What Do We Know about the Performance and Risk of Hedge Funds? Triphon Phumiwasana, Tong Li, James R. Barth and Glenn Yago *

Transcription

1 What Do We Know about the Performance and Risk of Hedge Funds? Triphon Phumiwasana, Tong Li, James R. Barth and Glenn Yago * Introduction A front-page story in September of 2006 was the unraveling of the hedge fund Amarath Advisors. Its assets fell by a reported 65 percent in a month and 55 percent, or $6 billion, for the year. The back-page story was that financial markets barely reacted to this shocking development. This was in sharp contrast to the near-collapse of Long-Term Capital Management (LTCM) in Despite the lack of a broader market reaction, the rapid and huge losses suffered by Amarath raise serious issues about the performance and risk of hedge funds more generally. The purpose of our paper is to use a comprehensive data source on hedge funds to examine the performance and risk of these funds. Mutual funds, unlike hedge funds, are widely available to the public and therefore must be registered with the Securities and Exchange Commission. They are, moreover, 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. Furthermore, although the word hedge typically 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 employ strategies that do not involve hedging as more commonly understood. Indeed, many funds do just the opposite, which explains the collapse of Amarath and LTCM. The paper will therefore examine some of the different strategies employed by hedge funds, assess whether there are any differences among them in terms of performance and risk, and examine some of the factors that help explain why some funds remain in the industry and others exit. Several previous studies have addressed the implications of hedge funds for financial stability. But the results of these efforts thus far have been less successful than one might hope. For instance, in a recent study that attempts 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 that It is very difficult to provide any conclusive evidence on the impact of hedge funds on financial markets. Moreover, as regards regulation, Timothy Geithner (2006, p.8), President of the Federal Reserve Bank of New York, states that Clearly, capital supervision and market discipline remain the key tools for limiting systemic risk. The emergence of new market participants such as leverage institutions does not change that. In addition, Danielsson, Taylor and Zigrand (2005, pp ) while arguing that there is a need for a credible resolution mechanism to deal with the default of systemically important hedge funds 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 impressive efforts of well-recognized experts, we have decided not to try to expand and improve upon this line of enquiry in the present paper. * Triphon Phumiwasana (ephumiwasana@milkeninstitute.org), and Tong Li (cli@milkeninstitute.org) are Economists at the Milken Institute; James R. Barth (jbarth@milkeninstitute.org) is a Lowder Eminent Scholar in Finance at Auburn University and Senior Fellow at the Milken Institute; Glenn Yago (gyago@milkeninstitute.org) is Director of Capital Studies at the Milken Institute. This is a shorter version of a longer paper that is available upon request from the authors. An earlier version of this paper was presented at Conference on International Financial Instability: Cross-Border Banking and National Regulation, Federal Reserve Bank of Chicago, Chicago, IL, October 5-6,

