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dc.contributor.authorPınar, M. Ç.en_US
dc.date.accessioned2016-02-08T10:04:44Z
dc.date.available2016-02-08T10:04:44Z
dc.date.issued2009en_US
dc.identifier.issn0233-1934
dc.identifier.urihttp://hdl.handle.net/11693/22788
dc.description.abstractRecently, Cont introduced a quantitative framework for measuring model uncertainty in the context of derivative pricing [Model uncertainty and its impact on the pricing of derivative instruments, Math. Finance, 16(3) (2006), pp. 519-547]. Two measures of model uncertainty were proposed: one measure based on a coherent risk measure compatible with market prices of derivatives and another measure based on convex risk measures. We show in a discrete time, finite state probability setting, that the two measures introduced by Cont are closely related to calibrated option bounds studied recently by King et al. [Calibrated option bounds, Inf. J. Ther. Appl. Financ., 8(2) (2005), pp. 141-159]. The precise relationship is established through convex programming duality. As a result, the model uncertainty measures can be computed efficiently by solving convex programming or linear programming problems after a suitable discretization. Numerical results using S&P 500 options are given.en_US
dc.language.isoEnglishen_US
dc.source.titleOptimizationen_US
dc.relation.isversionofhttp://dx.doi.org/10.1080/02331930902741770en_US
dc.subjectModel uncertaintyen_US
dc.subjectOption pricingen_US
dc.subjectIncomplete marketsen_US
dc.subjectCoherent risk measuresen_US
dc.subjectConvex risk measures;en_US
dc.subjectCalibrated option bounden_US
dc.subjectDualityen_US
dc.titleMeasures of model uncertainty and calibrated option boundsen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineering
dc.citation.spage335en_US
dc.citation.epage350en_US
dc.citation.volumeNumber58en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1080/02331930902741770en_US
dc.publisherTaylor & Francisen_US
dc.identifier.eissn1026-7662


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