TY  - CONF
A1  - Frerichs, Hergen
A1  - Löffler, Gunter
T1  - Evaluating credit risk models : a critique and a proposal
N2  - Evaluating the quality of credit portfolio risk models is an important issue for both banks and regulators. Lopez and Saidenberg (2000) suggest cross-sectional resampling techniques in order to make efficient use of available data. We show that their proposal disregards cross-sectional dependence in resampled portfolios, which renders standard statistical inference invalid. We proceed by suggesting the Berkowitz (1999) procedure, which relies on standard likelihood ratio tests performed on transformed default data. We simulate the power of this approach in various settings including one in which the test is extended to incorporate cross-sectional information. To compare the predictive ability of alternative models, we propose to use either Bonferroni bounds or the likelihood-ratio of the two models. Monte Carlo simulations show that a default history of ten years can be sufficient to resolve uncertainties currently present in credit risk modeling.
KW  - credit risk
KW  - backtesting,
KW  - density forecasts
KW  - model validation
KW  - bank regulation
KW  - Kreditrisiko
KW  - Portfoliomanagement
KW  - Gütefunktion
KW  - Parametertest
KW  - Signifikanzniveau
KW  - Statistischer Test
KW  - Testtheorie
Y1  - 2001
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/35041
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-350418
UR  - http://ssrn.com/abstract=269575
N1  - EFMA 2001 Lugano Meetings
IS  - Version: October 9, 2001
ER  -