Mean-variance vs. full-scale optimization
Subtitle: broad evidence for the uk
By: by Björn Hagströmer ... [et al.].
Contributors: Hagströmer, Björn.; Federal Reserve Bank of St. Louis.
Series: Working paper -- 2007-016A; Working paper (Federal Reserve Bank of St. Louis : Online) -- 2007-016A.
Publisher: Federal Reserve Bank of St. Louis
Published: 2007
Place of publication: [St. Louis, Mo.]
Language: eng
Format: Electronic resource
Description: "In a portfolio choice setting of three common assets (FTSE 100, FTSE 250 and FTSE Emerging Market Index), we identify several utility functions under which Full-Scale Optimization is a substantially better approach than the mean variance approach is.  With the Full-Scale Optimization approach the complete empirical financial return probability distribution is considered, and the utility maximising solution is found through grid search.  Earlier studies have shown that this approach is useful for investors following non-linear utility functions (such as bilinear and S-shaped utility) and choosing between highly non-normally distributed assets, such as hedge funds.  We expand the area of usage to common indices, and show that the results are robust for a broader range of utility function specifications"--Federal Reserve Bank of St. Louis web site.
Notes: Title from PDF file as viewed on 4/16/2007.

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