Björn Hagströmer (bjh@fek.su.se), Richard G. Anderson (anderson@stls.frb.org), Jane Binner (j.m.binner@sheffield.ac.uk), Thomas Elger and Birger Nilsson (birger.nilsson@nek.lu.se)
Additional contact information
Björn Hagströmer: School of Business, Stockholm University, Postal: School of Business , Stockholm University, SE-106 91 STOCKHOLM, Sweden
Richard G. Anderson: Federal Reserve Bank of St. Louis, Postal: Research Division, Federal Reserve Bank of St. Louis, P.O. Box 442, St. Louis, MO 63166-0442, USA
Jane Binner: Sheffield University
Thomas Elger: Department of Economics, Lund University, Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund, Sweden
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
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
JEL-codes: G11
32 pages, October 24, 2007
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