Hedge fund performance prediction

61 Pages Posted: 11 Sep 2017 Last revised: 16 Jul 2019

See all articles by Nicolas P. B. Bollen

Nicolas P. B. Bollen

Vanderbilt University - Finance

Juha Joenväärä

Aalto University School of Business; University of Maryland - Robert H. Smith School of Business

Mikko Kauppila

University of Oulu

Date Written: June 5, 2019

Abstract

This paper studies the forecasting power of a comprehensive set of hedge fund performance predictors introduced in prior research. Several predictors based on skill and incentives select top quintiles that significantly outperform bottom quintiles. The benefit realized by investors deteriorates after reversing upward biases in returns and constraining the number of funds selected. In a multi-asset class portfolio, seven of the predictors reliably select funds that raise the Sharpe ratio compared to a stock/bond portfolio over the 1997 – 2016 sample. Hedge fund allocations reduce volatility robustly through time, but leave the Sharpe ratio unchanged in the 2008 – 2016 sub-period.

Keywords: hedge fund performance

JEL Classification: G11, G12, G14, C31

Suggested Citation

Bollen, Nicolas P.B. and Joenvaara, Juha and Kauppila, Mikko, Hedge fund performance prediction (June 5, 2019). Vanderbilt Owen Graduate School of Management Research Paper No. 3034283. Available at SSRN: https://ssrn.com/abstract=3034283 or http://dx.doi.org/10.2139/ssrn.3034283

Nicolas P.B. Bollen (Contact Author)

Vanderbilt University - Finance ( email )

401 21st Avenue South
Nashville, TN 37203
United States

Juha Joenvaara

Aalto University School of Business ( email )

Finland

University of Maryland - Robert H. Smith School of Business ( email )

MD
United States

Mikko Kauppila

University of Oulu ( email )

P.O. Box 4600
Oulu FIN-90014
Finland

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