2 What we do instead in this paper is provide a comprehensive and detailed examination of many important aspects of the hedge fund industry. This examination is based on a dataset assembled by HedgeFund.net. As Table 1 shows, there are several sources of hedge fund data with differing coverage features. HedgeFund.net provides information on the most funds and the most assets. It starts with 8 hedge funds with $57 million in assets in 1981 and grows to 6,445 funds with $969 billion in assets as of June We are able to use this dataset to examine differences in important characteristics of hedge funds both over time and by the type of strategy that funds choose to employ. We pay particular attention to the changes in the performance and risk of funds over time as well as assess whether there are differences in these dimensions based upon the strategies they employ. Also, we use regression analyses to examine the association between various characteristics of a fund and its performance and risk, and to examine the association between various characteristics and the likelihood that a fund will remain alive or enter the graveyard. An Overview of the Hedge Fund Industry Growth and Size The recent flurry of news stories about hedge funds might lead some to think that such funds are a relatively new development. However, Fung and Hsieh (1999) report that the first hedge fund was actually formed in It employed a long/short equity strategy and operated on the basis of leverage, which describes the strategies of many hedge funds today. They point out that the fund was relatively unknown until a magazine article in 1966 drew attention to its high return compared to the returns of mutual funds. The number of hedge funds subsequently grew fairly rapidly for a few years before suffering losses due to the poor performance in the equity market. According to Fung and Hsieh (1999), the industry rebounded once again when another magazine article in 1986 reported that a newly established hedge fund earned an extraordinary return in the first few months of its existence. The publicizing of high returns thus appears to have been a significant contribution to accelerated growth in the industry during its more formative years. Table 2 documents the growth in the industry over the past quarter of a century. Both in terms of numbers and assets, the industry has experienced continuous and rapid growth, until the decline in the number of funds during the first six months of From 1981 to June 2006 the number of funds grew at a 30 percent average annual rate, while total assets grew at a 47 percent average annual rate. Not all funds, of course, that entered the industry during this time period remained alive until the ending date. Indeed, the two tables show that by June 2006 there were 3,100 funds with $257 billion in assets that had exited the industry. Despite these exits, there were still 6,445 funds remaining with $969 in total assets. Differences in Size, Domicile, Asset Location, and Age of Funds Although there has been growth in both the number and assets of hedge funds, asset growth has exceeded number growth. As a result, the average size of hedge funds has increased by more than 2,000 percent from 1981 to June 2006, to $150 million from $7 million. This occurred despite the fact that the average size of exiting funds is greater than the average size of entering funds. This latter difference reflects the fact that the age of exiting funds is greater than that of the newly entering funds. As regards the distribution in sizes of funds in terms of number and assets, the funds with $1 billion or more in assets account for only 3 percent of the total number of funds, but 35 2

3 percent of total assets. Conversely, those with $100 million or less in assets account for nearly 70 percent of the total number of all funds, but they account for only 12 percent of the total assets. A different perspective of the hedge fund industry is provided by the domicile (or headquarter location) of hedge funds and the location of the assets of hedge funds. Of the 6,445 funds as of June 2006, slightly more than 50 percent 3,354 are domiciled in the United States, and of these about half have their assets located in the United States, with nearly all the remaining assets allocated globally. Europe is second to the United States in terms of number of domiciled funds, accounting for approximately 33 percent 2,153 of the total number of funds, and of these only about 20 percent have their assets located in Europe. The majority of the funds, 64 percent, have allocated their assets globally. The funds domiciled in the United States account for the largest amount of assets, $503 billion, with those in Europe second with $371 billion. Together these regions account for slightly more than 90 percent of the $969 billion in total fund assets. For funds domiciled in the United States, 52 percent and 43 percent are allocated to the United States and globally, respectively, In contrast, for funds dominated in Europe 22 and 63 percent are allocated to Europe and globally, respectively. The European domiciled funds, moreover, allocate more assets to Asia in terms of both absolute amount and as a share of their total assets compared to funds domiciled in the United States. As regards the degree of concentration of assets within the hedge fund industry, the top 1 percent of funds control 19 percent of all fund assets, the top 5 percent control 47 percent, and the top 10 percent control 63 percent. However, there is wide variation in concentration ratios with respect to the location of fund assets. The top 1 percent of funds with assets located in South America, for example, account for 58 percent of all assets located in South America and the top 1 percent of funds with assets located in Africa account for 46 percent of all assets located in Africa. Similarly, there are substantial differences in the concentration ratios with respect to where the funds are domiciled. The top 1 percent of funds domiciled in Africa and the Middle East account for 72 percent of all assets of funds domiciled in the region. In Europe and the United States, however, the concentration ratios are relatively low at 18 percent in both cases because so many funds are domiciled in these places. The last comment to be made in this section concerns the average age of hedge funds. Not surprisingly, the average age of a fund has increased since As of June 2006, the typical fund had been in existence 5.3 years. Hedge Fund Strategies Hedge funds not only come in a variety of sizes, asset locations, and domiciles, but also in a variety of strategies. Our dataset lists 42 different strategies for the hedge funds being examined, including other and unknown. These 42 strategies, in turn, are collapsed into 12 strategies, including other and unknown. It is these strategies, after combining other and unknown into a single strategy, we examine next. 1 Table 3 contains information on the relative importance of the different strategies in terms of each strategy s share of the total number and assets of hedge funds. The two most important strategies employed are the fund-of-funds-multi-strategy and the long/short-equitystrategy, with 25 and 20 percent of all funds employing these two strategies, respectively. The funds employing these two strategies also account for 30 and 17 percent of the total assets of funds, respectively. 3

