Rankings of the Largest 25 Hedge Funds during the period. Greg N. Gregoriou * and Maher Kooli ** Abstract

Transcription

1 Rankings of the Largest 25 Hedge Funds during the period Greg N. Gregoriou * and Maher Kooli ** Abstract We use the live Barclay Hedge database and examine 25 of the largest onshore and offshore hedge funds during the period the period. Our results show that the majority of our considered large hedge funds do a good job of outperforming their own respective hedge fund benchmark over the 5-year period. However, hedge fund returns for 2013 alone is somewhat not as good as the 5-year period. The performance persistence tests reveal that during our sample period, winners remain winners. * Greg N. Gregoriou, Ph.D. is Professor of Finance at State University of New York (Plattsburgh), 101 Broad Street, Plattsburgh, NY Tel: (518) greg.gregoriou@plattsburgh.edu. ** Maher Kooli, Ph.D. is Professor of Finance and Caisse de Depot et Placement du Quebec Research Chair in Portfolio Management at the School of Management, Universite du Quebec a Montreal. (514) ext kooli.maher@uqam.ca. 315, Rue St-Catherine Est, R-3555, Montreal, QC H2X 3X2.

2 Introduction Bloomberg Markets magazine is well-known for its rankings of the largest 100 hedge funds on an annual basis. Bloomberg readers get a chance to see which hedge funds had the highest returns and how much each fund was managing over the preceding two years with the current ranking of each fund being compared to the previous year s ranking. Although this may interest readers, it does not provide detailed information for institutional investors, insurance companies, endowment funds, pension funds, wealthy individuals and family offices that have specific criteria before they can invest in hedge funds. The Bloomberg Markets magazine rankings will differ from the rankings in this paper since hedge fund reporting is voluntary and some hedge fund managers will report to all databases while others will only report to a few selected vendors. In addition, data quality of hedge funds as well as other features can also differ among the numerous database vendors ([Fung and Hsieh [2002]). Furthermore, the overlap of hedge funds from three databases is 30% according to Agarwal, Daniel and Naik [2004] but a more recent study by Joenväärä, Kosowski and Tolonen, [2013] puts it at 26% as a result of combining five hedge fund databases: (1) TASS-Lipper (2) HFR (Hedge Fund Research), BarclayHedge, EurekaHedge and Morningstar. The Institutional Investor Alpha magazine also has a yearly ranking list that is almost identical to Bloomberg Markets and likely there are numerous other magazines that do yearly rankings. In addition, Edelman, Fung and Hsieh [2013] use data from the Institutional Investor Hedge Fund 100 list Absolute Return and Alpha Billion Dollar Club that do not provide returns to Barclay Hedge, Hedge Fund Research and Lipper TASS databases. The authors use ending asset under management and claim that using end of year numbers is more reliable because of the checks done by audit organizations.

3 Although the rankings of Bloomberg and other are based on assets under management potential investors cannot rely solely on the yearly returns. Selecting a hedge fund is a demanding process that should include analyzing both returns and risks. When selecting hedge funds, institutional investors could consider their performance for at least a period of 3 to 5 year with detailed statistics. Potential investors might also consider not investing in newly launched hedge funds since they are likely to die according to Brown, Goetzmann and Park [2001]. Of note is the fact that large sized hedge funds receiving capital tend to generate lower performance down the line (Agarwal, Daniel and Naik, [2003] but have lower volatility than small hedge funds (Amman and Moerth, 2005). However, large funds tend to have longer survival times as well as lower volatility (Baba and Goko, [2009]). Annual rankings as displayed in various magazines do not provide however data over a longer period which is important when screening hedge fund managers. In this study, we complement previous rankings by examining the performance of the 25 largest hedge funds for the period using several performance measures. Specifically, we consider risk-adjusted returns, standard deviation, modified value at risk (VaR), modified expected tail loss, and maximum drawdown in order to provide more complete statistics for potential investors. We also add an analysis of performance persistence. Past research by Boyson [2007] finds that performance persistence has its strongest presence in new and small sized hedge funds. Boyson [2003] identifies quarterly performance persistence for hedge funds. Recently, Hamza and Kooli [2014] examine the performance persistence of Fund of Hedge Funds (FoHFs) over the January 1994 to November 2010 period and that FoHFs that show performance persistence over a short time horizon are more likely to be persistent over a longer one. They also find that hot

