Faster comparison of stopping times by nested conditional Monte Carlo

Fabian Dickmann and Nikolaus Schweizer

Journal of Computational Finance

Abstract: ABSTRACT We show that deliberately introducing a nested simulation stage can lead to significant;variance reductions when comparing two stopping times by Monte Carlo. We derive;the optimal number of nested simulations and prove that the algorithm is remarkably;robust to misspecifications of this number. The method is applied to several problems;related to Bermudan/American options. In these applications, our method allows us to;substantially increase the efficiency of other variance reduction techniques, namely,;quasi-control variates and multilevel Monte Carlo.

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