  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 Algorithm for
approximating worst Value-at-Risk for portfolios with arbitrary marginal loss
distributions are given. In particular, a novel Adaptive Rearrangement
Algorithm is introduced and investigated. These algorithms are implemented
using the R package qrmtools.