4 hands are among FoHFs with high-water mark provision, with incentive fess less than the average and offshore funds. Data and methodology We use the live Barclay Hedge database and examine 25 of the largest onshore and offshore hedge funds using the EVestment software. Barclay Hedge provides hedge fund returns net of management and performance fees on a monthly basis. Further, we identify each hedge fund with its respective strategy and use numerous characteristics to further add insight. We then provide a broader picture right after the recent financial crisis and use the investigative period from January 2009 to December 2013 as well as for 2013 alone. We do recognize the presence of survivorship bias [Fung and Hsieh (2002)] in our rankings as well as those listed in the issue of Bloomberg markets magazine. However, we should note that a large majority of hedge funds with assets above $1 billion tend to survive the longest [Baba and Goko (2009)]. We use conventional statistics that are already considered and well-known to the investment public. In addition to the Bloomberg Markets rankings, we display a wide variety of characteristics of each fund. We examine offshore and onshore funds as well as their strategy, standard deviation, management fees, performance fees, redemption period, minimum investment and ending assets under management, hurdle rate, high watermark and lock-up period (Exhibit 1). To complement traditional statistics we add a few measures to highlight each fund s Maximum Consecutive Gain, Modifed VaR (MVaR), Maximum Drawdown, and Modified Expected Tail Loss. The maximum consecutive gain statistic signifies that in the entire return stream of the fund it is the highest consecutive return. Traditionally, Value-at-Risk represents the largest loss over a specific time period using a certain confidence level. As hedge funds are known to exhibit non-

5 normal returns distributions due to their use of derivatives, short selling and leverage, we use the Modified VaR (at a 95% confidence level) to better address the drawback presented by the traditional VaR which is used for normal distributions. MVaR is better suited for hedge funds to account for skewness and kurtosis (3 rd and 4 th moment of a distribution). The MVaR is represented by the following equation from Favre and Galeano [2002]: MVaR W { z ( z 1) S ( z 3z ) K (2 z 5z ) S } c c c c c c (1) where σ =standard deviation; Zc=is the critical value for probability (1-α)-1.96 for a 95% probability; S=skewness and K=kurtosis. MVaR is frequently used by risk analysts to calculate the exposure of risk a hedge fund assumes. The MVaR measure can discern between two hedge funds that have the identical mean and standard deviation (the 1 st and 2 nd moments of a distribution) because each fund s extreme losses will likely be different. We also use the modified expected tail loss (at a 95% confidence level) to account for nonnormal returns which are simply the average returns exceeding MVaR. Evestment provides the following definition for Modified Expected Tail Loss (ETL) The average expected loss beyond MVaR and can be interpreted as the expected shortfall assuming MVaR as a benchmark. Modified ETL does not have the deficiencies of MVaR as it is a true downside risk measure which can recognize diversification opportunities and has good optimality properties. (Evestment [2013]; As for maximum drawdown Evestment defines this as the The drawdown is in effect from the time the fund's retrenchment begins until a new fund high is reached. The maximum drawdown encompasses both the period from the fund's peak to the fund's valley (length), and the time from the fund's valley to a new fund high (recovery). It measures the largest percentage drawdown that has occurred in any fund's data record. (Evestment [2013];

