 235 209 263 307 300 386 497 Millions) Average Monthly 1.15 1.90 1.23 2.17 0.41 1.78 1.79 1.64 0.73 2.39 1.05 0.65 0.30 1.33 0.70 0.74 0.94 0.59 Returns (Percent) Standard Deviation of Monthly Return Across 0.76 0.74 0.59 0.68 0.71 0.69 0.71 0.77 1.01 1.09 1.20 0.80 0.62 0.52 0.43 0.41 0.41 0.37 Funds (Percent) 12-Month Standard Deviation of All Fund 0.92 1.88 0.79 0.92 0.83 1.11 1.49 1.93 2.32 2.15 2.38 1.24 0.86 0.87 1.13 1.26 1.33 0.54 Monthly Return (Percent) 17
  18. 18. Figure 2: Numbers, Assets and Returns of Non-Fund-of-Fund Hedge Funds, January 1980 to May 2007 Numbers 6,000 5,000 4,000 3,000 2,000 1,000 0 80 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 99 00 01 03 04 06 07 81 82 98 02 05 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja US$ Billions Assets 1,000 800 600 400 200 0 92 80 81 82 3 4 85 6 7 88 9 90 91 93 94 95 96 97 98 9 00 1 2 03 4 5 06 07 -8 -8 -8 -8 -8 -9 -0 -0 -0 -0 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n n n n n n n n n n Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Average Monthly Returns Percent 20 15 10 5 0 -5 -10 -15 80 81 82 84 85 87 88 89 90 91 93 94 96 97 98 99 00 01 02 03 06 07 83 86 92 95 04 05 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Table 3: Numbers, Assets, Standard Deviation of Assets, Returns, Standard Deviation of Returns Across and Across Funds of Non-Fund-of-Fund Hedge Funds, 1990 to May 2007 May 199 199 199 199 199 199 199 2007 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 0 1 2 3 4 5 6 , YTD 1,21 1,63 2,18 2,55 2,92 3,42 3,92 4,53 4,93 4,80 4,79 Number 115 169 241 343 455 643 881 0 2 3 3 8 4 7 4 3 8 0 Assets (US$ Billions) 5 7 8 13 15 20 30 50 68 125 148 201 225 366 516 614 784 866 Average Fund Assets 40 41 34 37 33 32 34 41 42 57 58 68 66 93 114 124 163 181 (US$ Millions) Standard Deviation of Fund Assets (US$ 162 142 136 130 133 115 98 109 125 246 208 259 226 225 273 302 402 534 Millions) Average Monthly 1.32 2.18 1.32 2.21 0.58 2.06 1.93 1.77 0.89 2.54 1.13 0.75 0.35 1.52 0.79 0.87 1.07 0.62 Returns (Percent) Standard Deviation of Monthly Return Across 0.91 0.87 0.69 0.77 0.79 0.78 0.81 0.88 1.14 1.23 1.36 0.92 0.72 0.61 0.50 0.49 0.49 0.45 Funds (Percent) 12-Month Standard Deviation of All Fund 1.00 2.36 1.02 0.93 0.75 1.23 1.61 2.06 2.46 2.33 2.60 1.43 0.98 1.03 1.23 1.33 1.40 0.56 Monthly Return (Percent) 18
  19. 19. Figure 3: Numbers, Assets and Returns of Fund of Hedge Funds, January 1980 to May 2007 Numbers 3,000 2,500 2,000 1,500 1,000 500 0 84 80 81 82 83 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja US$ Billions Fund of Funds 600 400 200 0 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Average Monthly Returns Percent 15 10 5 0 -5 -10 -15 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- n- Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Ja Table 4: Numbers, Assets, Standard Deviation of Assets, Returns, Standard Deviation of Returns Across and Across Funds of Fund of Hedge Funds, 1990 to May 2007 May 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007, YTD Number 29 46 67 90 128 194 272 357 465 635 817 1,063 1,410 