This paper develops a variance reduction technique for Monte Carlo simulations of path-dependent options driven by high-dimensional Gaussian vectors. The method combines " importance sampling" based on a change of drift with "stratified sampling" along a small number of key dimensions. The...

This paper develops efficient methods for computing portfolio value-at-risk (VAR) when the underlying risk factors have a heavy-tailed distribution. In modeling heavy tails, we focus on multivariate "t" distributions and some extensions thereof. We develop two methods for VAR calculation that...