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dc.contributor.authorSalmon-Bélisle, Louis-Étienne
dc.date.accessioned2014-08-26 15:13:33 (GMT)
dc.date.available2014-08-26 15:13:33 (GMT)
dc.date.issued2014-08-26
dc.date.submitted2014
dc.identifier.urihttp://hdl.handle.net/10012/8709
dc.description.abstractCredit risk modelling can take many different approaches. Each method has its strengths and weaknesses and studying a variety of them can help find new ways of performing credit risk analysis. We present here three different models, each classified either as static or dynamic, and structural or reduced-form. The static structural model from Lucas et al. (2000) helps us derive a moment behaviour theorem within the dynamic structural setting of Bush et al. (2011). For comparison, we also present the dynamic reduced-form model of Giesecke et al. (2012). A calibration exercise of the dynamic structural model is implemented and we study its performance through changing financial environment. This highlights the horse race between simplicity and efficiency of a model that still needs to be adequately addressed, as the results from the calibration show the difficulty of capturing the key financial environment’s aspects.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectCredit default risken
dc.subjectModellingen
dc.subjectCalibrationen
dc.subjectMomentsen
dc.titleStatic and Dynamic Modelling of Credit Default Risk: Tails, Moments, and Calibrationen
dc.typeMaster Thesisen
dc.pendingfalse
dc.subject.programQuantitative Financeen
uws-etd.degree.departmentQuantitative Financeen
uws-etd.degreeMaster of Quantitative Financeen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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