4 It is also interesting to note the changing relative importance in strategies employed by hedge funds over time. The commodity trading advisor and directional funds accounted for the larger shares of number and assets in the 1980s, but those shares declined sharply thereafter. At the same time, they were replaced in relative importance by the fund-of-funds-multi-strategy and long/short equity-strategy funds. Table 4 slows that the top 10 percent of the total number of funds for each of the 12 different strategies account for between 50 and 71 percent of the total assets of each of the strategies. The strategy with the lowest degree of concentration is the sector strategy (50 percent), while the one with the highest degree of concentration is the macro strategy (71 percent). Overall, there is little variation in the average ages of funds employing different strategies, with the exception of the funds choosing the commodity trading advisor strategy. Management Fees The management fees of hedge funds attract a lot of attention from not only potential investors but also 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. The funds with only 5 percent of total assets set management fees at 0.75 percent or less. The funds accounting for 55 percent of total assets, however, set fees at 1.25 percent or higher. The 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. The performance incentives of hedge funds clearly attract the most attention. As of June 2006, 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. There appears to be a bimodal distribution of incentive fees in the following sense. Most funds with the most assets either charge less than 10 percent or between 15 and 20 percent. There is roughly a 30 to 50 percent split, in terms of both number and assets, for the funds charging 10 percent or less and those charging between 15 and 20 percent, respectively. The performance incentives, moreover, have tended to drift upwards since the early 1980s despite the tremendous increase in the number and assets of hedge funds. Lock-up Periods In addition to fees, attention is frequently focused on the lock-up periods of hedge funds. When investors initially put their money into such funds, they cannot freely cash out at any time thereafter. Instead, investors are required to remain in the fund over a specified period of time before any withdrawals can take place. The required minimum time period is called the initial lock-up period. Nearly 50 percent of funds have a lock-up period of up to 30 days, with the vast majority of the remaining funds having a lock-up period of up to a year. The distribution of the assets of funds by lock-up period closely parallels that for the number of funds. The data indicate that 49 percent of the assets of all funds are linked to lock-up periods of up to 30 days. Only 2 percent of assets are linked to lock-up periods exceeding a year. Over time, there has been a shift toward longer lock-up periods employed by more funds with more assets. We also examine the lock-up periods employed by funds of different sizes and strategies. There is not much of a difference in lock-up periods employed by funds of varying sizes. However, for funds with different strategies, the lock-up period is shortest for the commodity 4

