Jacobson Fund Managers Ltd.

Transcription

1 Investable Hedge Fund Indices: An Assessment and Review ABSTRACT: Investable Hedge Fund Indices (IHFI s) have grown in numbers since the first meaningful introduction of these during While making their presence wide spread through a number of main providers, investors have been left with the task of considering whether or not IHFI s achieve in practice a better if not outright alternative to established Hedge Funds of Funds (HFOF s ). What the assessments provided by this report show is that IHFI s are not very different to HFOF s and in many ways HFOF s remain a more viable alternative. Large dispersions are shown to exist for the same types of Hedge Fund Strategies amongst the different IHFI providers. The subscription and redemption costs, notice periods and annual fees make the actual performance which investors can expect to realise from Buy and Hold investing, substantially less than that reported for the underlying indices on which the IHFI s are based. In summary, many practical challenges remain open with investing in IHFI s and will require considerable time and resources to shift the vote towards IHFI s away from HFOF s if at all. Jacobson Fund Managers A Research White Paper 1

2 Investable Hedge Fund Indices An Assessment and Review ABSTRACT: Investable Hedge Fund Indices (IHFI s) have grown in numbers since the first meaningful introduction of these during While making their presence wide spread through a number of main providers, investors have been left with the task of considering whether or not IHFI s achieve in practice a better if not outright alternative to established Hedge Funds of Funds (HFOF s ). What the assessments provided by this report show is that IHFI s are not very different to HFOF s and in many ways HFOF s remain a more viable alternative. Large dispersions are shown to exist for the same types of Hedge Fund Strategies amongst the different IHFI providers. The subscription and redemption costs, notice periods and annual fees make the actual performance which investors can expect to realise from Buy and Hold investing, substantially less than that reported for the underlying indices on which the IHFI s are based. In summary, many practical challenges remain open with investing in IHFI s and will require considerable time and resources to shift the vote towards IHFI s away from HFOF s if at all. 1. INTRODUCTION The rise of the hedge fund of funds (HFOF s) industry, and its additional layer of fees imposed upon investors above that of individual underlying hedge funds begs the question as to whether sufficient value is added in all cases to justify such fees beyond that created by simple scale economies. It would appear that in many, although not all cases, the overlay fee is justified due to provision of tangible investment management services. The introduction of Investable Hedge Fund Indices (IHFI s) during 2003 by various sponsors has created an opportunity at the margin for investors to weigh such HFOF s fees against a passive investment in IHFI s. This report quantifies the performance net of expenses of holding a portfolio of these instruments, and investigates whether, in full consideration of transaction costs and investment restrictions, a simple trading allocation model might provide superior investment performance. In addition to evaluating the returns to buy and hold strategies, this report tests if either the momentum and mean reversion effects of Debondt & Thaler (1985, 1989) can be found amongst supposedly pure alpha generating investments such as hedge fund strategies. We find in general that some positive serial correlations exist in IHFI returns over short measurement periods such as one month, but that this relationship tends to deteriorate when longer time periods are used, where there is a greater incidence of negative serial correlations. This would suggest that over shorter holding period s momentum type strategies might be optimal, but mean-reversion type strategies might be more profitable over longer holding periods. We perform an additional series of tests using Rachev Ratios for ranking purposes and portfolio formation, which have the benefit of accounting for non-gaussian return distributions and adjusting for risk. For our full sample period, before taking account of costs and fees, equally weighted buy and hold portfolios yield annualized returns of 8.81%, 8.81%, 10.57%, 9.38% and 9.55% for HFRX Certificates, HFRX Funds, MSCI Lyxor Funds, FTSEhx Funds, and SPhinX Funds respectively, with a combined portfolio based on these index groups earning an average of 9.42% per annum over this period. With costs and fees these returns fall to 6.35%, 7.32%, 9.05%, 8.24%, and 8.16% respectively, for a combined average portfolio return of 7.83%. The average effect of costs is a reduction in annualized return of -16.9%. Despite the effect of costs, in the majority of our tests a simple momentum model yields higher returns then a buy/hold strategy. The presence of some negative serial correlations also creates some situations in which a simple strategy of buying the poorest performers will outperform a buy and hold strategy as well. However, when considering risk adjusted measures, the results of our tests using the Rachev Ratio based momentum model show that after accounting for transaction costs, all scenarios in our test period fail to generate returns greater than a buy and hold strategy. When the Rachev methodology is applied to a Contra/Reversal strategy, there are some situations where profitable strategies may exist. However all of the aforementioned results may be anomalous due to stale pricing or valuation averaging effects with respect to certain strategies. Certainly it is interesting to note the article by De Souza and Gokcan (2004) who have argued that studies showing superior risk/return characteristics of hedge funds are misleading. They attempt to demonstrate that most hedge fund strategy returns display significant amounts of serial correlation due more to NAV valuation than performance effects. 2

