Mean-Variance Versus Full-Scale Optimization: Broad Evidence For The Uk
AbstractPortfolio 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. Copyright � 2008 The Authors. Journal compilation � 2008 Blackwell Publishing Ltd and The University of Manchester.
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Bibliographic InfoArticle provided by University of Manchester in its journal Manchester School.
Volume (Year): 76 (2008)
Issue (Month): s1 (09)
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- David Johnstone & Dennis Lindley, 2013. "Mean-Variance and Expected Utility: The Borch Paradox," Papers 1306.2728, arXiv.org.
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