Advances in multivariate back-testing for credit risk underestimation

Stephan Sauer, François Coppens, Manuel Mayer, Laurent Millischer, Florian Resch and Klaas Schulze ()

No 1885, Working Paper Series from European Central Bank

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. JEL Classification: C12, C52, G21, G24

Keywords: back-testing; credit ratings; one-sided; probability of default (search for similar items in EconPapers)
Date: 2016-02
New Economics Papers: this item is included in nep-ecm and nep-rmg
Note: 362683
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20161885

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