1,775 2,215 2,460 2,487 2,354 Assets (US$ Billions) 0 1 2 5 5 6 8 13 17 25 37 58 81 170 230 308 396 407 Average Fund Assets 14 16 24 54 40 33 31 35 36 39 45 54 58 96 104 125 159 173 (US$ Millions) Standard Deviation of Fund Assets (US$ 41 37 48 98 175 131 120 118 127 117 124 144 151 310 349 295 352 412 Millions) Average Monthly 0.96 1.08 1.00 2.07 -0.08 1.05 1.49 1.38 0.35 2.03 0.88 0.44 0.21 0.99 0.56 0.58 0.77 1.18 Returns (Percent) Standard Deviation of Monthly Return Across 0.44 0.35 0.32 0.36 0.44 0.37 0.38 0.37 0.57 0.56 0.66 0.40 0.33 0.28 0.24 0.21 0.18 0.15 Funds (Percent) 12-Month Standard Deviation of All Fund 0.66 0.72 0.79 1.10 1.17 0.96 1.22 1.58 2.07 1.70 1.85 0.75 0.62 0.61 1.03 1.20 1.30 0.54 Monthly Return (Percent) 19
  20. 20. Figure 4: Risk and Returns by Fund Strategies Average Monthly Returns, June 1997 to May 2007 3.0 2.5 2.0 1.5 y = 0.1523x + 0.721 R2 = 0.4892 1.0 0.5 0.0 0 2 4 6 8 10 12 Standard Deviation of Monthly Returns 20
  21. 21. Table 5: Number of Fund by Domicile and Location of Assets, May 2007 Asset Location Total Number by Australia/ North South United Domicile Africa Asia Oceania Europe America America States Global Country Anguilla 0 0 0 0 0 0 0 1 1 Argentina 0 0 0 0 0 4 0 1 5 Australia 0 19 35 0 0 0 4 29 87 Austria 0 0 0 1 0 0 2 27 30 Bahamas 1 1 0 6 0 4 7 29 48 Barbados 0 0 0 0 0 0 0 3 3 Belgium 0 0 0 0 0 0 0 1 1 Bermuda 6 25 0 29 1 0 35 84 180 Brazil 0 0 0 0 0 53 0 16 69 British Virgin Islands 1 0 0 1 0 0 3 32 37 Canada 0 7 0 1 50 0 6 55 119 Cayman Islands, BWI 0 12 0 41 2 4 17 65 141 Channel Islands 0 12 0 4 2 0 3 50 71 Chile 0 0 0 0 0 1 0 0 1 China 0 7 0 0 0 0 1 2 10 Cyprus 0 0 1 1 0 0 0 0 2 Czech Republic 0 0 0 0 0 0 0 1 1 Denmark 0 0 0 2 0 0 0 0 2 Finland 0 0 0 3 0 0 0 4 7 France 0 1 0 20 0 0 13 118 152 Germany 0 0 0 3 0 0 2 16 21 Gibraltar 1 1 0 3 0 0 5 8 18 Greece 0 0 0 0 0 0 0 3 3 Grenada 0 0 0 0 0 0 0 2 2 Hong Kong 0 65 0 6 0 1 0 14 86 India 0 2 0 0 0 0 0 0 2 Indonesia 0 1 0 0 0 0 0 0 1 Ireland 0 0 0 3 0 0 3 19 25 Domicle Country Isle Of Man 0 0 0 0 0 0 1 2 3 Israel 0 1 0 0 0 0 0 0 1 Italy 0 2 0 27 0 0 2 53 84 Japan 0 17 0 0 0 0 0 1 18 Kuwait 0 1 0 1 0 0 5 0 7 Lebanon 0 0 0 0 0 0 0 3 3 Liechtenstein 0 0 0 0 0 0 0 2 2 Luxembourg 0 2 0 8 0 0 3 45 58 Malaysia 0 2 0 0 0 0 0 2 4 Malta 0 0 0 0 0 0 0 1 1 Mauritius 0 3 0 0 0 0 0 0 3 Mexico 0 0 0 0 0 1 0 0 1 Monaco 0 0 0 1 0 0 0 10 11 Netherland Antilles 0 0 0 1 0 0 0 4 5 Netherlands 1 1 0 11 0 0 0 20 33 New Zealand 0 0 0 0 0 0 0 13 13 Norway 0 0 0 5 0 0 0 14 19 Panama 0 0 0 0 0 0 0 3 3 Russia 0 0 0 16 0 0 0 1 17 Singapore 2 62 1 1 0 0 0 9 75 South Africa 17 0 0 0 0 0 1 13 31 Spain 0 1 0 3 0 0 0 8 12 St. Vincent & The Gren. 0 0 0 0 0 0 0 1 1 Sweden 0 0 0 16 0 0 0 18 34 Switzerland 0 33 0 50 2 3 37 419 544 Taiwan 0 0 0 0 0 0 0 3 3 Thailand 0 1 0 0 0 0 0 0 1 Turkey 0 0 0 0 0 0 0 1 1 Ukraine 0 0 0 1 0 0 0 0 1 United Arab Emirates 2 7 0 0 0 0 0 14 23 United Kingdom 4 175 0 320 3 3 56 874 1,435 US Virgin Islands 0 0 0 0 0 0 18 17 35 USA 2 140 1 70 36 8 1750 1521 3,528 Total Number by Location 37 601 38 655 96 82 1974 3652 7,135 21
