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On the Monte Carlo simulation of BSDEs: An improvement on the Malliavin weights

dc.contributor.authorTouzi, Nizar
dc.contributor.authorManolarakis, Konstantinos
dc.contributor.authorCrisan, Dan
dc.date.accessioned2011-01-24T08:44:04Z
dc.date.available2011-01-24T08:44:04Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5522
dc.language.isoenen
dc.subjectMalliavin calculusen
dc.subjectMonte Carlo methodsen
dc.subjectWeak approximationsen
dc.subjectBDEsen
dc.subject.ddc519en
dc.subject.classificationjelC15en
dc.titleOn the Monte Carlo simulation of BSDEs: An improvement on the Malliavin weightsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose a generic framework for the analysis of Monte Carlo simulation schemes of backward SDEs. The general results are used to re-visit the convergence of the algorithm suggested by Bouchard and Touzi (2004) [6]. By keeping the higher order terms in the expansion of the Skorohod integrals resulting from the Malliavin integration by parts in [6], we introduce a variant of the latter algorithm which allows for a significant reduction of the numerical complexity. We prove the convergence of this improved Malliavin-based algorithm, and derive a bound on the induced error. In particular, we show that the price to pay for our simplification is to use a more accurate localizing function.en
dc.relation.isversionofjnlnameStochastic Processes and their Applications
dc.relation.isversionofjnlvol120en
dc.relation.isversionofjnlissue7en
dc.relation.isversionofjnldate2010
dc.relation.isversionofjnlpages1133-1158en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/j.spa.2010.03.015en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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