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

90 Pages Posted: 20 Mar 2003 Last revised: 26 Feb 2021

See all articles by Mila Getmansky Sherman

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) - Laboratory for Financial Engineering; Santa Fe Institute

Igor Makarov

London School of Economics & Political Science (LSE)

Multiple version iconThere are 2 versions of this paper

Date Written: March 2003

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.

Suggested Citation

Getmansky Sherman, Mila 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: https://ssrn.com/abstract=387578

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) - Laboratory for Financial Engineering ( 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

Santa Fe Institute

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Igor Makarov

London School of Economics & Political Science (LSE) ( email )

Houghton Street
London, WC2A 2AE
United Kingdom

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