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Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK
Stockholm University, Faculty of Social Sciences. Stockholm University, Faculty of Social Sciences, School of Business. (Finance)
Federal Reserve Bank of St Louis. (Economics Research)
Aston Business School. (Economics Department)
Lund University. (Economics Department)
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2008 (English)In: Manchester School, ISSN 1463-6786, E-ISSN 1467-9957, Vol. 76, 134-156 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2008. Vol. 76, 134-156 p.
National Category
Business Administration
Research subject
Business Administration
URN: urn:nbn:se:su:diva-43257OAI: diva2:355089
Available from: 2010-10-05 Created: 2010-10-05 Last updated: 2010-10-15Bibliographically approved

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Hagströmer, Björn
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