On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations | Zendy

Christian Bayer | Zendy; Håkon Hoel | Zendy; Erik von Schwerin | Zendy; Raúl Tempone | Zendy

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On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations

Author(s) -

Christian Bayer,

Håkon Hoel,

Erik von Schwerin,

Raúl Tempone

Publication year - 2014

Publication title -

siam journal on scientific computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.674

H-Index - 147

eISSN - 1095-7197

pISSN - 1064-8275

DOI - 10.1137/130911433

Subject(s) - monte carlo method , mathematics , statistical physics , optimal stopping , mathematical optimization , statistics , physics

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.QC 2012050

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