Efficient skewness/semivariance portfolios

Abstract

This article proposes a flexible methodology for portfolio selection using a skewness/semivariance biobjective optimisation framework. The solutions of this biobjective optimisation problem allow the investor to analyse the efficient trade-off between skewness and semivariance. This methodology is used empirically on four data sets, collected from the Fama/French data library. The out-of-sample performance of the skewness/semivariance model was assessed by choosing three portfolios belonging to each in-sample Pareto frontier and measuring their performance in terms of skewness per semivariance ratio, Sharpe ratio and Sortino ratio. Both the in-sample and the out-of-sample performance analyses were conducted using three different target returns for the semivariance computations. The results show that the efficient skewness/semivariance portfolios are consistently competitive when compared with several benchmark portfolios.