Institute of Information Theory and Automation

Publication details

Modeling a Distribution of Mortgage Credit Losses

Journal Article

Gapko Petr, Šmíd Martin

serial: Ekonomický časopis vol.60, 10 (2012), p. 1005-1023

research: CEZ:AV0Z10750506

project(s): 46108, Univerzita Karlova, GD402/09/H045, GA ČR, GBP402/12/G097, GA ČR

keywords: credit risk, mortgage, delinquency rate, generalized hyperbolic distribution, normal distribution

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abstract (eng):

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 com- mon 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 compa- rable to the current crisis, the normal-distribution-based methodology can under- estimate the impact of changes in tail losses caused by underlying risk factors.


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Last modification: 21.12.2012
Institute of Information Theory and Automation