Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/154318
Authors: 
Coppens, François
Mayer, Manuel
Millischer, Laurent
Resch, Florian
Sauer, Stephan
Schulze, Klaas
Year of Publication: 
2016
Series/Report no.: 
ECB Working Paper 1885
Abstract: 
When back-testing the calibration quality of rating systems two-sided statistical tests can detect over- and underestimation of credit risk. Some users though, such as risk-averse investors and regulators, are primarily interested in the underestimation of risk only, and thus require one-sided tests. The established one-sided tests are multiple tests, which assess each rating class of the rating system separately and then combine the results to an overall assessment. However, these multiple tests may fail to detect underperformance of the whole rating system. Aiming to improve the overall assessment of rating systems, this paper presents a set of one-sided tests, which assess the performance of all rating classes jointly. These joint tests build on the method of Sterne [1954] for ranking possible outcomes by probability, which allows to extend back-testing to a setting of multiple rating classes. The new joint tests are compared to the most established one-sided multiple test and are further shown to outperform this benchmark in terms of power and size of the acceptance region.
Subjects: 
back-testing
credit ratings
one-sided
probability of default
JEL: 
C12
C52
G21
G24
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-2001-8
Document Type: 
Working Paper

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