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USING STATISTICAL ESTIMATORS TO GAIN MUCH IMPROVED CONVERGENCE OF NESTED MONTE-CARLO SIMULATIONS

2017/12/18 15:07  点击:[]

报告人:Zhu Dan (Monash University)

 

时间:2017.12.21(周四)10:00-11:00

 

地点:理科楼LD201

 

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.


学院联系人:张志民

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