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

See all articles by Björn Hagströmer

Björn Hagströmer

Stockholm University - Stockholm Business School

Richard G. Anderson

Federal Reserve Bank of St. Louis - Research Division

Jane M. Binner

University of Birmingham - Department of Accounting and Finance

Thomas Elger

Lund University

Birger Nilsson

Lund University - Department of Economics

Date Written: May 2008

Abstract

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

Hagströmer, Björn and Anderson, Richard G. and Binner, Jane M. and Elger, Thomas and Nilsson, Birger, Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK (May 2008). FRB of St. Louis Working Paper No. 2007-016D. Available at SSRN: https://ssrn.com/abstract=979811 or http://dx.doi.org/10.2139/ssrn.979811

Björn Hagströmer (Contact Author)

Stockholm University - Stockholm Business School ( email )

Stockholm
Sweden

Richard G. Anderson

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

Jane M. Binner

University of Birmingham - Department of Accounting and Finance ( email )

Birmingham, B15 2TY
United Kingdom

Thomas Elger

Lund University ( email )

Box 117
Lund, SC Skane S221 00
Sweden

Birger Nilsson

Lund University - Department of Economics ( email )

P.O. Box 7082
S-220 07 Lund
Sweden

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