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dc.contributor.authorMrad, Moez
dc.contributor.authorTouzi, Nizar
dc.contributor.authorZeghal, Amina
dc.date.accessioned2014-06-26T09:23:40Z
dc.date.available2014-06-26T09:23:40Z
dc.date.issued2006
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/13602
dc.language.isoenen
dc.subjectMonte Carloen
dc.subjectMalliavin calculusen
dc.subjectquantizationen
dc.subjectAmerican optionsen
dc.subject.ddc519en
dc.titleMonte Carlo Estimation of a Joint Density Using Malliavin Calculus, and Application to American Optionsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe use the Malliavin integration by parts formula in order to provide a family of representations of the joint density (which does not involve Dirac measures) of (X_θ, X θ + δ), where X is a d-dimensional Markov diffusion (d ≥ 1), θ > 0 and δ > 0. Following Bouchard et al. (2004), the different representations are determined by a pair of localizing functions. We discuss the problem of variance reduction within the family of separable localizing functions: We characterize a pair of exponential functions as the unique integrated-variance minimizer among this class of separable localizing functions. We test our method on the d-dimensional Brownian motion and provide an application to the problem of American options valuation by the quantization tree method introduced by Bally et al. (2002).en
dc.relation.isversionofjnlnameComputational Economics
dc.relation.isversionofjnlvol27en
dc.relation.isversionofjnlissue4en
dc.relation.isversionofjnldate2006
dc.relation.isversionofjnlpages497-531en
dc.relation.isversionofdoihttp://dx.doi.org/10.1007/s10614-005-9005-3en
dc.relation.isversionofjnlpublisherSpringeren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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