  22. 22. Table 6: Assets of Hedge Fund by Domicile and Location of Assets, May 2007 Asset Location Total Asset by Australia/ North South United Domicile Africa Asia Oceania Europe America America States Global Country Anguilla 0 0 0 0 0 0 0 44 44 Argentina 0 0 0 0 0 348 0 10 358 Australia 0 4,159 2,339 0 0 0 910 4,549 11,957 Austria 0 0 0 0 0 0 54 1,813 1,867 Bahamas 257 50 0 911 0 532 168 1,518 3,436 Barbados 0 0 0 0 0 0 0 77 77 Belgium 0 0 0 0 0 0 0 129 129 Bermuda 26 1,389 0 3,856 4 0 6,311 10,414 22,000 Brazil 0 0 0 0 0 4,370 0 4,304 8,674 British Virgin Islands 9 0 0 14 0 0 164 3,480 3,667 Canada 0 173 0 17 2,903 0 260 9,950 13,303 Cayman Islands, BWI 0 1,814 0 3,958 47 410 2,256 11,886 20,371 Channel Islands 0 2,579 0 286 52 0 196 4,760 7,872 Chile 0 0 0 0 0 44 0 0 44 China 0 2,155 0 0 0 0 30 86 2,271 Cyprus 0 0 62 37 0 0 0 0 99 Czech Republic 0 0 0 0 0 0 0 24 24 Denmark 0 0 0 71 0 0 0 0 71 Finland 0 0 0 67 0 0 0 1,130 1,197 France 0 65 0 4,528 0 0 3,378 44,527 52,498 Germany 0 0 0 45 0 0 98 509 652 Gibraltar 10 2 0 652 0 0 3,045 306 4,015 Greece 0 0 0 0 0 0 0 3 3 Grenada 0 0 0 0 0 0 0 11 11 Hong Kong 0 6,713 0 0 0 11 0 477 7,201 India 0 66 0 0 0 0 0 0 66 Indonesia 0 5 0 0 0 0 0 0 5 Ireland 0 0 0 229 0 0 677 2,991 3,897 Domicle Country Isle Of Man 0 0 0 0 0 0 12 84 96 Israel 0 0 0 0 0 0 0 0 0 Italy 0 174 0 5,508 0 0 79 8,077 13,839 Japan 0 2,854 0 0 0 0 0 20 2,874 Kuwait 0 0 0 0 0 0 52 0 52 Lebanon 0 0 0 0 0 0 0 303 303 Liechtenstein 0 0 0 0 0 0 0 27 27 Luxembourg 0 275 0 1,628 0 0 308 4,510 6,720 Malaysia 0 95 0 0 0 0 0 17 113 Malta 0 0 0 0 0 0 0 4 4 Mauritius 0 228 0 0 0 0 0 0 228 Mexico 0 0 0 0 0 100 0 0 100 Monaco 0 0 0 219 0 0 0 1,527 1,746 Netherland Antilles 0 0 0 51 0 0 0 227 278 Netherlands 41 27 0 854 0 0 0 3,769 4,691 New Zealand 0 0 0 0 0 0 0 45 45 Norway 0 0 0 2,060 0 0 0 809 2,869 Panama 0 0 0 0 0 0 0 157 157 Russia 0 0 0 1,485 0 0 0 279 1,764 Singapore 232 7,381 4 22 0 0 0 362 8,001 South Africa 1,390 0 0 0 0 0 0 40 1,431 Spain 0 0 0 85 0 0 0 415 500 St. Vincent & The Gren. 0 0 0 0 0 0 0 21 21 Sweden 0 0 0 1,317 0 0 0 5,295 6,612 Switzerland 0 3,075 0 8,842 70 561 12,827 56,753 82,129 Taiwan 0 0 0 0 0 0 0 32 32 Thailand 0 285 0 0 0 0 0 0 285 Turkey 0 0 0 0 0 0 0 176 176 Ukraine 0 0 0 75 0 0 0 0 75 United Arab Emirates 7 447 0 0 0 0 0 359 813 United Kingdom 293 19,375 0 89,853 106 46 14,700 164,323 288,695 US Virgin Islands 0 0 0 0 0 0 2,544 1,444 3,988 USA 42 16,215 16 14,487 2,970 368 295,798 302,208 632,104 Total Asset by Location 2,308 69,601 2,421 141,158 6,152 6,789 343,867 654,278 1,226,575 22
  23. 23. Table 7: Definition, First Appeared Month, and Last Appeared Month of Hedge Fund Strategies Date First Date Last Appeared in Appeared the in the Stategy Definition Database Database Aggressive Growth Jan-86 Jan-06 Asset Based Lending Apr-89 Current Capital Structure Arbitrage Jan-95 Current Convertible Arbitrage Jan-84 Current Country Specific Jun-92 Current CTA/Managed Futures Apr-74 Current Distressed Oct-89 Current Emerging Markets Jan-85 Current Energy Sector Oct-92 Current Event Driven Dec-86 Current Finance Sector Jan-90 Current Fixed Income (non-arbitrage) Jun-89 