3 In overall terms as based on the findings of this report, we find investing in Hedge Fund Investable Indices to be less than straightforward with many unresolved issues remaining. Investing on a Buy and Hold basis does not appear in all cases to offer an acceptable risk/reward position when compared to active management of HFOF s. Investors may not actually be able to realize profitable benefits from Buy and Hold that are risk/reward beneficial in practice, and strategies such as Contra/Reversal may pose significant operational and market risk issues. Funds of Funds may, for many of their own shortcomings, generally remain a more beneficial option for the time being until a more mature and commoditised investable index market develops. The reminder of this report is provided on four further sections. In the next section we review the data sets available for IHFI s. In section 3 we consider a number of alternative investing strategies in IHFI s ranging from Buy and Hold to contra and mean reversion approaches. Section 4 provides a discussion of the results and the final section provides the main conclusions. 2. DATA Our dataset consists of monthly returns of the available set of Investable Indices from Jan 1998 Sept This consists of investment instruments designed to track the indices of four calculation groups: FTSE Hedge Indices, HFRI Indices, MSCI Hedge Invest Indices, and Standard & Poor s Hedge Fund Indices. The FTSEhx Funds are investments emulating the FTSE Hedge Indices and are available through MSS Capital. FTSEhx returns have been derived from pro forma NAV's supplied by MSS capital and are net of approximately 1.06% per annum expenses (See Appendix A). As returns are NAV-NAV, no adjustment for fees has been performed. HFR Asset Management is both the calculation agent and investment provider for certain instruments which track the HFRX Indices. These investments take the form of either direct investment in funds managed by HFR asset management, and investment in Index-Linked Certificates, which are technically debt instruments of major investment banks and whose return is tied to the performance of specified indices. The difference between these two types of instruments are that direct investment funds levy no transaction costs in terms of purchases and sales of shares, and offer trading only infrequently, at month-end, subject to a 15 business day notice. Index certificates on the other hand offer continuous trading both Over-the-Counter (OTC) and on the Swiss Exchange, subject to a bid-ask spread, and generally have higher ongoing expenses related to fees charged by the Investment Bank. The designated primary market maker for HFRX Index Certificates on the Swiss Exchange is currently Dresdner Bank, which currently quotes a spread of 1.4 % versus the bid side of the market bid-offer differential. As such securities are thus relatively illiquid; an accounting convention would properly apply to investors in index certificates where such securities are valued on the basis of closing or most recent bid price in the case of long position. On this basis, therefore an investor in the HFRX certificates can be assumed to incur an instantaneous unrealized loss equal to the amount of the bid offer spread. As only limited history is available for the HFRX indices, HFRI returns have been substituted after appropriate adjustments have been made. HFRX Returns prior to April 2003 are pro forma reconstructed on the basis of historical returns of the relevant HFRI indices. Correlations, slope estimates, and y intercepts have been estimated using data for the HFRX indices from 1 st April 2003 through 1st October HFRI data were then adjusted by relevant slope and intercept factors. Returns are adjusted further downward by 1/12 of relevant fees listed in Appendix A. In the case of index certificates, returns have been further reduced by the amount of transaction cost denoted where applicable. MSCI Lyxor Funds are offered through Societe Generale, parent of Lyxor Asset Management, MSCI Lyxor returns are shown net of 1/12 annual expenses as per Appendix A. SPhinX Funds data were provided by fund manager PlusFunds group. The SPhinX funds are designed to track the performance of Standard & Poor s Hedge Fund Investable Indices. Pro Forma monthly returns are used from January 1998 to September Actual figures are used from October 2002 to present and 1/12 of PlusFunds' investment management fee represented in Appendix A has been deducted from monthly returns. 3

4 2.1 Descriptive Statistics Monthly descriptive statistics for 76 monthly returns for each index are set forth in Table 1. In all cases, our sample means are positive. However, due partially to the relatively small sample size in consideration, none of the indices are significantly different from zero at the 95% confidence level. Additionally, monthly sample standard deviations in most cases are greater in magnitude than mean returns. Of further note is evidence of non-gaussian distributions in the sample data. Evidence is present in numerous indices of negative skew and substantial excess kurtosis (or fat tails ). Cumulative returns for each index are set forth by provider and by style in Figures The most pronounced result observed based on both the summary statistics of Table 1 and the cumulative performance graphs shown in Figures 5-13 is the dispersion amongst the same strategy (or strategy types) relative to the different providers. This dispersion cannot be attributed simply to statistical uncertainty. It is to do with the realization that the underlying managers selected in each of the individual strategies, even for the same strategy type, are providing unequal although highly correlated returns. In addition, part of the differences can be attributed to the different costs and fees as summarized in Appendix A. There is ample evidence provided by these results that equal risks are not being rewarded by equal returns and more particularly, risk adjusted returns. In general, the same style returns are not equal or homogenous across the individual investable index providers. If shorting positions were to become available for these investable indices, arbitrageurs would have a field day at the expense of the underlying investors attempting to achieve a specific exposure and stable returns profile. Of further importance is the observation that the timing and notice periods required across the different investable indices means that a key virtue of being able to move quickly in and out of a specific style is not a uniformly available feature. The so called lock-up feature already familiar to HFOF s investors is also present with investable indices for the time being. Table 1: Descriptive Statistics, Investable Hedge Fund Indices Including Pro Forma results for defined periods FTSE Hedge FTSE Hedge Index Directional Event Driven Non- Convertible Directional Arbitrage CTA Managed Futures Distressed Opportunities Equity Arbitrage Equity Hedge Fixed Income Relative Value Global Macro Merger Arbitrage Mean 0.78% 1.18% 0.46% 0.39% % % 1.25% 0.15% 0.94% 0.41% Standard Deviatio n 1.13% 1.87% 1.47% 1.01% 1.67% 4.59% 2.23% 1.18% 2.38% 1.49% 2.06% 1.01% Sample Variance 0.01% 0.04% 0.02% 0.01% 0.03% 0.21% 0.05% 0.01% 0.06% 0.02% 0.04% 0.01% Kurtosis Skewness HFR Indices Macro Index Relativ e Value Arbitrag e Index 0.39% 0.64% Convertible Arbitrag e Index Merger Arbitrage Index Distressed Securities Index Event- Driven Index Equity Hedge Index Equity Market Neutral Index Mean 0.63% % % 0.71% 0.46% Standard Deviatio n 1.72% 1.48% 1.18% 1.71% 1.84% 2.19% 0.98% Sample Variance 0.03% % 0.01% 0.03% 0.03% 0.05% 0.01% Kurtosis Skewness MSCI Hedge CB Arbitrage CTA Managed Futures 1.04% 3.34% Event Driven Forex Trading Global Macro LS Equity Long Bias LS Equity No Bias LS Equity Variable Bias Mean 1.13% 0.75% 0.62% 0.78% 0.95% 0.85% 1.47% Standard Deviatio n 1.28% 1.75% 3.76% 2.09% 2.56% 2.91% 2.77% Sample Variance 0.02% 0.11% 0.03% 0.14% 0.04% 0.07% 0.08% 0.08% Kurtosis Skewness S&P Hedge Fund Indices S&P S&P S&P Fixed S&P Hedge Directional/ S&P Event- Managed Special Merger Managed Long/Sh ort Arbitrag e Distressed Macro Income Convertible Market Fund Index Tactica l Driven Index Futures Situations Arbitrage Futures Equity Arbitrage Neutral Index Arbitrage Index Index Mean % 0.71% 0.56% 0.78% 0.61% 0.35% 0.68% 0.57% 0.72% 0.76% 0.23% 0.82% 0.42% Standard Deviatio n 0.89% 1.21% 1.66% 1.41% 4.79% 1.83% 1.38% 1.75% 1.95% 3.64% 3.07% % 1.52% Sample Variance 0.01% 0.01% 0.03% 0.02% 0.23% 0.03% 0.02% 0.03% 0.04% 0.13% 0.09% 0.09% 0.01% 0.02% Kurtosis Skewness

5 Figure(s) 1-4 Investable Hedge Fund Indices by Provider Based on Pro Forma Data Figure 1: FTSEhx Funds-, Jan 1998 Through May 2004 Pro Forma Returns Jan 1998-Mar 2004, Actual Apr 2004-May Jan-98 Jan-99 FTSE Hedge Index FTSEhx- Directional FTSEhx- Event Driven FTSEhx- Non-Directional FTSEhx- Convertible Arbitrage FTSEhx- CTA Managed Futures FTSEhx- Distressed Opportunities FTSEhx- Equity Arbitrage FTSEhx- Equity Hedge FTSEhx- Fixed Income Relative Value FTSEhx- Global Macro FTSEhx- Merger Arbitrage Figure 2: HFRX Indices, With Costs Jan 1998 Through Sept 2004 Pro Forma Returns Jan Mar 2003, Actual Returns Apr 2003-Sept Jan-98 Jan-99 HFRX Macro Index HFRX Relative Value Arbitrage Index HFRX Convertible Arbitrage Index HFRX Merger Arbitrage Index HFRX Distressed Securities Index HFRX Event-Driven Index HFRX Equity Hedge Index HFRX Equity Market Neutral Index 5

6 Figure 3: MSCI Lyxor Funds, With Costs Jan 1998 Through Aug 2004 Pro Forma Returns Jan 2000-Jul 2003, Actual Returns Aug 2003 to Aug Jan-98 Jan-99 MSCI Lyxor CB Arbitrage MSCI Lyxor CTA Managed Futures MSCI Lyxor Event Driven MSCI Lyxor Forex Trading MSCI Lyxor Global Macro MSCI Lyxor LS Equity Long Bias MSCI Lyxor LS Equity No Bias MSCI Lyxor LS Equity Variable Bias Figure 4: SPhinX Funds, With Costs Jan 1998 Through Sept 2004 Pro Forma Returns Jan Sept 2002, Actual Returns October 2002-Present Jan-98 Jan-99-4 SPhinX Hedge Fund Index SPhinX Arbitrage Index SPhinX Directional/Tactical Index SPhinX Event-Driven Index SPhinX Managed Futures Index SPhinX Special Situations SPhinX Merger Arbitrage SPhinX Distressed SPhinX Macro SPhinX Managed Futures SPhinX Long/Short Equity SPhinX Fixed Income Arbitrage SPhinX Convertible Arbitrage SPhinX Market Neutral 6

7 Figures (5-13) Investable Hedge Fund Indices by Style Based on Pro Forma Data. Figure 5: Distressed Strategies,, Actual and Pro Forma Data, Feb 1998-May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04-2 FT SE Distressed Opportunities HFRX Distressed Securities Index SPhinX Distressed Figure 6: Equity Arbitrage Strategies,, Pro Forma and Actual Data, Feb 1998 through May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04-1 HFRX Merger Arbitrage Index FTSE Merger Arbitrage FTSE Equity Arbitrage SPhinX Merger Arbitrage 7

8 Figure 7: Equity Hedge Strategies,, Pro Forma and Actual Data, Feb 1998 through May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04-5 FTSE Equity Hedge HFRX Equity Hedge Index HFRX Equity Market Neutral Index SPhinX Long/Short Equity MSCI Lyxor LS Equity Long Bias MSCI Lyxor LS Equity No Bias MSCI Lyxor LS Equity Variable Bias SPhinX Market Neutral Figure 8: Event Driven Strategies,, Actual and Pro Forma Data, Feb 1998-May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04 FTSE Event Driven HFRX Event-Driven Index MSCI Lyxor Event Driven SPhinXS&P Event-Driven Index 8

9 Figure 9: Fixed Income/Convertible Arbitrage Strategies,, Actual and Pro Forma Data, Feb May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04-4 SPhinX S&P Arbitrage Index SPhinX Fixed Income Arbitrage SPhinX Convertible Arbitrage MSCI Lyxor CB Arbitrage FTSE Convertible Arbitrage HFRX Convertible Arbitrage Index Figure 10: Global Macro Strategies,, Actual and Pro Forma Data, Feb May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04 SPhinX Directional/Tactical FTSE Global Macro MSCI Lyxor Global Macro SPhinX Macro HFRX Macro Index FTSE Directional 9

10 Figure 11: Managed Futures,, Actual and Pro Forma Data, Feb May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04 FTSE CTA Managed Futures MSCI Lyxor CTA Managed Futures MSCI Lyxor Forex Trading SPhinX Managed Futures SPhinX S&P Managed Futures Index Figure 12: Merger Arbitrage Strategies,, Actual and Pro Form Data, Feb May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb-04-1 HFRX Merger Arbitrage Index FTSE Merger Arbitrage FTSE Equity Arbitrage SPhinX Merger Arbitrage 10

11 Figure 13: Relative Value Strategies,, Actual and Pro Forma Data, Feb May Feb-98 Feb-99 Feb-00 Feb-01 Feb-02 Feb-03 Feb HFRX Relative Value Arbitrage Index FTSEhx Fixed Income Relative Value 2.2 Autocorrelations The success of any momentum trading model will ultimately be due largely to the degree to which past returns are related to future returns. For each value of time period t, Table 2 outlines the correlation in our sample of the return at time T to the return at time T-1. Note that when t is a short interval length, as in one month, the mean autocorrelation is positive and equal on average to a value of.20. In this case 35 of our 42 indices show positive serial correlations. However, when t is lengthened to six months, mean autocorrelation turns negative and the average is equal to In this case only 25 of our 42 indices show positive serial correlations. The implication of this result is that as observed by Debondt and Thaler (1985, 1989) momentum effects are only at play only in the short term as observed by in the equity markets, but that mean-reversion may be at work over longer time periods. Note also that while there is positive clustering of autocorrelations for short values of t as evidenced by a standard deviation among these indices of only.16 as compared to the greater dispersion evidenced by standard deviations of.28 and.32 respective for t=6 months and t=12 months. 11

