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dc.contributor.authorBouchard, Bruno*
dc.contributor.authorTan, Xiaolu*
dc.date.accessioned2020-01-21T10:23:28Z
dc.date.available2020-01-21T10:23:28Z
dc.date.issued2019
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/20452
dc.language.isoenen
dc.subjectpath-dependent optionsen
dc.subjectprice impacten
dc.subject.ddc519en
dc.titleUnderstanding the dual formulation for the hedging of path-dependent options with price impacten
dc.typeDocument de travail / Working paper
dc.description.abstractenWe consider a general path-dependent version of the hedging problem with price impact of Bouchard et al. (2019), in which a dual formulation for the super-hedging price is obtained by means of PDE arguments, in a Markovian setting and under strong regularity conditions. Using only probabilistic arguments, we prove, in a path-dependent setting and under weak regularity conditions, that any solution to this dual problem actually allows one to construct explicitly a perfect hedging portfolio. From a pure probabilistic point of view, our approach also allows one to exhibit solutions to a specific class of second order forward backward stochastic differential equations, in the sense of Cheridito et al. (2007). Existence of a solution to the dual optimal control problem is also addressed in particular settings. As a by-product of our arguments, we prove a version of Itô's Lemma for path-dependent functionals that are only C^{0,1} in the sense of Dupire.en
dc.publisher.nameCahier de recherche CEREMADE, Université Paris-Dauphineen
dc.publisher.cityParisen
dc.identifier.citationpages29en
dc.relation.ispartofseriestitleCahier de recherche CEREMADE, Université Paris-Dauphineen
dc.identifier.urlsitehttps://hal.archives-ouvertes.fr/hal-02398881en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.identifier.citationdate2019-12
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2019-12-19T11:12:35Z
hal.person.labIds60*
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