Current Fixed Income Arbitrage Aug-76 Current Fund of Funds Jan-80 Current Healthcare Sector Nov-89 Current Long Only Nov-83 Current Long/Short Equity Jan-83 Current Macro Jan-87 Current Market Neutral Equity Jan-87 Current Market Timer Jan-86 Current Merger/Risk Arbitrage Feb-85 Current Mortgages Feb-95 Current Multi-Strategy Jan-76 Current Opportunistic Jun-93 Dec-05 Options Arbitrage Jan-98 May-04 Options Strategies Apr-93 Current Other Arbitrage May-83 Current Regulation D Mar-95 Current Short Bias Apr-85 Current Short-term Trading Jan-90 Current Small/Micro Cap May-85 Current Special Situations Oct-88 Current Statistical Arbitrage Feb-89 Current Technology Sector Oct-91 Current Value Oct-79 Current VC / Private Equity Jan-98 Sep-05 23
  24. 24. Table 8: Number, Size, Returns Characteristics of Hedge Fund by Strategies Annual Annual Standard Number Asset Average Standard Deviation of Growth Growth Monthly Deviation of Returns Rate, June Rate, June Returns, Returns, amoung funds Number, 1997 to May Assets, May 1997 to May June 1997 to June 1997 to with same May 2007 2007 2007 1997 May 2007 May 2007 strategies Aggressive Growth 0 N/A 0 N/A 0.97 2.19 5.57 Asset Based Lending 28 39.55 4,469 108.34 1.25 2.39 4.75 Capital Structure Arbitrage 16 23.11 1,821 68.28 0.34 3.42 4.84 Convertible Arbitrage 114 11.04 17,721 36.66 1.09 3.42 5.27 Country Specific 152 26.93 14,820 33.80 0.98 2.67 4.22 CTA/Managed Futures 483 12.48 64,714 20.39 1.03 1.71 3.81 Distressed 129 19.35 48,284 58.93 0.96 5.39 6.98 Emerging Markets 203 17.06 39,146 32.32 0.89 1.85 4.60 Energy Sector 71 28.03 13,304 81.01 1.35 4.30 7.02 Event Driven 185 16.85 45,133 36.64 1.42 3.76 5.27 Finance Sector 46 14.38 3,890 23.66 1.00 1.62 3.60 Fixed Income (non-arbitrage) 190 17.16 50,767 54.09 0.82 1.10 2.03 Fixed Income Arbitrage 138 15.74 33,386 25.26 2.71 10.48 8.39 Fund of Funds 2,354 22.12 407,388 44.86 1.13 3.01 4.58 Healthcare Sector 48 12.33 4,159 31.31 1.39 3.03 4.97 Long Only 101 14.98 12,375 34.68 2.12 1.96 3.86 Long/Short Equity 1,460 18.79 208,505 42.33 0.81 1.39 2.61 Macro 235 17.97 36,858 44.30 0.79 1.62 2.61 Market Neutral 257 18.77 39,454 34.67 0.90 1.02 2.79 Market Timer 7 -9.01 175 4.35 0.80 1.35 2.22 Merger/Risk Arbitrage 43 8.51 4,839 33.74 1.67 5.70 7.85 Mortgages 21 21.48 1,709 19.57 1.28 3.75 5.35 Multi-Strategy 381 22.27 131,020 51.30 1.03 1.62 4.71 Opportunistic 0 N/A 0 N/A 0.84 1.09 3.71 Options Arbitrage 0 N/A 0 N/A 0.86 1.07 2.59 Options Strategies 69 27.66 5,132 53.98 0.96 1.31 3.37 Other 28 3.95 2,225 18.64 0.87 0.99 3.26 Regulation D 31 10.92 3,897 30.45 0.80 0.98 2.96 Short Bias 25 3.34 707 5.02 1.46 2.54 3.28 Short-term Trading 18 7.18 1,615 51.71 0.83 1.33 2.50 Small/Micro Cap 90 13.22 7,768 33.21 1.16 1.07 2.00 Special Situations 47 27.94 9,350 62.55 0.98 1.37 3.98 Statistical Arbitrage 35 12.27 6,323 34.96 0.74 1.63 3.24 Technology Sector 32 3.82 3,259 19.57 1.23 1.48 4.50 Value 107 11.20 7,628 33.64 0.80 1.06 3.03 VC / Private Equity 0 N/A 0 N/A 1.34 4.62 5.69 Total 7,144 17.81 1,231,841 38.59 1.10 2.48 4.22 24

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