The economic value of controlling for large losses in portfolio selection

Research on asset pricing has shown that investor preferences include asymmetry and tail heaviness which affects the composition of optimal portfolios. This article investigates the out-of-sample economic value of introducing the risk of very large losses in portfolio selection. We combine mean-variance analysis with conditional Value-at-Risk using the subadditivity property of conditional Value-at-Risk, and we introduce a two stage method that preserves diversification while controlling for large losses. We find that strategies that account both for variance and the probability of large losses outperform efficient mean-variance portfolios, during and after the global financial crisis.