12 Table 2: Autocorrelations Rt, Rt-1; Investable Hedge Fund Indices Mean, Standard Deviation of Correlations - Rt, Rt-1 Key Observations: t Mean Stdev Mean autocorrelation across sample universe is positive for one month but negative for six months. 1M Dispersion of autocorrelations increases steadily with length of measurement period 2M Certain Sectors. E.g. mgd futures, exhibit persistency in direction of serial correlations across periods 6M M t = 1M t = 3M t= 6M t = 12M MSCI Hedge CTA Managed Futures MSCI Hedge Forex Trading FTSE Hedge Convertible Arbitrage S&P Managed Futures Index MSCI Hedge Forex Trading MSCI Hedge LS Equity No Bias S&P Macro FTSE Hedge Convertible Arbitrage FTSE Hedge CTA Managed Futures MSCI Hedge CTA Managed Futures MSCI Hedge Forex Trading MSCI Hedge CTA Managed Futures FTSE Hedge Global Macro S&P Managed Futures S&P Managed Futures FTSE Hedge CTA Managed Futures HFR Indices Equity Market Neutral Index S&P Directional/Tactical Index HFR Indices Convertible Arbitrage Index HFR Indices Event-Driven Index S&P Managed Futures S&P Managed Futures Index S&P Managed Futures Index HFR Indices Distressed Securities Index S&P Managed Futures Index 0.02 FTSE Hedge Global Macro MSCI Hedge CTA Managed Futures MSCI Hedge Forex Trading S&P Directional/Tactical Index 0.03 S&P Macro FTSE Hedge CTA Managed Futures S&P Fixed Income Arbitrage S&P Macro 0.07 HFR Indices Macro Index S&P Directional/Tactical Index FTSE Hedge Distressed Opportunities S&P Fixed Income Arbitrage 0.10 FTSE Hedge Fixed Income Relative Value FTSE Hedge Non-Directional S&P Managed Futures FTSE Hedge Merger Arbitrage 0.11 FTSE Hedge CTA Managed Futures FTSE Hedge Global Macro HFR Indices Macro Index S&P Merger Arbitrage 0.12 FTSE Hedge Directional MSCI Hedge LS Equity Long Bias FTSE Hedge Equity Arbitrage FTSE Hedge Fixed Income Relative Value 0.12 FTSE Hedge Equity Hedge FTSE Hedge Fixed Income Relative Value FTSE Hedge Global Macro S&P Arbitrage Index 0.13 FTSE Hedge Convertible Arbitrage HFR Indices Macro Index S&P Event-Driven Index HFR Indices Macro Index 0.14 FTSE Hedge Index S&P Event-Driven Index MSCI Hedge Event Driven MSCI Hedge LS Equity Long Bias 0.15 HFR Indices Convertible Arbitrage Index S&P Distressed MSCI Hedge LS Equity Long Bias FTSE Hedge Directional 0.16 MSCI Hedge Global Macro S&P Hedge Fund Index S&P Special Situations MSCI Hedge LS Equity No Bias 0.18 FTSE Hedge Non-Directional 0.01 S&P Convertible Arbitrage FTSE Hedge Fixed Income Relative Value HFR Indices Equity Hedge Index 0.19 HFR Indices Equity Market Neutral Index 0.02 S&P Special Situations S&P Distressed MSCI Hedge Global Macro 0.20 S&P Fixed Income Arbitrage 0.02 HFR Indices Relative Value Arbitrage Index FTSE Hedge Non-Directional FTSE Hedge Non-Directional 0.20 S&P Long/Short Equity 0.03 S&P Fixed Income Arbitrage HFR Indices Relative Value Arbitrage Index 0.00 S&P Long/Short Equity 0.21 MSCI Hedge Event Driven 0.04 S&P Long/Short Equity FTSE Hedge Event Driven 0.01 HFR Indices Merger Arbitrage Index 0.21 HFR Indices Relative Value Arbitrage Index 0.04 FTSE Hedge Equity Arbitrage S&P Directional/Tactical Index 0.01 FTSE Hedge Equity Arbitrage 0.22 MSCI Hedge LS Equity Long Bias 0.06 HFR Indices Distressed Securities Index S&P Long/Short Equity 0.01 S&P Market Neutral 0.24 S&P Market Neutral 0.07 FTSE Hedge Directional 0.01 HFR Indices Convertible Arbitrage Index 0.05 S&P Hedge Fund Index 0.24 S&P Event-Driven Index 0.07 HFR Indices Event-Driven Index 0.02 S&P Hedge Fund Index 0.10 FTSE Hedge Index 0.25 S&P Convertible Arbitrage 0.07 FTSE Hedge Index 0.02 MSCI Hedge Global Macro 0.11 HFR Indices Relative Value Arbitrage Index 0.26 S&P Hedge Fund Index 0.07 MSCI Hedge LS Equity No Bias 0.03 S&P Convertible Arbitrage 0.13 HFR Indices Event-Driven Index 0.30 HFR Indices Event-Driven Index 0.07 MSCI Hedge Global Macro 0.04 S&P Macro 0.16 MSCI Hedge LS Equity Variable Bias 0.32 HFR Indices Equity Hedge Index 0.08 S&P Arbitrage Index 0.05 FTSE Hedge Index 0.17 FTSE Hedge Equity Hedge 0.32 S&P Distressed 0.12 MSCI Hedge Event Driven 0.05 HFR Indices Equity Hedge Index 0.20 FTSE Hedge Convertible Arbitrage 0.33 S&P Special Situations 0.16 S&P Market Neutral 0.12 FTSE Hedge Equity Hedge 0.26 FTSE Hedge Event Driven 0.34 MSCI Hedge LS Equity Variable Bias 0.16 FTSE Hedge Distressed Opportunities 0.13 S&P Market Neutral 0.27 S&P Event-Driven Index 0.35 S&P Arbitrage Index 0.16 FTSE Hedge Equity Hedge 0.13 MSCI Hedge LS Equity Variable Bias 0.27 S&P Convertible Arbitrage 0.37 HFR Indices Distressed Securities Index 0.16 FTSE Hedge Event Driven 0.23 S&P Arbitrage Index 0.29 FTSE Hedge Distressed Opportunities 0.37 HFR Indices Merger Arbitrage Index 0.17 HFR Indices Equity Hedge Index 0.25 FTSE Hedge Directional 0.29 S&P Special Situations 0.39 FTSE Hedge Equity Arbitrage 0.21 MSCI Hedge LS Equity Variable Bias 0.28 HFR Indices Equity Market Neutral Index 0.36 HFR Indices Convertible Arbitrage Index 0.41 FTSE Hedge Event Driven 0.24 MSCI Hedge CB Arbitrage 0.38 HFR Indices Merger Arbitrage Index 0.37 MSCI Hedge CB Arbitrage 0.43 FTSE Hedge Distressed Opportunities 0.25 HFR Indices Merger Arbitrage Index 0.42 S&P Merger Arbitrage 0.55 MSCI Hedge Event Driven 0.43 S&P Merger Arbitrage 0.31 S&P Merger Arbitrage 0.50 FTSE Hedge Merger Arbitrage 0.56 S&P Distressed 0.44 FTSE Hedge Merger Arbitrage 0.39 FTSE Hedge Merger Arbitrage 0.57 MSCI Hedge LS Equity No Bias 0.64 HFR Indices Distressed Securities Index 0.45 MSCI Hedge CB Arbitrage 0.57 HFR Indices Equity Market Neutral Index 0.60 MSCI Hedge CB Arbitrage 0.75 Mean Autocorrelation 0.20 Mean Autocorrelation 0.01 Mean Autocorrelation Mean Autocorrelation 0.00 StDev 0.16 StDev 0.20 StDev 0.28 StDev TRADING MODELS Many investments in IHFI s carry a special caveat of required notice period for redemptions and subscriptions. Such as in the case of the HFRX funds, investments can be redeemed at month-end at NAV, subject to a notice period of 15 business days i.e. three weeks. To maintain consistency with respect to these considerations, monthly returns of various IHFI s for the period Jan 1998 though Aug 2004 IHFI s are sorted into five groups by provider: HFRX Certificates, HFRX Funds, MSCI Lyxor Funds, FTSEhx Funds, and SPhinX Funds. Full details with regard to trading restrictions and costs are set forth in Appendix A. This properly accounts for differences in information availability with regard to the historical returns at the time the investment decision is made. Our sample holding periods commence 1 January 2000 and end 31 December 2003, and coincide with quarter, semi-annual, and calendar year ends where applicable. We then perform out of sample tests by extending our measurement period to include available YTD returns. These include returns through 31 May 2004 for FTSEhx Funds, through 31 August 2004 for MSCI Lyxor and SPhinX Funds, and through 30 Sept 2004 for the HFRX Certificates and Funds. We compare the hypothetical experience of an investor in hedge fund investable indices under several circumstances. First we consider the investment experience of such an investor who holds an equal weighted portfolio of our IHFI universe throughout our sample holding periods. We consider this both with and without the effect of transaction and holding expenses. We next consider if this performance can be improved by using a simple momentum trading rule of holding only the funds over the subsequent holding period which have performed in the top quintile (20the percentile) of each respective group over each respective measurement period. We then test a contra/reversal strategy of holding the indices which have performed the most poorly, i.e. in the bottom quintile over the relevant measurement period. Ranking for these purposes is done on two basis, first simply on the basis of cumulative return, and second, ranking using the Rachev Ratio, (see Biglova, Jasic, Rachev & Fabozzi, 2004) to properly adjust for risk and non-gaussian return distributions. We note however, none of these tests or criteria are sufficient to establish long term validation of results. This observation is based on the fact that underlying market behavior is, as is well known, non-stationary. 12

