A regularity structure for rough volatility

dc.contributor.authorBayer, Christian
dc.contributor.authorFriz, Peter K.
dc.contributor.authorGassiat, Paul
dc.contributor.authorMartin, Jorg
dc.contributor.authorStemper, Benjamin
dc.date.accessioned2020-11-16T11:33:25Z
dc.date.available2020-11-16T11:33:25Z
dc.date.issued2019-11-19
dc.date.updated2020-10-19T12:56:08Z
dc.description.abstractA new paradigm has emerged recently in financial modeling: rough (stochastic) volatility. First observed by Gatheral et al. in high‐frequency data, subsequently derived within market microstructure models, rough volatility captures parsimoniously key‐stylized facts of the entire implied volatility surface, including extreme skews (as observed earlier by Alòs et al.) that were thought to be outside the scope of stochastic volatility models. On the mathematical side, Markovianity and, partially, semimartingality are lost. In this paper, we show that Hairer's regularity structures, a major extension of rough path theory, which caused a revolution in the field of stochastic partial differential equations, also provide a new and powerful tool to analyze rough volatility models.en
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2020en
dc.identifier.eissn1467-9965
dc.identifier.issn0960-1627
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/11960
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-10842
dc.language.isoenen
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
dc.rights
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc510 Mathematikde
dc.subject.otherfinancial modelingen
dc.subject.otherrough volatilityen
dc.subject.otherstochastic volatility modelsen
dc.titleA regularity structure for rough volatilityen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.1111/mafi.12233en
dcterms.bibliographicCitation.issue3en
dcterms.bibliographicCitation.journaltitleMathematical Financeen
dcterms.bibliographicCitation.originalpublishernameWileyen
dcterms.bibliographicCitation.originalpublisherplaceNew York, NYen
dcterms.bibliographicCitation.pageend832en
dcterms.bibliographicCitation.pagestart782en
dcterms.bibliographicCitation.volume30en
tub.accessrights.dnbfreeen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften>Inst. Mathematik>AG Stochastik und Finanzmathematikde
tub.affiliation.facultyFak. 2 Mathematik und Naturwissenschaftende
tub.affiliation.groupAG Stochastik und Finanzmathematikde
tub.affiliation.instituteInst. Mathematikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
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