Intelligent Hedge Fund Investing
Successfully Avoiding Pitfalls through Better Risk Evaluation
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John Okunev and Derek White


A repeating theme in this volume is that what you get with hedge fund investments may be more than what you see and that may not be a good thing. The extensive literature on hedge fund styles, to which Okunev and White add their voice here, is an attempt to reveal more about hedge fund risk and return than is found in standard measures used in the mutual fund industry.

Okunev and White provide a method for correcting reported hedge fund returns for “smoothing,” in part an artifact of infrequent trading and illiquid pricing of positions taken by the fund managers. Their methodology for removing first and second order autocorrelations this effect shows that “de-smoothed” hedge fund index returns may have as much as two times the volatility as the originally reported returns for some categories of hedge funds.

They then use their de-smoothed returns to identify linear and non-linear (i.e., option-like) risk factors that best explain the returns. By associating hedge fund index returns with factors, investors can understand the actual risk drivers behind those returns. It may be the case that hedge fund categories have returns explained by similar risk drivers, even when their measured correlations are low.

Okunev and White find, just as others have recently found, that nonlinear factors are important to understanding the distribution of hedge fund index returns. In particular, short option structures consistently appear in the explanation of returns.

The finding of important non-linear effects motivates the use of value-at-risk historical simulations to estimate the risk in hedge fund indexes. The historical simulation value-at-risk approach lets the data speak for itself in measuring risk. Okunev and White use the estimated risk factor mappings from their style analysis in risk estimation.

The de-smoothed returns are likely a better historical record than the reported returns. But for risk estimation a forward looking estimation is required. The risk factor mappings indicate how a hedge fund return will respond to specific future realizations of possible market movements. Therefore a simulation using the factor mappings will simulate the effects of the trading dynamics that take place, and provide a more truthful estimate of likely future extreme returns.

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  1. Ackermann, C., R. McEnally and D. Ravenscraft, 1999, “The Performance of Hedge Funds: Risk, Return, and Incentives” The Journal of Finance, 54, 833-874.
  2. Agarwal, V. and N.Y. Naik, 2004, Risks and Portfolio Decisions Involving Hedge Funds, Review of Financial Studies 17, 63 – 98.
  3. Asness, C., J. Liew, and R. Krail, 2001, "Do Hedge Funds Hedge?," Journal of Portfolio Management, Fall, pp. 6?19.
  4. Brooks, C. and H. Kat, 2002, "The Statistical Properties of Hedge Fund Index Returns and Their Implications for Investors," Journal of Alternative Investments, Fall, pp. 26-44.
  5. Brown, S. J., 1989, "The number of factors in security returns," Journal of Finance, 44, pp. 1247 – 1262.
  6. Brown, S. J., and W. Goetzmann, 2003, "Hedge Funds with Style", Journal of Portfolio Management, 29(2), pp. 101-112.
  7. Brown, S.J., W.N. Goetzmann, and R.G. Ibbotson, 1999, "Offshore Hedge Funds: Survival and Performance 1989-95," Journal of Business 72(1), 91-117.
  8. Buetow G. W., R. R. Johnson, and D. E. Runkle, 2000, "The Inconsistency of Return-Based Style Analysis," Journal of Portfolio Management, 26(3), 61 – 77.
  9. Fama, E., and K. French, 1993, "Common Risk Factors in the Returns on Stocks and Bonds," Journal of Financial Economics, 33, PP. 3 – 56.
  10. Fung, W., and Hsieh D., 1997, "Empirical Characteristics of Dynamic Trading Strategies", Review of Financial Studies, 10, pp. 275-302.
  11. Fung, W. and Hsieh, D. A., 2000, "Performance Characteristics of Hedge Funds and Commodity Funds," Journal of Financial and Quantitative Analysis, 35(3), pp. 291-307.
  12. Fung, W., and Hsieh D., 2001, "The Risk in Hedge Fund Strategies: Theory and Evidence from Trend Followers," Review of Financial Studies, 14 (June), 313-341.
  13. Fung, W. and Hsieh, D. A., 2002, "Asset-Based Style Factors for Hedge Funds," Financial Analysts Journal 58(5), pp. 16 – 27.
  14. Fung, W. and Hsieh, D. A., 2002, “Risk in Fixed-Income Hedge Fund Styles. The Journal of Fixed Income, (September), pp. 6-27
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  16. Geltner, D., 1993, "Estimating Market Values From Appraisal Values Without Assuming an Efficient Market," Journal of Real Estate Research 8, PP. 325 – 345.
  17. Getmansky, M., A. W. Lo, and I. Makarov, 2003, "An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns, Working paper, MIT Sloan School of Management.
  18. Glosten, L., and R. Jagannathan, 1994, "A Contingent Claim Approach to Performance Evaluation," Journal of Empirical Finance 1, pp. 133 – 160.
  19. Grinblatt, M., and S. Titman, 1989, "Portfolio Performance Evaluation: Old Issues and New Insights," Review of Financial Studies 2, pp. 393 – 421.
  20. Henriksson, R.D. and R.C. Merton, 1981, “On Market Timing and Investment Performance II: Statistical Procedures for Evaluating Forecasting Skills", Journal of Business, pp. 54, 513-533.
  21. Jensen, M.C., 1968, "The Performance of Mutual Funds in the Period 1945 – 1964," Journal of Finance 23, pp. 389 – 416.
  22. Jorion, P., 2000, "Risk Management Lessons From Long Term Capital Management," European Financial Management 6, pp. 277-300.
  23. Kat, H. M., and S. Lu, 2002, "An Excursion Into the Statistical Properties of Hedge Fund Returns," Working paper, The University of Reading.
  24. Liang, B., 2000, “Hedge Funds: The Living and the Dead", Journal of Financial and Quantitative Analysis, 35, pp. 309-326.
  25. Lo, A., 2001, "Risk Management for Hedge Funds: Introduction and Overview," Financial Analysts Journal 57, pp. 16–33.
  26. Lo, A., 2002, "The Statistics of Sharpe Ratio," Financial Analyst Journal, 58(4), pp. 36-52.
  27. Merton, R.C., 1981, “On Market Timing and Investment Performance I: An Equilibrium Theory of Value for Market Forecasts", Journal of Business, 54, pp. 363-406.
  28. Mitchell, M. and T. Pulvino, 2001, “Characteristics of Risk and Return in Risk Arbitrage", The Journal of Finance, 56, 2135-2175.
  29. MSCI, 2002, "Hedge fund indices: Manager guide to classification", mimeo.
  30. Okunev, J. and D. White, 2003, "Hedge Fund Risk Factors and Value at Risk of Credit Trading Strategies," working paper.
  31. Sharpe, W.F., 1992, “Asset Allocation: Management Style and Performance Measurement", The Journal of Portfolio Management (Winter), pp. 7-19.
  32. Treynor, J.L. and K.K. Mazuy, 1966, “Can Mutual Funds Outguess the Market", Harvard Business Review, 44, pp. 131-136.
  33. Ineichen, A., 2000, "In Search of Alpha: Investing in Hedge Funds," working paper, UBS Warburg.

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  1. Other research by John Okunev:
    SSRN website
  2. Other research by Derek White:
    SSRN website

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Table of Contents


"How exciting to read a book that is so timely and practical"
Tanya Styblo Beder, CEO, Tribeca Investments

Publisher: Risk Books
Hardcover: 470 pages
ISBN: 19044339220

Editor: Barry Schachter
(US$ 153.00)
(GBP 85.00)

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© 2004 Barry Schachter