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Optimizing Benchmark-Based Portfolios with Hedge Funds

41 Pages Posted: 24 May 2007  

Ivilina Popova

Texas State University - San Marcos

Elmira Popova

University of Texas at Austin

David Morton

University of Texas at Austin - College of Engineering

Jot Yau

Seattle University

Abstract

Hedge funds typically have non-normal return distributions marked by significant positive or negative skewness and high kurtosis. Mean-variance optimization models ignore these higher moments of the return distribution. If a mean-variance optimization model suggests significant allocation to hedge funds, an investor concerned about unwanted skewness and kurtosis is rightfully skeptical. We apply a new stochastic programming model which incorporates Monte Carlo simulation and optimization to examine the effects on the optimal allocation to hedge funds given benchmark related investment objectives: expected shortfall, semi-variance as well as the third and fourth moments of the shortfall. Our results show that a substantial allocation - approximately 20% - to hedge funds is justified even after taken into consideration their unusual skewness and kurtosis. Moreover, results also show that our method produces a fund of funds with desired features. Specifically, our portfolios' return distributions skew to the right relative to those of the optimal mean-variance portfolios, resulting in higher Sortino ratios. Additionally, an out-of-sample backtest shows that our optimal benchmark-based portfolio achieves its goal - beating the selected benchmark.

Suggested Citation

Popova, Ivilina and Popova, Elmira and Morton, David and Yau, Jot, Optimizing Benchmark-Based Portfolios with Hedge Funds. Available at SSRN: https://ssrn.com/abstract=988176 or http://dx.doi.org/10.2139/ssrn.988176

Ivilina Popova (Contact Author)

Texas State University - San Marcos ( email )

601 University Drive
San Marcos, TX 78666-4616
United States

HOME PAGE: http://www.business.txstate.edu/users/ip12/

Elmira Popova

University of Texas at Austin ( email )

Austin, TX 78712
United States

David Morton

University of Texas at Austin - College of Engineering ( email )

1 University Station
Austin, TX 78712-1179
United States

Jot Yau

Seattle University ( email )

901 12th Avenue
Seattle, WA 98122
United States

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