Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 7, 2018 erstellt
Beschreibung:
This paper introduces a new approach to constructing optimal mean-variance portfolios. The approach relies on a novel unconstrained regression representation of the mean-variance optimization problem combined with high-dimensional sparse-regression methods. Our estimated portfolio, under a mild sparsity assumption, controls the risk and attains the maximum expected return as both the numbers of assets and observations grow. The superior properties of our approach are demonstrated through comprehensive simulation and empirical analysis. Notably, we fi nd that investing in individual stocks in addition to the Fama-French three factor portfolios using our strategy leads to substantially improved performance