Alternative Objective Functions for Quasi-Shrinkage Portfolio Optimization

Abstract

In this paper we propose a quasi-shrinkage approach for minimum-variance portfolios which does not use a quadratic loss function to derive the optimal shrinkage intensity. We develop two alternative objective functions for linear shrinkage. The first targets the reduction of portfolio variance. The second incorporates returns of assets to improve portfolio performance with respect to mean and variance. We compare the out-of-sample performance of our proposed portfolios to nine benchmark strategies across seven data sets. Our strategies often have lower portfolio variance and higher Sharpe ratios than the benchmark strategies. In particular, we beat the naive portfolio empirically on all seven and significantly on three data sets.