6 We measure the persistence of HF returns according to Hurst exponent that has the advantage to not make any assumption on the return distribution. The Hurst exponent, H, is defined as: H=log(R/S)/log(T) (2) where T is the duration of the data sample, and R/S is the corresponding value of the rescaled range. The latter characterizes the divergence of the return series, and is defined as the range of the sum of the data deviations from the mean divided by the sample standard deviation. The interpretation of the coefficient is as follow: If H=0.5, the behavior of the return series is similar to a random walk (i.e., no persistence); if H<0.5, the return series covers less "distance" than a random walk (i.e., if the return series increases, it is more probable that it will continue to decrease, and vice-versa; reverse persistence); if H>0.5, the return series covers more "distance" than a random walk (i.e., if the return series increases, it is more probable that it will continue to increase) which indicates positive persistence. However, it is worth mentioning that a high Hurst exponent does not indicate whether it is negative returns or positive returns that persist. Discussion of results Exhibit 1 presents hedge fund characteristics for the period. Hedge funds can be domiciled in onshore or offshore locations. In our sample, we find that 60% of the 25 largest hedge funds are based offshore while the remaining 40% are based onshore. We also find that a large majority of funds (88%) have no hurdle rates and 80% use some leverage. Furthermore, 88% of funds have a high watermark while 60% of funds have a quarterly redemption period and 24% have monthly a monthly redemption period. In terms of management fees the highest charged was 4% and the lowest was 0% charged by Millennium International Ltd. (a multi-strategy fund) while

7 for performance fees it ranged from 0% (and the highest was 20%. The minimum investment ranged from $1,000 to $5 million. Finally, the advanced notice period varied greatly from 1 day to 90 days while the most frequent lock-up period was 365 days, however 64% of funds did not report lock-up periods. When examining leverage 80% of the funds used leverage, ranging from 100% to 686% (Prologue Feeder Fund L.P. Offshore). Further, 88% of the funds have no hurdle rate and the average minimum investment is US $2.6 million while the average lock-up period is 47.6 days (with three funds not reporting). Maslakovic [2013] notes that the hedge funds industry has become more concentrated in recent years and the largest 100 hedge funds accounted for 61% of total industry assets in We find that the total assets under management (ending 2013) for our 25 largest fund is $95.5 bn. We also observe that the average ending assets under management is $3.8 trillion with the average management and performance are 1.5% and 15.6% which is below the traditional 2% and 20% hedge funds charge. Could this be the start in the industry of reducing hedge fund fees [Zuckerman, Chung and Corkery, 2013]. According to Preqin report [2010], hedge fund managers are becoming more flexible with their fee structures to attract new investors and to maintain a competitive advantage. The report also sustains that after the financial crisis, just 38% of single manager hedge funds charge 2 & 20. Exhibit 2 presents hedge fund performance measures for the period. In terms of returns, the SPM Structured Servicing Holdings, L.P. had the highest cumulative rate of return (458.4%) while Dexia Index Arbitrage Fund had the lowest (9.05%) during the period. In terms of risk-adjusted returns SPM Structured Servicing Holdings, L.P. was the highest with an Annualized Sharpe ratio of 2.8%. The annualized standard deviation ranged from a low of 0.80% to a high of 20.7% (Bay Resource Partners Offshore Fund Ltd.), but for the downside deviation Dexia Index

8 Arbitrage Fund (0.25%). When examining maximum consecutive gains, SPM Structured Servicing Holdings, L.P. had the best result with 257.2%, while the fund that had the largest maximum drawdown was DWS Akkumula with a % with Dexia Index Arbitrage Fund having the lowest (-0.55%). In terms of returns for 2013, Bay Resource Partners Offshore Fund Ltd was in the number one spot with a 21.98% followed by Oyster European Opportunities Class EUR (19.87%) net return while the lowest was Dexia Index Arbitrage Fund (1.32%). We find that SPM Structured Service Holdings, L.P. has the highest maximum consecutive gain of % followed by Pine River Fixed Income Master Fund Ltd. (185.39%). If we examine the MVaR which factors in skewness and kurtosis, we observe that in terms of absolute value the fund with the lowest MVaR is the Dexia Index Arbitrage Fund (-0.12) which implies that it has the least amount of exposure to extreme market negative events, while Bay Resource Partners Offshore Fund Ltd., had the largest (-7.33) with the lowest being Dexia Index Arbitrage Fund (-0.12). In terms of Modified Expected Tail Loss, Bay Resources Partners Offshore Fund Ltd., has the largest negative loss ( ), while Dexia has the lowest ( ). For performance analysis, we do not use the S&P 500 as a benchmark giving Brunel [2005, 2007] s result that traditional benchmarks are not a logical choice for hedge funds and can lead to misleading expectations. In Exhibit 2, we find that 18 out of 24 1 (75%) funds outperformed their respective hedge fund benchmark using the Barclay Hedge Indexes over the five-year period. Meanwhile, using only 2013 alone, we find that 11 out of 24 funds (45.8%) outperformed their respective hedge fund index. Brunel and Elmes [2012] examine the returns of three generic hedge funds strategy groups and point out that the hedge funds industry has matured, and consequently, 1 We contacted the relationship manager at the Dexia Index Arbitrage Fund in Luxembourg and he mentioned that their fund has no equivalent hedge fund benchmark because it tries to provide absolute returns above Eonia (Euro Overnight Index Average). Therefore, we do not factor this fund in our calculation of returns over the 1-year and 5-year periods.

