Join BookitisSave favorites, build lists, and follow creators.

Mean-variance vs. full-scale optimization

Work detail

Bookitis Pick
Mean-variance vs. full-scale optimization
MV
Björn Hagströmer1 editions

"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.

Overview

Shared work-level identity and catalog context.

1 credited authorSearch language english

Bookitis keeps work pages focused on the shared book identity and the editions that actually belong to it. Unrelated books should not appear here as primary content.

Contributors

People credited with this work in the active catalog.

  • Björn Hagströmer

    Author profile in the active Bookitis catalog

    Open Author

Editions

Publication-specific versions linked to this work only.