0385822 20240103201808.220130111235959.9 000287979900026 19 s. cav_un_epca*02504190013-30356010 (2012)1005-1023Ekonomický ústav SAV credit risk mortgage delinquency rate generalized hyperbolic distribution normal distribution cav_un_auth*0264433 Gapko Petr Ekonometrie Department of Econometrics E E UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101206 Šmíd Martin Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/E/smid-modeling a distribution of mortgage credit losses.pdf 46108 Univerzita Karlova CZ GD402/09/H045 GA ČR cav_un_auth*0253998 GBP402/12/G097 GA ČR CZ cav_un_auth*0281000 CEZ:AV0Z10750506 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. 2013 AH 2 RVO:67985556 http://hdl.handle.net/11104/0216180 ECONOMICS 0.04 7 0.231 26.6 0.15 Q3 2.405 8.559 Q4 Q3 2012 000287979900026 WOS cav_un_epca*0250419 Ekonomický časopis 0013-3035 0013-3035 Roč. 60 č. 10 2012 1005 1023 Ekonomický ústav SAV