5 trading adviser funds and longest for the sector funds. In the case of the former, 91 percent of the assets are in the funds with a lock-up period of 30 days or less, whereas in the latter case 61 percent of the assets are in the funds with a lock-up 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 those funds account for 65 percent of total assets. Nearly 40 percent of the funds with 41 percent of 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 one-fourth of all funds with about the same percentage of total assets. Performance and Risk of Hedge Funds The performance and risk of hedge funds understandably attracts the most attention. Table 5 shows the average monthly (annualized) return of hedge funds from 1981 to June 2006 range from a low of 0.4 (4.8 percent) in 1994 to a high of 2.7 (32.4 percent) in There is substantial variation in returns depending upon the strategy that a fund employs. As the table shows, the highest average monthly return was reported by those funds employing a global strategy (11 percent), while the lowest return was reported by those also employing a global strategy (-2.2 percent). The volatility of average monthly returns, as measured by the standard deviation of returns, shows that volatility for all funds has decreased over time, but that it differs widely among funds depending upon the strategy being employed. The most volatile return was reported by those funds employing a macro strategy in 1987, while the lowest volatility was reported by the fund of funds employing multiple strategies in It is also useful to examine the persistence of both positive and negative returns reported by funds. In Tables 6 the number and assets of funds with persistent positive returns over selected time periods are reported. The tables indicate that 1,559 funds with $442 billion in assets, as of June 2006, reported positive returns over the previous consecutive five-year period. In contrast, Tables 7 show similar information for funds reporting negative returns. Only two funds reported consecutive negative returns for any year from 1981 to June This happened in 1999 and the two funds had only $16 million in assets. However, as of June 2006, there were 1,128 funds with $104 billion in assets that reported negative returns in the previous year. As regards the risk-return trade-offs for hedge funds grouped on the basis of strategy, there is a significantly positive relationship on average between return and risk. Still, some of the strategies employed by funds have underperformed compared to others in terms of generating a return that compensates for the associated risk. This is the case for several strategies when examining the trade-offs both for the most recent five-year period and the past year, but especially so in the latter case. We also compare the annualized return on hedge funds to the rate on one-year U.S. Treasury securities. The spread between the two returns has tended to narrow over the past 25 years, though the spread differs widely in some years. Moreover, the sixty-month rolling annualized return correlations between the CSFB Tremont Hedge Fund Index and three other indices (namely equity, bond and commodity indices) have tended to increase significantly in recent years, with the exception of the commodity index. This means that rather than being a 5

6 good hedge to stock returns, hedge fund returns have recently tended to move more closely in line with them. Hedge funds have performed comparatively well over various time periods when compared to the performance of major benchmark indices, both using the aggregate return of the funds and the returns for funds employing different strategies. There is, however, a substantial difference in performance depending on the strategies that the funds employ. Furthermore, no single strategy dominates all other strategies over all the time periods examined. Some Statistical Analyses A. Relationship between the Return and Selected Characteristics of a Hedge Fund There are a number of rigorous studies of the performance and risk of hedge funds in recent years (see the selected references). We do not attempt to provide a comparable study here. Instead our goal is a much more modest one to exam the relationship between returns and selected characteristics of hedge funds. We examine the relationship between the risk-adjusted return, non-risk-adjusted return, and standard deviation of non-risk-adjusted returns and selected characteristics of hedge funds. The return regressions show that there is a significantly positive relationship between the riskadjusted return and the asset size of funds. Management fee, performance incentive, length of lock-up period and age of a fund are not related to risk-adjusted return. Furthermore, the positive relationship between risk-adjusted return and asset size appears to be solely due to the negative relationship between the standard deviation of returns and asset size, not the non-risk-adjusted return and size. B. Relationship between the Likelihood of a Fund Being Alive and Its Characteristics Our dataset allows us to examine the relationship between selected characteristics of a fund and its likelihood of being alive. To a very limited degree, this analysis provides information about the risk of individual funds. 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 for as Schinasi (2006, p. 191) points out: the turbulence surrounding the near-collapse of LTCM in the autumn of 1998 posed the risk of systemic consequence for the international financial system, and seemed to have created consequences for real economic activity. To the extent that a similar or worse situation could occur again, this topic clearly merits further study. The results of our logit regressions for the relationship between the likelihood of a fund being alive and selected fund characteristics are reported in Table 8. They indicate the following: The more volatile the return the greater the likelihood of the fund not being alive. The greater the average monthly returns over the period 1997 to 2005, the higher probability of a fund being alive. The likelihood of a fund being alive is greater the bigger the fund and the longer it has been in existence. Management fees and performance incentives are positively associated with the likelihood of a fund being alive. The longer the initial lock-up period the greater the likelihood of a fund being alive. 6

