Modeling a distribution of mortgage credit losses
| Author(s): | PhDr. Petr Gapko Ph.D., RNDr. Martin Šmíd Ph.D., |
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| Type: | Articles in journals with impact factor |
| Year: | 2012 |
| Number: | 0 |
| ISSN / ISBN: | |
| Published in: | Ekonomický časopis |
| Publishing place: | |
| Keywords: | Credit Risk, Mortgage, Delinquency Rate, Generalized Hyperbolic Distribution, Normal Distribution |
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| Suggested Citation: | |
| Grants: | 402/09/0965: New Approaches for monitoring and prediction of capital markets 402/09/H045 - Nelineární dynamika v peněžní ekonomii a financích. Teorie a empirické modely GAUK 46108: New Nonlinear Capital Markets Theories: Fractal, Bifurcational and Behavioral Approach |
| 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 underestimate the impact of changes in tail losses caused by underlying risk factors. |
