the web's biggest credit risk modeling resource.

Credit Jobs

Home Glossary Links FAQ / About Site Guide Search


Submit Your Paper

In Rememberance: World Trade Center (WTC)

doi> search: A or B

Export citation to:
- Text (plain)
- BibTeX

Predicting the Credit Cycle with an Autoregressive Model

by Steffi Höse of Technische Universität Dresden, and
Konstantin Vogl of Technische Universität Dresden

August 2, 2005

Abstract: Credit default events show cross sectional as well as serial correlation. While the latter is often neglected by current credit risk models, this work incorporates both types of dependence. A Bernoulli mixture model is considered, where in each rating grade the probit of the stochastic Bernoulli parameter follows an autoregressive stationary process with exogenous variables. The model parameters are estimated for a large retail portfolio. Exemplarily, prediction intervals of the default probabilities of the best and worst nondefault rating grade are given and predicted credit portfolio loss distributions are plotted in contrast to the unconditional loss distributions.

This paper is republished in...

Books Referenced in this paper:  (what is this?)

Download paper (790K PDF) 18 pages