Portfolio optimization with decreasing absolute risk aversion stochastic dominance constraints

Abstract

An optimization method is developed for constructing investment portfolios which stochastically dominate a given benchmark for all decreasing absolute risk-averse investors, using Quadratic Programming. The method is applied to a standard data set of historical returns of equity industry portfolios. The proposed optimization method improves upon the performance of mean-variance optimization by tens to hundreds of basis points per annum out of sample, depending on whether short sales are allowed. The improvements critically depend on imposing the complex condition of Decreasing Absolute Risk Aversion in addition to the simpler conditions of global risk aversion and decreasing risk aversion. © 2026 Elsevier B.V.