Mean-Semivariance Optimization: A Heuristic Approach

16 Pages Posted: 9 Dec 2015

Multiple version iconThere are 2 versions of this paper

Date Written: December 3, 2015

Abstract

Academics and practitioners optimize portfolios using the mean-variance approach far more often than the mean-semivariance approach, despite the fact that semi-variance is often considered a more plausible measure of risk than variance. The popularity of the mean-variance approach follows in part from the fact that mean-variance problems have well-known closed-form solutions, whereas mean-semivariance optimal portfolios cannot be determined without resorting to obscure numerical algorithms. This follows from the fact that, unlike the exogenous covariance matrix, the semi-covariance matrix is endogenous. This article proposes a heuristic approach that yields a symmetric and exogenous semi-covariance matrix, which enables the determination of mean-semivariance optimal portfolios by using the well-known closed-form solutions of mean-variance problems. The heuristic proposed is shown to be both simple and accurate.

Suggested Citation

Estrada, Javier, Mean-Semivariance Optimization: A Heuristic Approach (December 3, 2015). Journal of Applied Finance (Formerly Financial Practice and Education), Vol. 18, No. 1, 2008, Available at SSRN: https://ssrn.com/abstract=2698700

Javier Estrada (Contact Author)

IESE Business School ( email )

IESE Business School
Av. Pearson 21
Barcelona, 08034
Spain
+34 93 253 4200 (Phone)
+34 93 253 4343 (Fax)

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