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The Brave New World of Hedge Fund Indexes Desperately Seeking Pure Style Indexes. Lionel Martellini Marshall School of Business University of Southern California Chercheur Associé EDHEC martelli@usc.edu Joint work with Noël Amenc.
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The Brave New World of Hedge Fund Indexes Desperately Seeking Pure Style Indexes Lionel Martellini Marshall School of Business University of Southern California Chercheur Associé EDHEC martelli@usc.edu Joint work with Noël Amenc © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Outline • Motivation • Performance Mesurement and Asset Allocation • Problems with Hedge Fund Indexes • The World of Hedge Fund Indexes • Overview of Popular Hedge Fund Strategies • Survey of Existing Hedge Fund Indexes • Hedge Fund Indexes are not Created Equal • Heterogeity in Competing Hedge Fund Index Returns • Implications for Asset Allocation • Desperately Seeking Pure Style Indexes • Statistical Approach • Portfolio Approach • How Pure is Pure? • The Two Basic Theorems of Pure Indexing • Testing Representativeness of Pure Indexes © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Motivation From an Absolute to a Relative Return Perspective • HF managers often use risk-free rate as a benchmark • This absolute return approach is theoretically valid if and only if • CAPM is the true model • Hedge fund beta is zero • Hedge fund indexes and sub-indexes are a natural choice for benchmarking hedge fund returns • Right benchmarking is a fundamental problem in the presence of incentive fees • Reliable HF indexes are also needed for • Strategic Asset Allocation • Tactical Asset Allocation © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Universe of Equity (20000+) MSCI Sub-Universe Russell Sub Universe Wilshire Sub-Universe (5000 approx) S&P Indices (value, growth) Russell Indices (growth,value) Motivation Equity Universe, Sub-Universes, and Specialized Indexes • Composite of World Unknown • Sub-universe (e.g., MSCI) may or may not represent World Index • Competing indexes for the same universe © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
MotivationHF Universe, Sub-Universes, and Specialized Indexes Zurich Sub-Universe (1300 approx) Universe of Hedge Funds (6000+) Zurich Hedge Fund Indices CSFB/Tremont Index TASS Sub-Universe EACM 100 HFR Sub Universe • Composite of World Unknown • Sub-universe (e.g., HFR, TASS) may or may not represent World Index • Competing indexes for the same universe © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Motivation Problems are Amplified for Hedge Fund Indexes • Existing indexes are not fully representative • Because of the lack of regulation on hedge fund performance disclosure, existing data bases only cover a relatively small fraction of the hedge fund population • Probably only a little more than half of existing hedge funds choose to self-report their performance to one of the major hedge fund databases • One of the most popular hedge fund indexes, the EACM 100, does not account for more than a tiny percentage of all existing hedge funds • Most HF indexes are equally-weighted (all but CSFB/Tremont) • Existing indexes are biased • Most hedge fund indexes are based upon managers' self-proclaimed styles • Given that hedge fund managers jealously protect the secret of their investment strategies (the so-called black-box problem), relying on managers' self-proclaimed style is actually almost a necessity • This procedure only makes sense under the following two conditions: (1) a manager follows a unique investment and (2) a manager's self-proclaimed style matches the manager's actual trading strategies • Style drift problem (see for example Lhabitant (2001)) © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Population of hedge funds following a given strategy Lack of representativeness Sample of hedge funds in the database used by a given commercial index Presence of a style bias MotivationPure Style Indexes are not Observable © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
World of HF Indexes – Popular StrategiesHedge Funds Classification © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
World of HF Indexes – Popular StrategiesHedge Funds Styles • Directional strategies: aimed at benefiting from market movements and trends • Global macro • Hedge (long bias) • Long (e.g. “growth” or “value” stocks) • Short (e.g. “overvalued”, “glamour” stocks) • Non directional strategies: • Event driven (corporate events such as takeovers, spin-offs, mergers, etc.) • Restructuring (buying or shorting securities of companies under Chapter 11 and/or undergoing some form of reorganization) • Fixed-income arbitrage (long and short via treasuries, corporate and/or asset-backed securities) • Capital structure arbitrage (buying and selling different securities of the same issuer, e.g., convertibles/common stock) • Equity market neutral (long-short zero beta strategies) © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
World of HF Indexes – Competing ProvidersThere exist at least a Dozen HF Index Providers © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
World of HF Indexes – Competing ProvidersStrategies Covered in this Paper © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
World of HF Indexes – Competing ProvidersStrategies Not Covered in this Paper ©Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Hedge Fund Indexes are not Created EqualHeterogenity in Hedge Fund Indexes – Max Difference © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Hedge Fund Indexes are not Created EqualHeterogeity in Hedge Fund Indexes – Correlation © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Hedge Fund Indexes are not Created EqualImplications for Asset Allocation Efficient frontiers based on monthly data for the period extending from January 1996 to October 2001 © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesInvestment in Hedge Funds • Problems • Competing indexes disagree • All are potentially flawed • Can not tell which is best • All existing indexes have both advantages and drawbacks • For example, Zurich indexes may be less biased than some of their competitors, but they are less representative • Statistical approach • Portfolio approach • Maximization of Representativeness • Minimization of Bias © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesStatistical Approach – Kalman Filter • Simple model • Rkt is the return on competing index k • It is the (unobservable) return on pure index • ekt is the noise, measurement error resulting from presence of biases and absence of representativeness • Assume normally distributed pure indexes and measurement errors • Kalman filter is used both to evaluate the likelihood function and to forecast and smooth the unobserved state variables • Here, our motivation is to estimate (smooth) the unobserved pure index, based on the observed returns on competing indexes: © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesStatistical Approach – The Results Performance of Kalman filter pure index (in parenthesis, the average of competing index) © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesStatistical Approach – Convertible Arbitrage © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – The Method • Black-Box problem • A pure index generated Kalman filtering techniques has an appealing built-in element of optimality (minimized mean squared error) • It can not, however, be regarded as index in its own right, since it can not be expressed as a portfolio of individual hedge funds • Portfolio approach • Taking a portfolio of existing indexes should intuitively be better than selecting any of them • Is equally-weighting a good scheme? • Maximization of representativeness • Principal component analysis • Minimization of bias • Minimum-variance analysis © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – PCA • Use factor analysis techniques to generate a set of pure indexes • They can be thought of as the best possible one-dimensional summaries of information conveyed by competing indexes for a given style, in the sense of the larger fraction of the variance explained. • Here, we are looking for the portfolio weights that make the combination of competing indexes capture the largest possible fraction of the information contained in the data from the various competing indexes • The method • From a mathematical standpoint, it involves transforming a set of K correlated competing indexes into a set of orthogonal variables, or implicit factors, which reproduces the original information present in the correlation structure • Each implicit factor is defined as a linear combination of original variables • Use the first component of a PCA of competing indexes as a candidate for a pure style index (typically captures a large proportion of cross-sectional variations because competing styles tend to be at least somewhat positively correlated) © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPCA – The Results © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – Min Var Analysis • Pure hedge fund indexes generated as the first component in a factor analysis should be as representative as possible since there is no other linear combination of competing indexes that implies a lower information loss • Another approach consists in focusing on minimization of the bias • Use same model as before • Add assumptions • Noise term is zero on average • Noise term is uncorrelated with return on pure index • Homoscedastic model © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – Min Var Analysis • Define the return on a portfolio of indexes • Under previous assumptions, we have that • The problem of minimizing the bias is • Solution is © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – Additional Assumption • If one is willing to make the additional assumption of no correlation between noise terms for various competing indexes, then the variance-covariance matrix of residuals is diagonal, and one obtains the following simple solution • May also impose positivity constraints to ensure that resulting index is a long-only portfolio of individual hedge funds © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Desperately Seeking Pure Style IndexesPortfolio Approach – Additional Assumption © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Index 1 Index 2 Index 3 How Pure is Pure?The Two (Obvious) Theorems of Pure Indexing • PCA and min-var analysis have appealing element of optimality • However, any portfolio (e.g., equally-weighted portfolio) should perform better than competing indexes • Theorem 1: An index of the indexes is always less biased than the average of the set of indexes it is extracted from • Theorem 2: An index of the indexes is always more representative than any competing index © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
How Pure is Pure?Testing Representativeness – The Method • Reduction of bias is very hard to test (chicken-and-egg problem) • We have tested enhancement of representativeness using the following test experiment • We have merged the 3 major databases providing information on individual fund return (MAR, TASS and HFR) • We have also added data on funds which do not report to any data base, that had been directly obtained from administrators • We have gathered monthly returns on a total of 7,422 hedge funds, including 2,317 funds that do not report their returns to the major data bases • We have formed equally-weighted portfolios for each style based on managers’ self-proclaimed styles and compute correlation with pure indexes • These portfolios are • Arguably biased • Undoubtly representative © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
How Pure is Pure?Testing Representativeness – The Results © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02
Conclusion • Contribution • Document heterogeneity in competing hedge fund index providers • Attempt to provide remedies to the problem • Extensions • We have suggested that a database of pure style indexes be maintained at the EDHEC-MISYS Risk and Asset Management Research Center, and posted on a dedicated web site • The index construction methodology • Step 1: Use the first 3 years of monthly returns to calibrate the model. • Step 2: Perform a PCA analysis of competing indexes for each strategy on the data used for calibration purposes • Step 3: These portfolios are held for 3 months, their monthly returns are recorded, and the same process is repeated • Our results can easily be extended to traditional investment styles such as growth/value, small-cap/large-cap © Edhec 2002 Mesure de la Performance et des Risques de la Gestion Alternative 18/06/02