13 3.1 Equal Weight Buy and Hold Portfolio Before taking account for the effect of costs, investments in equal weighted portfolios of each of our sub-universe groupings would yield annualized returns over our sample period of 8.81%, 8.81%, 10.57%, 9.38% and 9.55% for HFRX Certificates, HFRX Funds, MSCI Lyxor Funds, FTSEhx Funds, and SPhinX Funds respectively, with an equal weighted portfolio of our five providers earning 9.42% over this period. With the full effect for transaction costs in the case of index certificates, and fund management and administrative fees in all cases, these returns fall to 6.35%, 7.36%, 9.05%, 8.24%, and 8.16% respectively, for an average of 7.83%. The impact of costs on returns is thus These results are summarized in Table 3 and graphically demonstrated in the Figures 14 through to 18. Table 3: Impact of Trading Costs and Expenses on Equal Weight Buy/Hold Portfolio of Different Investable Indices Effect of Costs on Buy/Hold Return, Full Period Notice Required Funds Without Costs With Costs %Differential HFRX Certificates No Notice % 6.35% % HFRX Funds 0-1M Notice % 7.36% % MSCI Lyxor Funds 0-1M Notice % 9.05% % FTSEhx Funds 1-2M Notice % 8.24% % SPhinX Funds 2-3M Notice % 8.16% % Average 9.42% 7.83% Figure 14: HFRX Certificates- Impact of Costs, Equal Weight Portfolio Jan 2000-Sept Without Costs With Costs 13

14 Figure 15: HFRX Funds, Impact of Costs, Equal Weight Portfolio, Jan 2000-Sept Cumulative P/L With Costs Without Costs Figure 16: MSCI Lyxor Funds, Impact of Costs, Equal Weight Portfolio, Jan 2000-Aug M Rebalance Without Costs 14

15 Figure 17: FTSEhx Funds, Impact of Cost, Equal Weight Portfolio, Jan 2000-May % 4 35% 3 25% 2 15% 1 5% Without Costs With Costs Figure 18: SPhinX Funds, Impact of Costs, Equal Weight Portfolio, Jan Aug Without Costs With Costs 15

16 3.2 Simple Ranking Model Our first test involves the construction of simple momentum and reversal models via portfolios formed on the basis of cumulative returns through the measurement period used for portfolio formation. For consistency purposes, we consider only the returns which were known pro-forma at the time investment decisions were made. Thus for example, where a notice period of between zero and 1 months applies, T-1 monthly returns are not known at the time a decision is required, an investors will only know T-2 and prior. We then form equal weight portfolios which we reallocated respectively each 3, 6, and 12 months on the basis of ranked performance ranking over the most recent period of equal length to the holding period of which data was available. Thus for example, for a six month holding period where a one month s notice period of up to one month applies, allocation decisions are made on the basis of ranked performance of each index over preceding 2-7 months, i.e. on the basis of performance from T-7 to T-2. For consistency and simplification, information which may have been available between prior month end and the decision cutoff point has been ignored. Indices are rebalanced at stated frequency on the basis of cumulative absolute returns which have become known in the interim holding period. For example, for those requiring 1-2 months notice and rebalanced every six months, returns used are that of the prior T-7 through T-3 months. Indices are then ranked from either lowest-highest or highest-lowest cumulative returns based whether a momentum or contra/reversal strategy is desired. From these rankings, portfolio weights are generated on the basis of their inclusion in the appropriate percentile cutoff. Thus utilizing a 20 th percentile criterion will form equal weight portfolios throughout of the top or bottom 2 of performers over the prior measurement period. As fractional percentile cutoffs are not feasible, the rank cutoff points have been truncated to next lowest integer value where applicable, e.g. the 2 percentile is two indices amongst a universe of 14, and 3 indices amongst a universe of 15. Results of our tests involving a simple momentum strategy are shown below in Table 4 and Figures 19 through 28. As shown, in the absence of costs returns are highest for the HFRX Certificates, with annualized returns above 15% in all cases. This is most likely due to the benefit derived from short run positive serial correlations and is evidence, in the absence of any filtering, of some momentum effects in Investable hedge fund indices. The source of such momentum is not however known and we note in particular the report by De Souza and Gokcan (2004) who have argued that most hedge fund strategy returns display significant amounts of serial correlation due more to valuation than performance effects. To consider properly the ability for investors to earn superior returns to buy/hold strategies as well as that of actively managed fund-of-funds (HFOF s), we must again take full consideration for all the costs involved. With regard to momentum strategies, the impact is most substantial on funds requiring no notice such as the HFRX index certificates, as an investor will incur a transaction cost each time a rebalance occurs, in addition to management and administrative fees. In most cases, however returns using this simple model appear to be superior to that of a passive buy/hold strategy. Even in the case of funds with such high fees as the HFRX Certificates, momentum effects are sufficiently strong in our sample to yield profitable results despite the effect of costs. Likely due to the presence of negative serial correlations in the data set, there are some situations in which a simple strategy of buying the poorest performers will outperform a buy and hold strategy as well before transaction costs are factored. This is most pronounced in the case of 3 month rebalancing for the MSCI Lyxor and SPhinX Funds. A summary of these Contra Model results is provided in Table 5 and the accompanying Figures 29 through

