报告人：Zhu Dan (Monash University)
摘要：The problem of estimating expectations of functions of conditional expectations using nested Monte Carlo simulation is studied. Itis shown that typically the bias arising from non-linearity is in leading order inversely proportional to the number of sub-simulation paths when using a naive estimate. Various improved statistical estimators are introduced for the inner simulation. Applications to pricing of VIX derivatives, the computation of credit valuation adjustments and computation of Value-At-Risk are presented. It is shown that only small numbers of sub-paths are necessary for high accuracy.