7 Funds domiciled outside of the United States and funds with assets located outside of the United States are associated with a higher probability of being alive, even after controlling for different strategies that fund employ. Conclusions The hedge fund industry has grown rapidly in recent years in terms of both number and assets. Such funds represent an alternative and important investment vehicle for wealthier and more financially sophisticated investors. They also help better allocate resources by seeking out exploitable inefficiencies in firms and markets located throughout the world. The returns of hedge funds have generally been relatively high over the years, but so too have the risks. Indeed, the returns for some funds over the selected time periods examined have not compensated for their risk as compared to other funds employing different strategies. This means investors face different risk-return tradeoffs when investing in funds employing different strategies. This, of course, should not a cause for alarm, given the type 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. The current state of knowledge appears to be that no one knows for sure the exact magnitude of this risk. Yet, to the degree the industry has thus far operated without causing any serious disruptions in markets and economies, there would appear to be no need for introducing new governmental regulation at this time. After all, wealthier and more sophisticated investors can always take action that attracts its displeasure by simply withdrawing their funds. And the banks lending to such funds as well as the brokers and accounting firms servicing them can also take appropriate action to impose greater market discipline on those funds they view as taking on too much risk. 1 The different strategies are defined as follows: 1) Fund of funds - Multi-Strategies: A strategy that invest in many strategies of hedge funds and mutual funds. They are intended to benefit from diversification across strategies and across funds. 2) Long/Short Equity: A strategy that involves buying certain stocks long and selling others short. Thus the net positions are based on relative value rather than absolute value of stock. These types of funds usually invest in countries that allow short sales. 3) Fund of funds: A strategy that invests in a strategy of hedge funds and mutual funds. 4) Event-driven: A strategy that takes significant positions in a certain number of companies with special situations, including distressed stocks, mergers and takeovers. 5)Market-neutral: A strategy that seeks to exploit differences in stock prices by being long and short in stocks within the same sector, industry, market capitalization, country, etc. This strategy creates a hedge against market factors. Fixed income, equity and futures arbitrage strategies fall into this category. 6) Commodity Trading Advisor: A strategy that engage in buying or selling commodity futures or option contracts. 7) Multi-Strategy: A strategy that use many strategies to produce returns. 8) Global: A strategy that bases its investment on overall economic and political views of various countries, regions, or groups including emerging markets, Asian countries, and eastern European countries. 9) Macro: A strategy that bases its investment on macroeconomic principles, including relative performance of country interest rate trends, movements in the general flow of funds, political changes, government policies, inter-government relations, and other broad systemic factors. 10) Sector: A strategy that bases its investment on specific sector such as bio-tech, technology, auto industry and defense industry for example. 11) Directional: A strategy that bases its investment on long or short position only. 7

