We introduce a universal framework for mean-covariance robust risk measurement andportfolio optimization.We model … population distribution.Our approach is related to the theory of optimal transport and exhibits superior statistical … andcomputational properties than existing models. We find that, for a large class of risk measures,mean-covariance robust portfolio …

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using …. We find that the model can be tuned easily using Value-at-Risk (VaR) related benchmarks. In the multi-stage setting, we … formally prove that the optimal solution consists of a sequence of myopic (single-stage) decisions with risk …

Linear optimization problems are investigated whose parameters are uncertain. We apply coherent distortion risk …, principally, for the mean-risk portfolio selection problem. Each risk constraint induces an uncertainty set of coefficients, which … optimization ; data depth ; weighted-mean trimmed regions ; central regions ; coherent risk measure ; spectral risk measure …