The Sampling Error in Estimates of Mean-Variance Efficient Portfolio Weights


  • Mark Britten-Jones

    1. London Business School
    Search for more papers by this author
    • London Business School. I thank Mark Grinblatt and Olivier Ledoit for many helpful discussions, and for pointing out an error in an earlier draft. I also thank the referee, Jay Shanken, for helpful comments, and the editor, René Stulz, for suggesting an international focus for the empirical section. Remaining errors are of course my responsibility.


This paper presents an exact finite-sample statistical procedure for testing hypotheses about the weights of mean-variance efficient portfolios. The estimation and inference procedures on efficient portfolio weights are performed in the same way as for the coefficients in an OLS regression. OLS t- and F-statistics can be used for tests on efficient weights, and when returns are multivariate normal, these statistics have exact t and F distributions in a finite sample. Using 20 years of data on 11 country stock indexes, we find that the sampling error in estimates of the weights of a global efficient portfolio is large.