Portfolio Choice Under Cumulative Prospect Theory: Sensitivity Analysis and an Empirical Study

In this paper we study the portfolio selection problem under cumulative prospect theory (CPT), both from a theoretical and empirical point of view. Our aim is twofold. First, we study through a simulation-based procedure, the implication of higher-moments and CPT parameters on Mean/Risk efficient frontier. In this part, motivated by recent results, we assume a multivariate variance gamma (MVG) distribution for log-returns. On a second stage, we investigate empirically, for a hedge fund portfolio, the optimal choice problem for an investor who behaves according to the CPT. We construct several optimal CPT portfolios by considering different parameters for the CPT utility function. We then compare our empirical results with the Mean Variance (MV) and the Global Minimum Variance (GMV) portfolios, from an in-sample and out-of-sample perspective.