9 some alpha (defined as a non-beta-adjusted excess return vis-a-vis traditional asset benchmarks) dilution could occur. In terms of standard deviation the group had an annualized standard deviation of 7.00%, a downside deviation 3.10% and a Sharpe ratio of The maximum drawdown the group average was -7.65%, and the average maximum consecutive gain was 44.31%, while the MVaR was % and the Modified Expected Tail Loss was %. In terms of risk measures, large funds appear to provide good returns and superior downside equity risk management as is well-known in the industry when compared to traditional asset classes. Exhibit 3 shows the Hurst exponent for each hedge fund. We find that for all hedge funds, Hurst indexes are well above 0.5 (except for MKP Opportunity Offshore, Ltd.). Thus, we confirm that overall the 25 largest HFs who show persistence over a short time horizon are more likely to be persistent over a longer one. In other words, past hedge funds returns for the 25 largest funds should partially explain their future returns. Conclusion Our main findings can be summarized as follows. The results demonstrate that a majority of large hedge funds do a good job of outperforming their respective hedge fund benchmark over the five year period; however the return in 2013 is a mixed bag with only 45.8% of funds failing to outperform their respective hedge fund benchmark. Our performance persistence tests reveal that during our sample period, winners remain winners. These results are important for investors who are looking for useful indicators to select the best performing hedge fund. However, investors should also take a number of other non-reporting factors into account when selecting hedge fund managers particularly liquidity and transparency.

10 Acknowledgements The authors would like to thank the editor, Jean Brunel, for his insightful comments and suggestions. We also thank both Sol Waksman the President at Barclay Hedge ( and Beto Carminhato the Information Technology Manager for providing the data and the Barclay Hedge Indexes. We also thank Evestment ( and client services for assistance with the Pertrac Software. The PerTrac software was critical in performing our ranking analysis. References Agarwal, V., Daniel, N.D. and Naik, N.Y. (2004). Flows, Performance, and Managerial Incentives in the Hedge Fund Industry. Working Paper, Georgia State University and London Business School. Agarwal, V., Daniel, N.D. and Naik, N.Y. (2011). Do Hedge Funds Manage Their Reported Returns? Review of Financial Studies, Vol. 24, No. 10, pp Ammann, M. and Moerth, P. (2005). Impact of Fund Size on Hedge Fund Performance. Journal of Asset Management, Vol. 6, No. 3, pp Baba, N. and Goko, H. (2009). Hedge Fund Survival: Non-Normal Returns, Capital Outflows and Liquidity. Journal of Financial Research, Vol. 32, No.1, pp Boyson, N. (2003) Do Hedge Funds Exhibit Performance Persistence? A New Approach. Working Paper Purdue University. Boyson, N. (2007). Hedge Fund Performance Persistence: A New Approach. Financial Analyst Journal, Vol. 64, No.6, pp Brown, S.J., Goetzmann, W. N. and Park, J. (2001). Careers and Survival: Competition and Risk in the Hedge Fund and CTA Industry. Journal of Finance, Vol. 56, No.5, pp Brunel, Jean. (2005). A First Cut Evaluation of the Impact of Industry Cash Flows on Hedge Fund Alpha. Journal of Wealth Management, Vol. 7, No. 4, pp Brunel, Jean L. P. (2007). Are Hedge Fund Strategies Just About Leverage? Journal of Wealth Management, Vol.10, No. 3, pp Brunel, Jean L. P. and Elmes, John T. (2012). Alternative Assets: Are They Still Worth It? Journal of Wealth Management. Vol. 15, No. 2, pp Edelman, D. and Fung, W. and Hsieh, D. (2013) Exploring Unchartered Territories of the Hedge Fund Industry: Empirical Characteristics of Mega Hedge Fund Firms. Journal of Financial Economics, Vol. 109, No.3, pp