8 Selected References Agarwal, Vikas and Narayan Y. Naik, 2000, Multi-Period Performance Persistence Analysis of Hedge Funds, The Journal of Financial and Quantitative Analysis, Vol. 35, September, pp Agarwal, Vikas and Narayan Y. Naik, 2004, Risks and Portfolio Decisions Involving Hedge Funds, The Review of Financial studies, Vol. 17, pp 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. Brown, Stephen J., William N. Goetzmann, and Rogger G. Ibbotson, 1999, Offshore Hedge Funds: Survival and Performance, The Journal of Business, Vol. 72, January, pp Chan, Nicholas, Mila Getmansky, Shane Haas, and Andrew W. Lo, 2005, Systemic Risk and Hedge Funds, National Bureau of Economic Research Working Paper No , March. Danielson, Jon, Ashley Taylor and Jean-Pierre Zigrand, 2005, Highwaymen or Heros: Should Hedge Funds be Regulated?, Journal of Financial Stability, Vol. 1, pp 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, pp Fung, William and David A.Hsieh, 1999, A Primer on Hedge Funds, Journal of Empirical Finance, Vol.6, pp Fung, William and David A. Hsieh, 2000, Measuring the Market Impact of Hedge Funds, Journal of Empirical Finance, Vol. 7, pp Garbaravicius, Tomas and Frank Dierick, 2005, Hedge Funds and Their Implications for Financial Stability, European Central Bank, Occasional Paper Series, No. 34, August. Geithner, Timothy F, 2006, Hedge Funds and Derivatives and Their Implications for the Financial System, Speech, Federal Reserve Bank of New York, September 15, Getmansky, Mila, 2005, The Life Cycle of Hedge Funds: Fund Flows, Size and Performance, Working Paper, January. Lhabitant, Francois L, 2004, Hedge Funds Investing: A Quantitative Look Inside the Black Box, EDHEC Risk and Asset Management Research Center, EDHEC Business School, working paper, April. Liang, Bing, 2000, Hedge Funds: The Living and the Dead, The Journal of Financial and Quantitative Analysis, Vol. 35, September, pp Lo, Andrew, 2001, Risk Management for Hedge Funds: Introduction and Overview, Financial Analysts Journal, Vol. 57, November/December, pp Lumpkin, Stephen and Hans J. Blommestein, 1999, Hedge Funds, Highly Leveraged Investment Strategies and Financial Markets, Financial Market Trends, No. 73, June, pp Schinasi, Garry J, 2005), Safeguarding Financial Stability: Theory and Practice, Washington D.C.: International Monetary Fund. 8

9 Table 1: Comparison of Selected Commercial Hedge Fund Databases Active Funds Graveyard Funds Assets of Active Funds ($ Billions) Time Coverage (Years) Hedgefund.net 6,500 3,350 1, Hedgefund Research.com (HFR) 5,900 3, (excluding FOF) 15 Morningstar (Altvest) 6,000 n/a Barclay Alternative Asset Center 5,500 3, TASS - Hedgeworld 4,000 2, Hedgeco.net 4,000 n/a n/a n/a Table 2: Total Number and Assets of Hedge Funds Of which Graveyard (Accumulation of Total Changes in Entering Exiting Exiting Funds) Assets Assets Assets Assets Assets Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) na na na na na na na na na na na na na na na na na na na na na na na na , na na na na , na na na na , na na na na , na na na na , , na na na na , , na na na na , , ,248 na na na na , , ,596 na na na na , , na na na na , , ,008 na na na na ,117 35, , ,952 na na na na ,522 58, , ,793 na na na na ,041 76, , , , , , , , , , , , , , , , , , , , , , , ,966 1,117 25, , , , , ,974 1,176 59, ,552 1,402 65, , , ,783 1,372 50, ,791 1, , , , ,476 1,057 45, ,725 2, ,256 June , , , , ,582 3, ,838 Note: Data on exiting funds only became available since Source: Hedgefund.net 9

10 Table 3: Total Number and Assets of Hedge Funds by Strategy Number Total Share of Total Number (%) Assets Fund of funds - Multi- Strategies Long/Short Equity Fund of funds Event-driven Market-neutral ($Mn) Assets Assets Assets Assets Assets Assets ($Mn) ($Mn) ($Mn) ($Mn) ($Mn) ($Mn) Number Number Number Number Number Number , , , , June , Share of Total Number (%) Multi-Strategy Global Macro Sector Directional Other Assets Assets Assets Assets Assets Assets ($Mn) ($Mn) ($Mn) ($Mn) ($Mn) ($Mn) Number Number Number Number Number Number June Commodity Trading Advisor Table 4: Asset Concentration Ratios of Firms Owning Hedge Funds by Strategy (Percent) Strategy Top 1% Top 5% Top 10% Fund of funds-multi 16% 43% 57% Long/Short 13% 38% 54% Directional 21% 41% 55% Fund of funds 13% 36% 52% Event-driven 18% 45% 61% Market-neutral 21% 46% 59% CTA 19% 47% 64% Multi-Strategy 23% 47% 64% Global 19% 42% 56% Macro 32% 58% 71% Sector 8% 31% 50% Other 32% 48% 64% All Strategies 19% 47% 63% Source: Hedgefund.net 10

