Improved precision matrix estimation for mean-variance portfolio selection

This paper deals with the problem of reducing the estimation error of the precision matrix in mean-variance portfolio selection. A new shrinkage estimator for the precision matrix is proposed and the optimal shrinkage intensity is obtained by maximizing the investor's utility function. An oracle estimator is proposed and many feasible estimators are derived in the paper. Feasible estimators are easy to implement in practice. The performance of the proposed shrinkage estimator is evaluated with both simulations and empirical experiments.