11 Favre, L., and Galeano, J. A. (2002) Mean Modified Value-at-Risk with Hedge Funds. The Journal of Alternative Investments, Vol. 5, No.2, pp Fung, W. and Hsieh, D.A. (2002) Hedge Fund Benchmarks: Information Content and Biases. Financial Analysts Journal, Vol. 58, No.1, pp Hamza, O. and Kooli, M. (2014). Do Hot Hands Exist in Funds of Hedge Funds. Journal of Wealth Management, Vol. 16, No. 4, pp Joenväärä, J., Kosowski, R. and Tolonen, P. (2013) Hedge Fund Performance: What Do We Know? Working Paper, Available at SSRN: or Maslakovic, M. (2013) Hedge funds. Financial Markets Series, TheCityUK Report. Preqin Research Report (2010) Hedge Funds: The Fee Debate An End to 2 & 20?, Available at Preqin: Zuckerman, G., J., Chung, G. and Corkery, M. (September 9, 2013). Hedge Funds Cut Back on Fees. Wall Street Journal.

12 Exhibit 1. Offshore and Onshore Hedge Fund Characteristics Jan 1, 2009-Dec 31, 2013 Hedge fund Strategy Offshore Onshore Hurdle Rate Leverage Ending Assets High Under Management Millennium International, Ltd. Multi-Strategy Yes No N/A $ 12,149,000,000 Yes Renaissance Institutional Equities Fund (RIEF) LLC Equity Long-Bias Yes No % $ 8,732,067,000 Yes Series B Capula Global RV Fund Limited Fixed Income - Arbitrage Yes No Yes $ 5,711,760,000 Yes Millennium USA LP Multi-Strategy Yes No N/A $ 5,304,000,000 Yes DWS Akkumula Equity Long Only Yes No % $ 4,613,137,549 No Orbis Optimal (USD) Fund Equity Long/Short Yes No N/A $ 4,381,000,000 No Atlas Global Investments Ltd. Restricted Multi-Strategy Yes No Yes $ 4,097,000,000 Yes MKP Opportunity Offshore, Ltd. Macro Yes No Yes $ 3,905,000,000 Yes Permal Fixed Income Holdings N.V. - A USD Fund of Funds Yes No % $ 3,901,000,000 Yes Pine River Master Fund Ltd Multi-Strategy Yes No Yes $ 3,459,800,000 Yes Graham Discretionary Portfolio Enhanced Vol Series A Macro Yes No Yes $ 3,426,200,000 Yes Graham Discretionary Portfolio Macro Yes No % $ 3,426,200,000 Yes Pine River Fixed Income Master Fund Ltd Fixed Income - Mortgage Backed Yes No % $ 3,381,400,000 Yes Knighthead Master Fund Distressed Securities Yes No N/A $ 3,096,000,000 Yes Bay Resource Partners Offshore Fund Ltd Equity Long-Bias Yes No % $ 2,812,000,000 Yes Visium Balanced Offshore Fund Ltd Sector - Health Care/Biotech Yes No % $ 2,625,100,000 Yes Prologue Feeder Fund L.P. (Offshore) Class B EUR Fixed Income - Long/Short Credit Yes No % $ 2,593,000,000 Yes Pharo Macro Fund, Ltd. Emerging Markets - Global Yes No % $ 2,554,000,000 Yes Oyster European Opportunities Class EUR Equity Long Only Yes No % $ 2,435,323,884 Yes Double Black Diamond L.P. (Carlson) Multi-Strategy Yes No % $ 2,351,000,000 Yes Prisma Spectrum Fund Ltd. Class B Fund of Funds Yes US T-Bill % $ 2,328,877,000 Yes Pinnacle Natural Resources, L.P. Fund of Funds Yes No N/A $ 2,223,000,000 Yes SPM Structured Servicing Holdings, L.P. Fixed Income - Mortgage Backed Watermark Yes LIBOR+50bp Yes $ 2,152,966,000 Yes Dexia Index Arbitrage Fund Equity Long/Short Yes EUR 1 mo % $ 1,940,135,560 No Magnitude International - Class A Fund of Funds Yes No % $ 1,882,764,000 Yes 12

