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

Bjorn Hagstromer, Richard G. Anderson, Jane Binner (), Thomas Elger () and Birger Nilsson ()
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Jane Binner: Aston Business School, Postal: Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK, http://www.abs.aston.ac.uk/newweb/staff/detail.asp?sfldStaffID=A0000477
Birger Nilsson: Department of Economics, Lund University, Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund, Sweden, http://www.nek.lu.se/NEKBNI/

No 2008:1, Working Papers from Lund University, Department of Economics

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 (search for similar items in EconPapers)
JEL-codes: G11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-upt
Date: 2007-10-24
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Published in The Manchester School, 2008, pages 134-156.

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Working Paper: Mean-variance vs. full-scale optimization: broad evidence for the U.K (2007)
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