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On non-asymptotic optimal stopping criteria in Monte Carlo Simulations

Bibliography:

Christian Bayer, Hakon Hoel, Erik Von Schwerin, and Raul Tempone, On non-asymptotic optimal stopping criteria in Monte Carlo Simulations, SIAM Journal on Scientific Computing, Volume 36, Issue 2, 2014

Authors:

Christian Bayer, Hakon Hoel, Erik Von Schwerin, and Raul Tempone

Keywords:

Monte Carlo methods, optimal stopping, sequential stopping rules, non-asymptotic

Year:

2014

Abstract:

We consider the setting of estimating the mean of a random variable by a sequential stopping rule Monte Carlo (MC) method. The performance of a typical second moment based sequential stopping rule MC method is shown to be unreliable in such settings both by numerical examples and through analysis. By analysis and approximations, we construct a higher moment based stopping rule which is shown in numerical examples to perform more reliably and only slightly less efficiently than the second moment based stopping rule.

ISSN:

ISSN (print): 1064-8275