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Mean-Variance vs. Full-Scale Optimization
Björn Hagströmer
其他書名
Broad Evidence for the UK.
出版
Department of Economics
, 2007
URL
http://books.google.com.hk/books?id=LNn1xwEACAAJ&hl=&source=gbs_api
註釋
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.