17 Table 4: Performance Before and After Costs-Simple Momentum Model 4(a) Simple Momentum Model Without Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 15.09% % HFRX Funds 0-1M Notice % 14.85% 14.83% 14.42% MSCI Lyxor Funds 0-1M Notice % 15.21% 13.22% 14.86% FTSEhx Funds 1-2M Notice % 10.91% 9.94% 9.56% SPhinX Funds 2-3M Notice % 9.07% 12.66% 8.89% Average 11.58% 13.02% 13.33% 12.65% 4(b) Simple Momentum Model With Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 11.18% 12.74% 11.14% HFRX Funds 0-1M Notice % 13.33% 13.31% 12.9 MSCI Lyxor Funds 0-1M Notice % 13.62% 11.66% 13.28% FTSEhx Funds 1-2M Notice % 9.75% 8.79% 8.41% SPhinX Funds 2-3M Notice % 9.75% 7.46% Average 9.41% 11.26% 11.25% 10.64% Table 5: Performance Before and After Transaction Costs-Contra/Reversal Model. 5(a) Simple Contra Model Without Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 6.46% 5.31% 6.7 HFRX Funds 0-1M Notice % 7.19% 9.14% 8.16% MSCI Lyxor Funds 0-1M Notice % 14.77% 13.13% 15.81% FTSEhx Funds 1-2M Notice % 7.22% 5.07% 6.91% SPhinX Funds 2-3M Notice % 7.06% 10.45% Average 11.81% 9.06% 7.94% 9.61% 5(b) Simple Contra Model With Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 1.71% 1.64% HFRX Funds 0-1M Notice % 5.76% 7.69% 6.72% MSCI Lyxor Funds 0-1M Notice % 13.19% 11.57% 14.22% FTSEhx Funds 1-2M Notice % 5.79% SPhinX Funds 2-3M Notice % 8.36% 5.48% 9.12% Average 9.34% 7.06% 6.08% 7.49% 17

18 Figure 19: HFRX Certificates, Momentum Model Without Costs Figure 20: HFRX Funds, Simple Momentum Model Without Costs m Rebalance 6m Rebalance 12M Rebalance 18

19 Figure 21: MSCI Lyxor Funds, Simple Momentum Model Without Costs Figure 22: FTSEhx Funds, Simple Momentum Model Without Costs M Rebalance 6m Rebalance 12M Rebalance 19

20 Figure 23: SPhinx Funds, Simple Momentum Model Without Costs m Rebalance 6M Rebalance 12M Rebalance Figure 24: HFRX Certificates, Simple Momentum Model With Costs

21 Figure 25: HFRX Funds, Simple Momentum Model With Costs m Rebalance 6m Rebalance 12M Rebalance Figure 26: MSCI Lyxor Funds, Simple Momentum Model With Costs

22 Figure 27: FTSEhx Funds, Simple Momentum Model With Costs M Rebalance 6m Rebalance 12M Rebalance Figure 28: SPhinx Funds, Simple Momentum Model With Costs m Rebalance 6M Rebalance 12M Rebalance 22

23 Figure 29: HFRX Certificates, Contra Model Without Costs Figure 30: HFRX Funds, Contra Model Without Costs m Rebalance 6m Rebalance 12M Rebalance 23

24 Figure 31: MSCI Lyxor Funds, Simple Contra Model Without Costs Figure 32: FTSEhx Funds, Contra Model Without Costs 45% 4 35% 3 25% 2 15% 1 5% -5% 3M Rebalance 6m Rebalance 12M Rebalance 24

25 Figure 33: SPhinx Funds, Contra Model Without Costs m Rebalance 6M Rebalance 12M Rebalance Figure 34: HFRX Certificates, Contra Model With Costs 14% 12% 1 8% 6% 4% 2% -2% -4% 25

26 Figure 35: HFRX Funds, Contra Model With Costs 5 45% 4 35% 3 25% 2 15% 1 5% -5% 3m Rebalance 6m Rebalance 12M Rebalance Figure 36: MSCI Lyxor Funds, Simple Contra Model With Costs

27 Figure 37: FTSEhx Funds, Contra Model With Costs 35% 3 25% 2 15% 1 5% -5% 3M Rebalance 6m Rebalance 12M Rebalance Figure 38: SPhinx Funds, Contra Model With Costs m Rebalance 6M Rebalance 12M Rebalance 27

