Safety-first portfolio selection

摘要

Das, Markowitz, Scheid, and Statman (2010) introduced portfolio optimization with mental accounts (POMA), which connects modern investment theory (MVT) and mean-variance utility (MVU) in a behavioral portfolio-style problem where the investors are concerned about downside risk. Their feasible solution is a system of implicit equations solved by numerical approximations. This article contributes several findings related to the POMA problem. First, with necessary and sufficient conditions measured by the safety-first risk management rule, we derive a closed-form solution with the threshold return relative to the orthogonal portfolio on the mean-variance frontier. Second, we show that POMA feasibility can be substantially improved through stepwise regressions in which sorting assets by the value-at-risk (VaR) constraint is equivalent to sorting the coefficients' t-statistics. Finally, we implement mean-variance efficiency testing from the VaR perspective.