Abstract Numerical challenges inherent in algorithms for computing worst Value-at-Risk in homogeneous portfolios are identified and solutions as well as words of warning concerning their implementation are provided. Furthermore, both conceptual and computational improvements to the Rearrangement...

We study the problem of ?finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals and a nonlinear loss function. We show that when the risk measure is CVaR, and the distributions are discretized, the problem can be conveniently solved using...

Numerical challenges inherent in algorithms for computing worst Value-at-Risk in homogeneous portfolios are identified and words of warning concerning their implementation are raised. Furthermore, both conceptual and computational improvements to the Rearrangement Algorithm for approximating...

We study the problem of finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals with nonlinear loss function. The method has applications to any situation where marginals are provided, and bounds need to be determined on total portfolio risk....