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An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns


Mila Getmansky Sherman


University of Massachusetts at Amherst - Eugene M. Isenberg School of Management - Department of Finance

Andrew W. Lo


Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)

Igor Makarov


London Business School

March 2003

NBER Working Paper No. w9571

Abstract:     
The returns to hedge funds and other alternative investments are often highly serially correlated in sharp contrast to the returns of more traditional investment vehicles such as long-only equity portfolios and mutual funds. In this paper, we explore several sources of such serial correlation and show that the most likely explanation is illiquidity exposure, i.e., investments in securities that are not actively traded and for which market prices are not always readily available. For portfolios of illiquid securities, reported returns will tend to be smoother than true economic returns, which will understate volatility and increase risk-adjusted performance measures such as the Sharpe ratio. We propose an econometric model of illiquidity exposure and develop estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds drawn from the TASS database, we show that our estimated smoothing coefficients vary considerably across hedge-fund style categories and may be a useful proxy for quantifying illiquidity exposure.

Number of Pages in PDF File: 90

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Date posted: March 20, 2003  

Suggested Citation

Sherman, Mila Getmansky and Lo, Andrew W. and Makarov, Igor, An Econometric Model of Serial Correlation and Illiquidity in Hedge Fund Returns (March 2003). NBER Working Paper No. w9571. Available at SSRN: http://ssrn.com/abstract=387578

Contact Information

Mila Getmansky Sherman
University of Massachusetts at Amherst - Eugene M. Isenberg School of Management - Department of Finance ( email )
Amherst, MA 01003-4910
United States
Andrew W. Lo (Contact Author)
Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )
100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)
HOME PAGE: http://web.mit.edu/alo/www
Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)
Stata Center
Cambridge, MA 02142
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Igor Makarov
London Business School ( email )
Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom
+44 (0)20 7000 8265 (Phone)
+44 (0)20 7000 8201 (Fax)
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