Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK

[Back]

Published in The Manchester School, 2008, vol. 76, 134-156.

Abstract: In the Full-Scale Optimization approach the complete empirical financial return probability distribution is considered and the utility maximizing solution 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