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dc.contributor.authorLawrenz, Claudia-
dc.contributor.authorTschiersch, Patrick-
dc.contributor.authorWeißbach, Rafael-
dc.date.accessioned2005-10-11T14:37:40Z-
dc.date.available2005-10-11T14:37:40Z-
dc.date.issued2005-10-11T14:37:40Z-
dc.identifier.urihttp://hdl.handle.net/2003/21638-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-14496-
dc.description.abstractBanks could achieve substantial improvements of their portfolio credit risk assessment by estimating rating transition matrices within a time-continuous Markov model, thereby using continuous-time rating transitions provided by internal rating systems instead of discrete-time rating information. A non-parametric test for the hypothesis of time-homogeneity is developed. The alternative hypothesis is multiple structural change of transition intensities, i.e. time-varying transition probabilities. The partial-likelihood ratio for the multivariate counting process of rating transitions is shown to be asymptotically c2 -distributed. A Monte Carlo simulation finds both size and power to be adequate for our example. We analyze transitions in credit-ratings in a rating system with 8 rating states and 2743 transitions for 3699 obligors observed over seven years. The test rejects the homogeneity hypothesis at all conventional levels of significance.en
dc.format.extent243324 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.subjectMarkov modelen
dc.subjectpartial likelihooden
dc.subjectPortfolio credit risken
dc.subjectRating transitionsen
dc.subjecttime-homogeneityen
dc.subject.ddc004-
dc.titleTesting Homogeneity of Time-Continuous Rating Transitionsen
dc.typeText-
dc.type.publicationtypereporten
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 475

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