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dc.contributor.authorAbi jaber, Eduardo*
dc.contributor.authorEl Euch, Omar*
dc.date.accessioned2018-09-03T09:41:45Z
dc.date.available2018-09-03T09:41:45Z
dc.date.issued2019
dc.identifier.issn1945-497X
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17921
dc.language.isoenen
dc.subjectlimit theorems
dc.subjectaffine Volterra processes
dc.subjectRough volatility models
dc.subjectrough Heston models
dc.subjectstochastic Volterra equations
dc.subjectfractional Riccati equations
dc.subject.ddc519en
dc.titleMulti-factor approximation of rough volatility models
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenRough volatility models are very appealing because of their remarkable fit of both historical and implied volatilities. However, due to the non-Markovian and non-semimartingale nature of the volatility process, there is no simple way to simulate efficiently such models, which makes risk management of derivatives an intricate task. In this paper, we design tractable multi-factor stochastic volatility models approximating rough volatility models and enjoying a Markovian structure. Furthermore, we apply our procedure to the specific case of the rough Heston model. This in turn enables us to derive a numerical method for solving fractional Riccati equations appearing in the characteristic function of the log-price in this setting.
dc.relation.isversionofjnlnameSIAM Journal on Financial Mathematics
dc.relation.isversionofjnlvol10
dc.relation.isversionofjnlissue2
dc.relation.isversionofjnldate2019
dc.relation.isversionofjnlpages309–349
dc.relation.isversionofjnlpublisherSIAM - Society for Industrial and Applied Mathematics
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2020-04-22T13:20:22Z
hal.person.labIds60*
hal.person.labIds141112*


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