11 Table 5: Average Monthly (Annualized) Returns of Hedge Funds (Percent) Strategy Fund of funds - Multi-Strategies Long /Short Equity Directional Fund of funds Commodity Trading Advisor Eventdriven Marketneutral Multi- Strategy Global Macro Sector Other All Strategies 1981 na na na na 2.4 na na na na na na na na na na na na na na na na na na na na na na 1.9 na na 0.9 na na 2.5 na na June Source: Hedgefund.net Table 6: Number and Assets of Hedge Funds with Persistent Positive Returns Number and assets of funds with consecutive positive returns for 1st year last 2 years last 3 years last 4 years last 5 years Assets Assets Assets Assets Assets Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,061 34, , , , , ,390 56, , , , , ,480 59, , , , , , ,467 1,325 83, , , , , ,988 1, ,890 1,004 84, , , , ,820 2, ,155 1, , , , , ,303 2, ,291 1, , , , , ,756 2, ,276 1, ,249 1, , , , ,840 4, ,046 2, ,469 1, , , , ,039 4, ,267 3, ,264 1, ,411 1, ,090 June , ,344 4, ,711 3, ,505 2, ,579 1, ,443 Source: Hedgefund.net 11

12 Table 7: Number and Assets of Hedge Funds with Persistent Negative Returns Number and assets of funds with consecutive negative returns for 1st year last 2 years last 3 years last 4 years last 5 years Assets Assets Assets Assets Assets Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) Number ($Mn) , , , , , , , , , , , ,511 62, , , , , , , , , , June , , , , Source: Hedgefund.net Table 8: The Relationship between the Likelihood of a Fund Being Alive and Selected Fund Characteristics (1) (2) (3) (4) (5) (6) C *** *** *** *** *** *** STDEV *** *** *** *** *** *** RTN *** *** *** *** *** *** LOG(ASSET9705) *** *** *** *** *** *** LIFE *** *** *** *** *** *** MANFEE *** *** *** *** *** *** INFEE *** *** *** *** *** INILOCK *** *** *** *** *** *** D_ROFF *** *** D_RASA *** *** D_REUR *** *** D_ROTH *** *** D_LGLO *** *** D_LEUR *** *** D_LASA *** *** D_LOTH *** *** D_SLS *** *** *** D_SFOF *** *** *** D_SEVD *** *** ** D_SGLOB *** ** D_SMAC ** ** McFadden R-squared Probability(LR stat) Number of Observations 7,649 7,649 7,649 7,649 7,649 7,649 Number of Live Funds 4,967 4,967 4,967 4,967 4,967 4,967 ***, ** and ** denote significance level at 1, 5, and 10 percent, respectively. The numbers in parentheses are standard errors. Note: STDEV9705 is the standard deviation of monthly returns from 1997 to 2005, RTN9705 is average monthly return from 1997 to 2005, LOG(ASSET9705) is log of average assets from 1997 to 2005, LIFE9705 is the age of funds by months from 1997 to 2005, INFEE is incentive fees, INILOCK is the longer of minimum initial lockup period, period between capital withdrawals, or number of days require to give notice before withdrawals, MANFEE is management fees based on assets under management, D_LASA is the dummy for location of assets in Asia, D_LEUR is the dummy for location of assets in Europe, D_LGLO is the dummy for location of assets in global, D_LOTH is the dummy for location of assets in other regions, D_RASA is the dummy for region of domicile in Asia, D_REUR is the dummy for region of domicile in Europe, D_ROFF is the dummy for region of domicile in off-shore centers, D_ROTH is the dummy for region of domicile in other regions, D_SEVD is the dummy for event driven strategy, D_SFOF is the dummy for fund of funds strategy, D_SGLOB is the dummy for global strategy, D_SMAC is the dummy for macro strategy, and D_SMN is the dummy for market neutral strategy. 12