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.
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Paper 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. Handle: RePEc:hhs:lunewp:2008_001
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