Optimal portfolio selection with maximal risk adjusted return

We investigate the portfolio diversification problem by maximizing the risk adjusted return (RAR) of the underlying portfolio. The model in this article has two primary advantages over the original portfolio selection model with maximal RAR: (1) it considers the set of available assets containing any number of assets instead of only two assets, which is more reasonable in practical applications and (2) it incorporates the general linear constraint other than the simple budget constraint, which can deal with additional constraints for rational investors. An application including in-sample and out-of-sample tests is provided where the results illustrate that the portfolios selected by our method lead to considerable increases of RAR in comparison with those by the minimization of variance approach, and the outperformance persists using different sample frequencies.