28 3.2 Rachev Ratio Ranking Model Our second series of tests are made using portfolios formed on the basis of the Rachev Ratio as calculated over the measurement period prior to portfolio formation. Full details on the Rachev Ratio calculation and methodology are found in Biglova, Jasic, Rachev, & Fabozzi (2004). The Rachev Ratio is essentially ratio of the expected value; given a positive Value-At-Risk threshold being breached, to the expected value given a negative Value-At-Risk threshold has been breached. Estimation of the ratio can be made by taking the sample observations above a given percentile cutoff, calculating the average, and doing the same for the sample observations below a lower percentile cutoff. The Rachev Ratio is then the ratio of the two means. This methodology has the benefit of adjusting for both risk and non-normal distributions, as for example, samples which exhibit negative skew will receive lower Rachev ratios than samples emulating a normal distribution. In our tests, measurement periods cover ten monthly observations in all cases. As before however, the case where notice periods are required the most recent ten months of data which were known pro forma at the time an investment decision would be made were used. As only ten observations were used in each case, Rachev Ratios at the 90 % confidence level for both positive and negative Conditional Value-At-Risk have been estimated by taking the ratio of maximum and minimum of the each sample as estimates for the 1 Conditional VaR in each case. To correct for some mathematical issues arising from cases where all observations were on the same side of zero versus others whether they were not, 10 has been subtracted from all observations prior to and for the exclusive purpose of estimating Rachev Ratios for the purposes of generating ranking. While these adjustment mean that the numbers used are not explicitly the Rachev Ratios, the rankings generated are identical to those which would be generated by an explicit calculation as would be feasible with a larger sample set. In these tests, momentum models in all scenarios in our test period fail to generate returns which are as good as a simple buy and hold strategy. A more interesting result however is observed when the Rachev methodology is applied to a Contra/Reversal strategy. Under these scenarios, significantly better returns are found amongst the MSCI Lyxor and FTSEhx Funds. The overall results for Rachev and Momentum measures ratio are provided in Table 6 and Figures 39 through 48. For the results based on Rachev ratio and Contra Model performance, these are provided on Table 7 and in Figures 49 through 58. As the practical measures involved in implementing a Rachev ratio with Contra Model investing are likely to pose considerable operational risks as regards IHFI s, our main conclusion from these finding is that active management of investable indices is not an immediate choice. 28

29 Table 6: Rachev Momentum Model Performance With and Without Costs 6(a) Rachev Momentum Model Without Costs Notice Required Funds in Percentile 3M 6M 12M Avg HFRX Certificates. No Notice HFRX Funds 0-1 Month MSCI Lyxor 0-1 Month % 8.86% % FTSEhx Funds 1-2 Months % 4.54% 4.24% 4.42% SPhinX Funds 2-3 Months % 7.64% 6.71% 7.59% Average 6.89% 6.85% 6.57% 6.77% 6(b) Rachev Momentum Model With Costs Notice Required Funds in Percentile 3M 6M 12M Avg HFRX Certificates. No Notice % 4.19% 4.19% 4.19% HFRX Funds 0-1 Month % 5.18% 5.18% 5.18% MSCI Lyxor 0-1 Month % 5.76% 5.61% 5.6 FTSEhx Funds 1-2 Months % 3.44% 3.14% 3.32% SPhinX Funds 2-3 Months % 6.06% 5.16% 6.01% Average % 4.66% 4.86% Table 7: Rachev Contra Model Performance With and Without Costs 7(a( Rachev Contra Model Without Costs Notice Required Funds in Percentile 3M 6M 12M Avg HFRX Certificates. No Notice % 7.82% 7.93% HFRX Funds 0-1 Month % 7.34% 6.89% 7.0 MSCI Lyxor 0-1 Month % 12.68% 10.97% 12.62% FTSEhx Funds 1-2 Months % 9.86% 11.65% 9.78% SPhinX Funds 2-3 Months % 7.13% 8.65% 8.25% Average 9.01% 9.14% % 7(b) Rachev Contra Model With Costs Notice Required Funds in Percentile 3M 6M 12M Avg HFRX Certificates. No Notice % 5.25% 4.76% 4.55% HFRX Funds 0-1 Month % 5.91% 5.46% 5.57% MSCI Lyxor 0-1 Month % 11.13% 9.44% 11.07% FTSEhx Funds 1-2 Months % 8.71% 10.49% 8.63% SPhinX Funds 2-3 Months % 5.55% 7.04% 6.64% Average 7.13% 7.31% 7.44% 7.29% 29

30 Figure 39: HFRX Index Certificates- Rachev Momentum Without Costs 4 35% 3 Cumulative Return 25% 2 15% 1 5% Figure 40: HFRX Funds, Rachev Momentum Without Costs

31 Figure 41: MSCI Lyxor Funds, Rachev Momentum Without Costs Figure 42: FTSEhx Funds- Rachev Momentum Without Costs 25% 2 Cumulative Return 15% 1 5% 31

32 Figure 43: SPhinX Funds-Rachev Momentum Without Costs 5 45% 4 35% Cumulative Return 3 25% 2 15% 1 5% Figure 44: HFRX Index Certificates- Rachev Momentum With Costs 25% 2 Cumulative Return 15% 1 5% -5% 32

33 Figure 45: HFRX Funds, Rachev Momentum With Costs Figure 46: MSCI Lyxor Funds, Rachev Momentum With Costs

34 Figure 47: FTSEhx Funds- Rachev Momentum With Costs 18% 16% 14% Cumulative Return 12% 1 8% 6% 4% 2% Figure 48: SPhinX Funds-Rachev Momentum With Costs 4 35% 3 Cumulative Return 25% 2 15% 1 5% 34

35 Figure 49: HFRX Index Certificates- Rachev Contra Without Costs Cumulative Return Figure 50: HFRX Funds, Rachev Contra Without Costs

36 Figure 51: MSCI Lyxor Funds, Rachev Contra Without Costs Figure 52: FTSEhx Funds- Rachev Contra Without Costs Cumulative Return

37 Figure 53: SPhinX Funds- Rachev Contra Without Costs Cumulative Return Figure 54: HFRX Index Certificates- Rachev Contra With Costs 35% 3 25% Cumulative Return 2 15% 1 5% -5% 37

38 Figure 55: HFRX Funds, Rachev Contra With Costs Figure 56: MSCI Lyxor Funds, Rachev Contra With Costs

39 Figure 57: FTSEhx Funds- Rachev Contra With Costs Cumulative Return Figure 58: SPhinX Funds- Rachev Contra With Costs Cumulative Return

