Optimal Hedge Fund Allocation with Asymmetric Preferences and Distributions

45 Pages Posted: 4 May 2006

See all articles by Ivilina Popova

Ivilina Popova

Texas State University

Elmira Popova

University of Texas at Austin

David Morton

University of Texas at Austin - College of Engineering

Jot Yau

Seattle University

Date Written: May 1, 2006

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, and thus fail to convince investors who care about the unwanted skewness and kurtosis that hedge funds may work well in a portfolio. We use a new method which incorporates Monte Carlo simulation and optimization to solve for a variety of investment objectives and address the special issues of hedge fund allocation. We applied the new optimization model to examine the effects of semi-variance, conditional third and fourth moments on portfolio allocation with hedge funds. We show that conditional on the investor's objective, a substantial allocation to hedge funds is justified even with consideration for the highly unusual skewness and kurtosis.

Suggested Citation

Popova, Ivilina and Popova, Elmira and Morton, David and Yau, Jot, Optimal Hedge Fund Allocation with Asymmetric Preferences and Distributions (May 1, 2006). Available at SSRN: https://ssrn.com/abstract=900012 or http://dx.doi.org/10.2139/ssrn.900012

Ivilina Popova (Contact Author)

Texas State University ( email )

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

HOME PAGE: http://https://faculty.txst.edu/profile/520678

Elmira Popova

University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 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