13 Exhibit 1 (cont d). Offshore and Onshore Hedge Fund Characteristics Jan 1, 2009-Dec 31, 2013 Hedge Fund Management Fee Incentive Fee Redemption Period Lock Up Period Minimum Investment Advance Notice Period Millennium International, Ltd. 0.00% 20.00% Qtrly N/A $5,000, days Renaissance Institutional Equities Fund (RIEF) LLC Series B 0.50% 10.00% Mthly N/A $5,000, days Capula Global RV Fund Limited 2.00% 20.00% Qtrly 730 days $5,000, days Millennium USA LP 0.00% 20.00% Qtrly N/A $5,000, days DWS Akkumula 1.45% 0.00% Daily N/A $1,000 1 day Orbis Optimal (USD) Fund 0.50% 0.50% Wkly N/A $50,000 N/A Atlas Global Investments Ltd. Restricted 2.00% 20.00% Mthly 365 days $1,000, days MKP Opportunity Offshore, Ltd. 1.50% 20.00% Mthly N/A $3,000, days Permal Fixed Income Holdings N.V. - A USD 2.00% 5.00% Mthly N/A $100, days Pine River Master Fund Ltd 1.50% 20.00% Qtrly N/A $1,000, days Graham Discretionary Portfolio Enhanced Vol Series A 4.00% 20.00% Qtrly N/A $3,000, days Graham Discretionary Portfolio 2.00% 20.00% Mthly N/A $3,000,000 3 days Pine River Fixed Income Master Fund Ltd 1.50% 20.00% Qtrly 365 days $5,000, days Knighthead Master Fund 2.00% 20.00% Qtrly 365 days $5,000, days Bay Resource Partners Offshore Fund Ltd 1.50% 20.00% Qtrly N/A $500, days Visium Balanced Offshore Fund Ltd 2.00% 20.00% Qtrly N/A $5,000, days Prologue Feeder Fund L.P. (Offshore) Class B EUR 2.00% 20.00% Qtrly 365 days $1,000, days Pharo Macro Fund, Ltd. 2.00% 20.00% Qtrly 365 days $5,000, days Oyster European Opportunities Class EUR 1.75% 10.00% Daily N/A $1,000 N/A Double Black Diamond L.P. (Carlson) 2.00% 20.00% Qtrly 365 days $5,000, days Prisma Spectrum Fund Ltd. Class B 1.00% 5.00% Qtrly 365 days $1,000, days Pinnacle Natural Resources, L.P. 1.00% 10.00% Qtrly N/A $1,000,000 N/A SPM Structured Servicing Holdings, L.P. 2.00% 20.00% Mthly N/A $1,000, days Dexia Index Arbitrage Fund 0.50% 20.00% Daily 1095 days $10,000 3 days Magnitude International - Class A 1.00% 10.00% Qtrly N/A $5,000, days * Funds with a 0% management fee and a 0% performance fee are correct after telephone conversations with the funds. 13