40 4. DISCUSSION AND REMARKS For our full sample period, before taking account of costs and fees, equal weight buy and hold portfolios yield annualized returns of 8.81%, 8.81%, 10.57%, 9.38% and 9.55% for HFRX Certificates, HFRX Funds, MSCI Lyxor Funds, FTSEhx Funds, and SPhinX Funds respectively, with a combined portfolio of our four index groups earning an average 9.42% per annum over this period. With costs and fees these returns fall to 6.35%, 7.36%, 9.05%, 8.24%, and 8.16% respectively, for a combined portfolio average return of 7.83%. The average effect of costs is a reduction in annualized return of 16.9 (Table 3). Table 3 Effect of Costs on Buy/Hold Return, Full Period Notice Required Funds Without Costs With Costs %Differential HFRX Certificates No Notice % 6.35% % HFRX Funds 0-1M Notice % 7.36% % MSCI Lyxor Funds 0-1M Notice % 9.05% % FTSEhx Funds 1-2M Notice % 8.24% % SPhinX Funds 2-3M Notice % 8.16% % Average 9.42% 7.83% Despite the effect of costs, in the majority of our tests momentum effects appear sufficiently strong to suggest superior returns to a buy/hold strategy (Table 4(b)). This however may be an anomalous situation as strategies that cannot markto-market on the basis of published market rates may be introducing an averaging effect in their valuations. Thus we reserve our views as to whether or not any such benefits exist in practice until more data and actual investment and valuation results can be examined. The presence of some negative serial correlations in certain strategies, such as Foreign Exchange (Forex) Trading and Managed Futures, also creates some situations in which a simple strategy of buying the poorest performers will outperform a buy and hold strategy as well (Table 5(b)). Forex Trading and Managed Futures tend to have real mark-to-market valuations which are readily achieved by reference to actual monthend closing prices as posted on futures exchanges and closing market rates of the Forex inter-bank market. The negative serial correlations are what would be expected in the other strategies if they too had firm and final end of month pricings. The concern we have therefore is that if any kind of valuation averaging (or price smoothing) is being introduced then the momentum benefits may be strictly due to valuation averaging effects rather than real correlated behavior. Of necessity some strategies require this approach to month-end valuations and these must be considered in their totality before any serial correlation or momentum related effects can be firmly concluded to apply in practice. Table 4(b) Simple Momentum Model With Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 11.18% 12.74% 11.14% HFRX Funds 0-1M Notice % 13.33% 13.31% 12.9 MSCI Lyxor Funds 0-1M Notice % 13.62% 11.66% 13.28% FTSEhx Funds 1-2M Notice % 9.75% 8.79% 8.41% SPhinX Funds 2-3M Notice % 9.75% 7.46% Average 9.41% 11.26% 11.25% 10.64% Table 5(b) Simple Contra Model With Costs Funds in Percentile Rebalance Frequency Notice Required 3M 6M 12M Average HFRX Certificates No Notice % 1.71% 1.64% HFRX Funds 0-1M Notice % 5.76% 7.69% 6.72% MSCI Lyxor Funds 0-1M Notice % 13.19% 11.57% 14.22% FTSEhx Funds 1-2M Notice % 5.79% SPhinX Funds 2-3M Notice % 8.36% 5.48% 9.12% Average 9.34% 7.06% 6.08% 7.49% 40

41 The results of our tests that employed the Rachev ratio, relative to results based on a momentum model show that after accounting for transaction costs, all scenarios considering the Rachev ratio test fail to generate returns greater than a buy and hold strategy. A more interesting result however is observed when the Rachev methodology is applied to a Contra/Reversal strategy (Table 7(b)). After transaction costs, returns in several scenarios are significantly higher than that under a buy/hold scenario. However for reasons already mentioned above these result may be anomalous as well. Table 7(b) Rachev Contra Model With Costs Notice Required Funds in Percentile 3M 6M 12M Average HFRX Certificates. No Notice % 5.25% 4.76% 4.55% HFRX Funds 0-1 Month % 5.91% 5.46% 5.57% MSCI Lyxor 0-1 Month % 11.13% 9.44% 11.07% FTSEhx Funds 1-2 Months % 8.71% 10.49% 8.63% SPhinX Funds 2-3 Months % 5.55% 7.04% 6.64% Average 7.13% 7.31% 7.44% 7.29% In overall terms and, based on the findings of this report, investing in Investable Hedge Fund Indices is not straight forward and many unresolved issues remain. Practical considerations are foremost. Investing on a Buy and Hold basis does not appear to offer an acceptable risk/reward position relative to established HFOF s. However, since the promoted benefit of Investable Hedge Fund Indices is to be based on Buy and Hold the findings of this report suggest that investors may not be able to actually realize the intended benefits from Buy and Hold and that are sufficiently beneficial on a risk/reward basis in practice due to the rather large discrepancies observed across the different investable indices for the same investment strategies. Introducing a Contra/Reversal strategy in practice is considered a very complex exercise as both operational and market risk issues will need complete assessments before pursuing any such efforts. Subscription and redemption notices are the biggest obstacles and appear for the most to not be any better than currently exist for investments in HFOF s. Perhaps the wisdom should be that two things attempting to do the same thing, albeit under different names, are unlikely to improve substantially over each other. Finally, the question of how well IHFI s fare relative to Hedge FOF s remains open. Given that there are considerable costs and fees associated with investments in IHFI s a separate comparison would be required to justify any remarks suggesting that IHFI s provide a more efficient or cost effective alternative to FOF s or HFOF s. Taking a simplified example based on the cost data presented in this report, we note there is room for considerable doubt to be cast over any absolute benefit to IHFI s over HFOF s (See Appendix A). Moreover, neither FOF s nor IHFI s have done well for investors during 2004, and with the added costs each of these have, poor performance has been exacerbated due to the multiple fee layers found in both FOF s and IHFI s. There is also a fairly wide degree of concern existing across the investor universe that the much touted large capacity promoted by IHFI s is not as simple as it sounds. The need to find underlying managers that are good and have capacity (and plenty of it) remains highly elusive. The concern being voiced by many would be investor s is therefore not entirely unreasonable. In simple terms that concern is, who are the managers being employed in the IHFI s? As established FOF s and HFOF s already have access to the top tier managers and the capacity of these managers is not generally infinite, then what is the basis of IHFI s for selecting the managers and capacity they have? A question we do not have any immediate answers for. If there was a completely affirmative answer, FOF s and HFOF s should be the biggest investors in IHFI s, but this does not appear to be the case. We conclude by highlighting a number of recently published exchanges as to what should be a rational basis for differentiating and defining appropriate attributes for FOF s, HFOF s and IHFI s. Jaeger (2004) notes that the dynamic and diverse characteristics of hedge funds bear contrast to assumptions underlying conventional index construction methods, that of homogenous underlying assets and investors who follow a buy and hold strategy. He demonstrates deviation between different index providers both at the broad index level and individual strategy level. He also notes that reporting biases exist which limit the usefulness of hedge fund data. Jaeger also sets out as important attributes of a good index as being: 1.) Unambiguously defined 2.) Representative 3.) Accurately measured 4.) Investable 41