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dc.contributor.authorHenry-Labordère, Pierre
dc.contributor.authorTan, Xiaolu
dc.contributor.authorTouzi, Nizar
dc.date.accessioned2018-01-15T16:02:44Z
dc.date.available2018-01-15T16:02:44Z
dc.date.issued2017
dc.identifier.issn1050-5164
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17350
dc.language.isoenen
dc.subjectUnbiased simulation of SDEsen
dc.subjectregime switching diffusionen
dc.subjectlinear parabolic PDEsen
dc.subject.ddc519en
dc.titleUnbiased simulation of stochastic differential equationsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose an unbiased Monte-Carlo estimator for E[g(X t 1 , · · · , X tn)], where X is a diffusion process defined by a multi-dimensional stochastic differential equation (SDE). The main idea is to start instead from a well-chosen simulatable SDE whose coefficients are updated at independent exponential times. Such a simulatable process can be viewed as a regime-switching SDE, or as a branching diffusion process with one single living particle at all times. In order to compensate for the change of the coefficients of the SDE, our main representation result relies on the automatic differentiation technique induced by Bismu-Elworthy-Li formula from Malliavin calculus, as exploited by Fournié et al. [14] for the simulation of the Greeks in financial applications. In particular, this algorithm can be considered as a variation of the (infinite variance) estimator obtained in Bally and Kohatsu-Higa [3, Section 6.1] as an application of the parametrix method.en
dc.relation.isversionofjnlnameThe Annals of Applied Probability
dc.relation.isversionofjnlvol27en
dc.relation.isversionofjnlissue6en
dc.relation.isversionofjnldate2017
dc.relation.isversionofjnlpages3305-3341en
dc.relation.isversionofdoi10.1214/17-AAP1281en
dc.identifier.urlsitehttps://hal.archives-ouvertes.fr/hal-01429548en
dc.relation.isversionofjnlpublisherInstitute of Mathematical Statisticsen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2018-01-08T10:13:27Z
hal.person.labIds7709
hal.person.labIds60
hal.person.labIds89626


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