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Stan Beckers Simon Weinberger

Stan Beckers Simon Weinberger Barclays Global Investors. Fundamental Factors in Hedge Fund Returns. Spitalfields Day Cambridge 10 March 2005. Overview. The Raw Data: Issues Skewness, Kurtosis and Autocorrelation

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Stan Beckers Simon Weinberger

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  1. Stan Beckers Simon Weinberger Barclays Global Investors Fundamental Factors in Hedge Fund Returns Spitalfields Day Cambridge 10 March 2005

  2. Overview • The Raw Data: Issues • Skewness, Kurtosis and Autocorrelation • Communality in Hedge Fund Returns • Systematic and Residual Factors

  3. 1. Hedge Fund Returns : Data Issues • Return data only (no transparency) • Bias in Pricing/ Returns • Survivorship Bias • Instant History Bias • Self-Reporting Bias • Short histories, low frequency data • Fund size ignored

  4. HFR Database : Fund inception date, Reporting start and end date

  5. Short histories

  6. Histogram of Hedge Fund AUM (Sept 2004): Not all funds are equally important

  7. 2. More data issues : these things aren’t normal !? • Skewness and Kurtosis • Downside Protection • Use of derivatives • Non-Linear Factors • Autocorrelation in return series • Data Smoothing

  8. Frequency Distribution Fixed Income Hedge Fund Index Returns 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 -2 -2.3 -3.5 -3.2 -2.9 -2.6 Skewness and Kurtosis 1 0.7 1.3 1.6 1.9 2.2 3.4 0.1 0.4 2.5 2.8 3.1 -1.7 -1.4 -1.1 -0.8 -0.5 -0.2 Standard Deviations

  9. Non-Linearity in Factors Period: January 1997- May 2004

  10. A Broad Cross Section of Funds Daily data

  11. A Broad Cross Section of Funds Monthly data

  12. Characteristics Return Distribution Fund X June 2002 – December 2004

  13. Characteristics Return Distribution Fund X January 1994 – June 2004

  14. 3. Looking for Communality in Hedge Fund Returns • Hedge Fund Styles as defined by the Index Providers • Self-Declared • Opportunistic • Statistical Approaches • Cluster Analysis • Principal Component Analysis

  15. The HFR Hedge Fund Style Classification HFRI Convertible Arbitrage Index HFRI Distressed Securities Index HFRI Emerging Markets (Total) HFRI Equity Hedge Index HFRI Equity Market Neutral Index HFRI Equity Non-Hedge Index HFRI Event-Driven Index HFRI Fixed Income (Total) HFRI Fixed Income: Arbitrage Index HFRI Fixed Income: Convertible Bonds Index HFRI Fixed Income: Diversified Index HFRI Fixed Income: High Yield Index HFRI Fixed Income: Mortgage-Backed Index HFRI Macro Index HFRI Market Timing Index HFRI Merger Arbitrage Index HFRI Relative Value Arbitrage Index HFRI Short Selling Index

  16. Defining the Number of Hedge Fund Styles: Cluster Analysis[1] [1] We require 60 months of data (199907-200406), which leaves us with 676 funds for this analysis.

  17. Defining the Number of Hedge Fund Styles: Average Return Correlation with Peers

  18. Defining the Number of Hedge Fund Styles: Explanatory Power of first Principal Component

  19. HFR Hedge Fund Style Classification

  20. Correlation Structure with Peers and Non-Peers Histograms of average correlation with peers (same hedge fund style) versus non-peers

  21. Cluster Analysis within Broadly Defined Styles

  22. 4. Dissecting Within-Style Hedge Fund Returns: Systematic and Residual factors • A Primer on Multiple Factor Models • Differentiating between Alpha and Beta • Identifying systematic factors • Principal Component analysis • Fundamental Factors • Where is the hedge?

  23. The Academic Background on Multiple Factor Models • The CAPM • Single Factor : The Market Portfolio • APT : Multiple Factors • Factors Undefined but the academic world would probably agree that – for equities - they include • Small versus Large • Value Versus Growth • Momentum • Broad Approaches for Factor Indentification • Macro-Economic Models • Fundamental Models • Statistical Models • Virtually all models are Linear

  24. Factor Model Selection Criteria • Academically Sound? • Best Fit? • Economic Interpretation? • Out of sample explanatory power? • Tradeable?

  25. A First Cut at Identifying Factors within each Style: Principal Component Analysis

  26. Selected Findings from the Hedge Fund Literature • Equity Strategies tend to have market exposure and exposure to Fama/French Factors SMB and HML (among others Fung and Hsieh, 2003) • 30% of market-neutral funds have market risk exposure (Patton, 2004) • Option Strategies have explanatory power for non-directional strategies (Agarwal and Naik, 2000) • Trend Following Strategy exhibits payoff similar to by lookback straddle (Fung and Hsieh, 2001) • Merger Arbitrage exhibits payoff like uncovered put on Equity Index (Mitchell and Pulvino, 2000)

  27. Mean/Median Forecast Error at successive steps Equity Hedge Funds

  28. Explanatory power of a factor risk model (Equity Funds) Median : 35% in sample, 23% out of sample Truncated Median: 41% in sample, 34% out of sample

  29. Equity Hedge Fund In-Sample Alpha

  30. Mean/Median Forecast Error at successive steps Fixed Income Hedge Funds

  31. Explanatory power of a factor risk model (Fixed Income Funds) Histogram of in-sample (199401-200406) and out-of-sample fit (regression of fund returns on return explained by risk model (product sum of prevailing exposure estimate and realised factor return)Median* disregards observations with extreme fit (<10% or >70%).

  32. Fixed Income Fund In Sample Alpha Fund-level rolling 36m estimation

  33. HFR Hedge Fund Index Returns: Where is the Hedge?T-Stat of Systematic Factors

  34. Summary • Given the Quality of the Data, all Hedge Fund Empirical Research has to be taken with a pinch of salt • Skewness, Kurtosis and Autocorrelation are less of an issue than some people would lead you to believe • Hedge Fund Styles are not clearly delineated and somewhat arbitrary • Even so, Common factors can be identified within broad hedge fund style classifications • Significant systematic factors are present in most hedge fund returns • Alpha does remain after taking systematic factors into account • Hedge Fund is somewhat of a misnomer

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