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dc.contributor.authorHenry-Labordere, Pierrede
dc.date.accessioned2011-02-23T03:41:00Zde
dc.date.accessioned2012-08-30T07:09:12Z
dc.date.available2012-08-30T07:09:12Z
dc.date.issued2007de
dc.identifier.urihttp://www.ssoar.info/ssoar/handle/document/22095
dc.description.abstractIn this paper we provide an extensive classification of one and two dimensional diffusion processes which admit an exact solution to the Kolmogorov (and hence Black-Scholes) equation (in terms of hypergeometric functions). By identifying the one-dimensional solvable processes with the class of {\it integrable superpotentials} introduced recently in supersymmetric quantum mechanics, we obtain new analytical solutions. In particular, by applying {\it supersymmetric transformations} on a known solvable diffusion process (such as the Natanzon process for which the solution is given by a hypergeometric function), we obtain a hierarchy of new solutions. These solutions are given by a sum of hypergeometric functions, generalizing the results obtained in the paper "Black-Scholes Goes Hypergeometric" \cite{alb}. For two-dimensional processes, more precisely stochastic volatility models, the classification is achieved for a specific class called gauge-free models including the Heston model, the $3/2$-model and the geometric Brownian model. We then present a new exact stochastic volatility model belonging to this class.en
dc.languageende
dc.subject.ddcWirtschaftde
dc.subject.ddcEconomicsen
dc.subject.otherApplied Mathematical Finance; Econophysics; Black-Scholes Model; Stochastic Volatility; Calibration of Stochastic Volatility; Volatility Modelling
dc.titleSolvable Local and Stochastic Volatility Models: Supersymmetric Methods in Option Pricingen
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalQuantitative Financede
dc.source.volume7de
dc.publisher.countryGBR
dc.source.issue5de
dc.subject.classozBasic Research, General Concepts and History of Economicsen
dc.subject.classozEconomic Statistics, Econometrics, Business Informaticsen
dc.subject.classozWirtschaftsstatistik, Ökonometrie, Wirtschaftsinformatikde
dc.subject.classozAllgemeines, spezielle Theorien und Schulen, Methoden, Entwicklung und Geschichte der Wirtschaftswissenschaftende
dc.identifier.urnurn:nbn:de:0168-ssoar-220959de
dc.date.modified2011-03-15T11:09:00Zde
dc.rights.licencePEER Licence Agreement (applicable only to documents from PEER project)de
dc.rights.licencePEER Licence Agreement (applicable only to documents from PEER project)en
ssoar.gesis.collectionSOLIS;ADISde
ssoar.contributor.institutionhttp://www.peerproject.eu/de
internal.status1de
dc.type.stockarticlede
dc.type.documentjournal articleen
dc.type.documentZeitschriftenartikelde
dc.rights.copyrightfde
dc.source.pageinfo525-535
internal.identifier.classoz10905
internal.identifier.classoz10901
internal.identifier.document32
internal.identifier.ddc330
dc.identifier.doihttps://doi.org/10.1080/14697680601103045de
dc.subject.methodsTheorieanwendungde
dc.subject.methodstheory applicationen
dc.description.pubstatusPostprinten
dc.description.pubstatusPostprintde
internal.identifier.licence7
internal.identifier.methods15
internal.identifier.pubstatus2
internal.identifier.review1
internal.check.abstractlanguageharmonizerCERTAIN
internal.check.languageharmonizerCERTAIN_RETAINED


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