We assume pairs of random variables (X_i, Y_i), whereby the real variable X_i measures the creditworthiness of individual i with i = 1, . . . , n. The Bernoulli variable Y_i represents the default indicator of individual i. Our main target is a division of the creditworthiness into a given number of groups with a homogeneous default risk, i.e. to estimate rating classes. The framework of change point analysis provides a nonparametric method to estimate the breakpoints between the rating classes under quite weak assumptions.
Up to now, the theory of breakpoint estimation is developed under the assumption of exactly one breakpoint. The contribution at hand, basically implements this theory, but extends it into a multi-stage heuristic. That means, we sequentially apply the theory for only one breakpoint as a multi-stage procedure. With this article we transfer the interesting theoretical issue of breakpoint estimation into an applicable form. Thereby, all the results are checked and obtained by simulation.
The main results are as follows. Applying a sequential breakpoint estimation basically works and leads to outcomes of practical purpose. Thereby, the multistage heuristic reveals some weakness esp. in the case of quite huge differences between default probabilities that can be resolved by some interventions.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30195 |
| Date | 27 March 2017 |
| Creators | Lehmann, Christoph |
| Publisher | TU Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:book, info:eu-repo/semantics/book, doc-type:Text |
| Source | Dresdner Beiträge zu Quantitativen Verfahren |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:14-qucosa-222671, qucosa:30256 |
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