dc.contributor.author | Salmon-Bélisle, Louis-Étienne | |
dc.date.accessioned | 2014-08-26 15:13:33 (GMT) | |
dc.date.available | 2014-08-26 15:13:33 (GMT) | |
dc.date.issued | 2014-08-26 | |
dc.date.submitted | 2014 | |
dc.identifier.uri | http://hdl.handle.net/10012/8709 | |
dc.description.abstract | Credit 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.iso | en | en |
dc.publisher | University of Waterloo | en |
dc.subject | Credit default risk | en |
dc.subject | Modelling | en |
dc.subject | Calibration | en |
dc.subject | Moments | en |
dc.title | Static and Dynamic Modelling of Credit Default Risk: Tails, Moments, and Calibration | en |
dc.type | Master Thesis | en |
dc.pending | false | |
dc.subject.program | Quantitative Finance | en |
uws-etd.degree.department | Quantitative Finance | en |
uws-etd.degree | Master of Quantitative Finance | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Unreviewed | en |
uws.scholarLevel | Graduate | en |