14 Hedge Fund Exhibit 2. Offshore and Onshore Hedge Fund Descriptive Statistics Jan 1, 2009-Dec 31, 2013 and Jan 2013-Dec 2013 Rank in terms of AUM Cumulative Rate of Return Barclay Hedge Respective Benchmark Cumulative Return Yearly Average Return 2013 Return Barclay Hedge Respective Benchmark 2013 Return Annualized Standard Deviation Annualized Sharpe Ratio Annualized Downside Deviation Maximum Drawdown Maximum Consecutive Gain Millennium International, Ltd % 58.01% 11.64% 13.07% % % -2.22% 23.08% Renaissance Institutional Equities % 14.55% 17.64% 10.91% % % 25.29% % 21.43% Fund (RIEF) LLC Series B Capula Global RV Fund Limited % 65.90% 7.19% 7.56% 8.57% 2.39% % -1.42% 19.81% Millennium USA LP % 58.01% 11.87% 13.30% 9.64% 2.61% % -2.13% 22.93% DWS Akkumula % 78.58% 10.20% 17.76% 21.43% 13.39% % % 21.49% Orbis Optimal (USD) Fund % 43.24% 3.68% 10.83% 15.00% 4.74% % -7.71% 14.66% Atlas Global Investments Ltd % 7.45% 11.33% 4.90% % -6.56% 14.25% % 9.64% Restricted MKP Opportunity Offshore, Ltd % 19.33% 7.55% 7.08% 5.23% 5.17% % -3.70% 10.68% Permal Fixed Income Holdings % 10.51% 11.04% 5.54% % -8.71% 35.20% % 8.29% N.V. - A USD Pine River Master Fund Ltd % 58.01% 28.38% 9.62% 9.64% 9.51% % -3.42% 92.09% Graham Discretionary Portfolio % 14.69% 7.22% 6.15% % -5.59% 49.35% % 5.23% Enhanced Vol Series A Graham Discretionary Portfolio % 19.33% 7.03% 3.61% 5.23% 3.04% % -2.83% 21.96% Pine River Fixed Income Master % 34.86% 10.14% 9.60% % -8.83% % % 8.57% Fund Ltd Knighthead Master Fund % 85.15% 22.49% 14.42% 16.88% 8.23% % % 82.27% Bay Resource Partners Offshore % 20.25% 21.98% 20.72% % % 49.28% % 21.43% Fund Ltd Visium Balanced Offshore Fund % 15.50% 18.73% 7.95% % -7.53% 18.04% % 28.46% Ltd Prologue Feeder Fund L.P % 7.36% 2.42% 2.98% % -2.24% 12.03% % 8.57% (Offshore) Class B EUR Pharo Macro Fund, Ltd % 57.96% 15.75% 18.46% 3.01% 8.65% % -8.20% 51.06% Oyster European Opportunities % 15.87% 19.87% 14.18% % % 23.52% % 21.43% Class EUR Double Black Diamond L.P % 11.00% 8.40% 5.08% % -6.53% 15.50% % 9.64% (Carlson) Prisma Spectrum Fund Ltd. Class % 8.03% 10.90% 4.10% % -6.22% 18.70% % 9.64% B Pinnacle Natural Resources, L.P % 22.97% 5.15% 1.07% 9.64% 7.36% % -9.80% 12.15% SPM Structured Servicing % 47.23% 2.95% 11.01% % -3.86% % % 8.57% Holdings, L.P. Dexia Index Arbitrage Fund % 43.24% 1.75% 1.32% 15.00% 0.80% % -0.55% 2.58% Magnitude International- Class A % 22.97% 9.95% 4.78% 9.64% 3.26% % -1.53% 29.26% Average 97.08% 14.00% 10.62% 7.00% % -7.65% 44.31% Modified VaR Modified Expected Tail Loss 14

15 Exhibit 3. Absolute Performance Persistence of Hedge Funds Measured by the Hurst Exponent- January 2009 to December 2013 Hedge Fund Rank in terms of AUM Hurst Exponent Millennium International, Ltd Renaissance Institutional Equities Fund (RIEF) LLC Series B Capula Global RV Fund Limited Millennium USA LP DWS Akkumula Orbis Optimal (USD) Fund Atlas Global Investments Ltd. Restricted MKP Opportunity Offshore, Ltd Permal Fixed Income Holdings N.V. - A USD Pine River Master Fund Ltd Graham Discretionary Portfolio Enhanced Vol Series A Graham Discretionary Portfolio Pine River Fixed Income Master Fund Ltd Knighthead Master Fund Bay Resource Partners Offshore Fund Ltd Visium Balanced Offshore Fund Ltd Prologue Feeder Fund L.P. (Offshore) Class B EUR Pharo Macro Fund, Ltd Oyster European Opportunities Class EUR Double Black Diamond L.P. (Carlson) Prisma Spectrum Fund Ltd. Class B Pinnacle Natural Resources, L.P SPM Structured Servicing Holdings, L.P Dexia Index Arbitrage Fund Magnitude International - Class A