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Modeling a Distribution of Mortgage Credit Losses

Publication at Faculty of Social Sciences |
2012

Abstract

In our paper, we focus on the credit risk quantification methodology. We demonstrate that the current regulatory standards for credit risk management are at least not perfect.

Generalizing the Well-known KMV model, standing behind Basel II, we build a model of a loan portfolio involving a dynamics of the common factor, influencing the borrowers' assets, which we allow to be non-normal. We show how the parameters of our model may be estimated by means of past mortgage delinquency rates.

We give statistical evidence that the non-normal model is much more suitable than the one which assumes the normal distribution of risk factors. We point out in what way the assumption that risk factors follow a normal distribution can be dangerous.

Especially during volatile periods comparable to the current crisis, the normal-distribution-based methodology can under-estimate the impact of changes in tail losses caused by underlying risk factors.