Testing Homogeneity of Time-Continuous Rating Transitions
| dc.contributor.author | Lawrenz, Claudia | |
| dc.contributor.author | Tschiersch, Patrick | |
| dc.contributor.author | Weißbach, Rafael | |
| dc.date.accessioned | 2005-10-11T14:37:40Z | |
| dc.date.available | 2005-10-11T14:37:40Z | |
| dc.date.issued | 2005-10-11T14:37:40Z | |
| dc.description.abstract | Banks 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.extent | 243324 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/2003/21638 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14496 | |
| dc.language.iso | en | |
| dc.subject | Markov model | en |
| dc.subject | partial likelihood | en |
| dc.subject | Portfolio credit risk | en |
| dc.subject | Rating transitions | en |
| dc.subject | time-homogeneity | en |
| dc.subject.ddc | 004 | |
| dc.title | Testing Homogeneity of Time-Continuous Rating Transitions | en |
| dc.type | Text | |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |