Characteristic-based mean-variance portfolio choice


We study empirical mean-variance optimization when the portfolio weights are restricted to be direct functions of underlying stock characteristics such as value and momentum. The closed-form solution to the portfolio weights estimator shows that the portfolio problem in this case reduces to a mean-variance analysis of assets with returns given by single-characteristic strategies (e.g., momentum or value). In an empirical application to international stock return indexes, we show that the direct approach to estimating portfolio weights clearly beats a naive regression-based approach that models the conditional mean. However, a portfolio based on equal weights of the single-characteristic strategies performs about as well, and sometimes better, than the direct estimation approach, highlighting again the di¢ culties in beating the equal-weighted case in mean-variance analysis. The empirical results also highlight the potential for ‘stockpicking’in international indexes, using characteristics such as value and momentum, with the characteristic-based portfolios obtaining Sharpe ratios approximately three times larger than the world market. JEL classi…cation: C22, C23, G11, G15.

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@inproceedings{Hjalmarsson2009CharacteristicbasedMP, title={Characteristic-based mean-variance portfolio choice}, author={Erik Hjalmarsson and Peter Manchev}, year={2009} }