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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.issued2018
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17921
dc.language.isoenen
dc.subjectlimit theoremsen
dc.subjectaffine Volterra processesen
dc.subjectRough volatility modelsen
dc.subjectrough Heston modelsen
dc.subjectstochastic Volterra equationsen
dc.subjectfractional Riccati equationsen
dc.subject.ddc519en
dc.titleMulti-factor approximation of rough volatility modelsen
dc.typeDocument de travail / Working paper
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.en
dc.identifier.citationpages40en
dc.relation.ispartofseriestitleCahier de recherche CEREMADE, Université Paris-Dauphineen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2018-09-03T09:26:05Z
hal.person.labIds60
hal.person.labIds17


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