Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK
FRB of St. Louis Working Paper No. 2007-016D
32 Pages Posted: 13 Apr 2007
Date Written: May 2008
Portfolio choice by full-scale optimization applies the empirical return distribution to a parameterized utility function, and the maximum is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory, under which full-scale optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality, the findings indicate much broader usefulness of full-scale optimization than has earlier been shown. The results hold in and out of sample, and the performance improvements are given in terms of utility as well as certainty equivalents.
Keywords: Portfolio choice, Utility maximization, Full-Scale Optimization, S-shaped utility, bilinear utility
JEL Classification: G11
Suggested Citation: Suggested Citation