Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK
AbstractIn 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.
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Bibliographic InfoPaper provided by Lund University, Department of Economics in its series Working Papers with number 2008:1.
Length: 32 pages
Date of creation: 24 Oct 2007
Date of revision:
Publication status: Published in The Manchester School, 2008, pages 134-156.
Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/
More information through EDIRC
portfolio choice; utility maximization; full-scale optimization; S-shaped utility; bilinear utility;
Other versions of this item:
- Björn Hagströmer & Richard G. Anderson & Jane M. Binner & Thomas Elger & Birger Nilsson, 2007. "Mean-variance vs. full-scale optimization: broad evidence for the U.K," Working Papers 2007-016, Federal Reserve Bank of St. Louis.
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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