Abstract: The fundamental conceptual difficulty in Monte Carlo methodologies is the ability to generate scenarios that mimic reality. The challenge, even in the static case, is to capture multidimensional distributions with very limited amount of historical information.

In this talk, we overview existing as well as new methodologies in the generic area of scenarion generation, and introduce a collection of benchmarks to evaluate the accuracy of each technique.
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