Evaluating credit risk models: a critique and a new proposal

  • Evaluating the quality of credit portfolio risk models is an important question for both banks and regulators. Lopez and Saidenberg (2000) suggest cross-sectional resampling techniques in order to make efficient use of available data and to produce measures of forecast accuracy. We first show that their proposal disregards crosssectional dependence in simulated subportfolios, which renders standard statistical inference invalid. We proceed by suggesting another evaluation methodology which draws on the concept of likelihood ratio tests. Specifically, we compare the predictive quality of alternative models by comparing the probabilities that observed data have been generated by these models. The distribution of the test statistic can be derived through Monte Carlo simulation. To exploit differences in cross-sectional predictions of alternative models, the test can be based on a linear combination of subportfolio statistics. In the construction of the test, the weight of a subportfolio depends on the difference in the loss distributions which alternative models predict for this particular portfolio. This makes efficient use of the data, and reduces computational burden. Monte Carlo simulations suggest that the power of the tests is satisfactory. JEL classification: G2; G28; C52

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Metadaten
Author:Hergen Frerichs, Gunter Löffler
URN:urn:nbn:de:hebis:30:3-349902
URL:http://ww2.odu.edu/bpa/efma/hfrerichs.pdf
Document Type:Report
Language:English
Year of Completion:2001
Year of first Publication:2001
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2014/09/17
Tag:backtesting; bank regulation; credit risk; model validation
GND Keyword:Kreditrisiko; Portfoliomanagement; Gütefunktion; Parametertest; Signifikanzniveau; Statistischer Test; Testtheorie
Issue:Version February 14, 2001
Page Number:30
HeBIS-PPN:348151519
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Classification:C Mathematical and Quantitative Methods / C5 Econometric Modeling / C52 Model Evaluation and Selection
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht