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Validation of internal rating systems and PD estimates

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  • Dirk Tasche

Abstract

This paper elaborates on the validation requirements for rating systems and probabilities of default (PDs) which were introduced with the New Capital Standards (Basel II). We start in Section 2 with some introductory remarks on the topics and approaches that will be discussed later on. Then we have a view on the developments in banking regulation that have enforced the interest of the public in validation techniques. When doing so, we put the main emphasis on the issues with quantitative validation. The techniques discussed here could be used in order to meet the quantitative regulatory requirements. However, their appropriateness will depend on the specific conditions under which they are applied. In order to have a common ground for the description of the different techniques, we introduce in Section 3 a theoretical framework that will be the basis for the further considerations. Intuitively, a good rating system should show higher probabilities of default for the less creditworthy rating grades. Therefore, in Section 4, we discuss how this monotonicity property is reflected in the theoretical framework from Section 3. In Section 5, we study the meaning of discriminatory power and some tools for measuring it in some detail. We will see that there are tools that might be more appropriate than others for the purpose of regulatory validation of discriminatory power. The topic in Section 6 is calibration of rating systems. We introduce some of the tests that can be used for checking correct calibration and discuss the properties of the different tests. We then conclude in Section 7 with some comments on the question which tools might be most appropriate for quantitative validation of rating systems and probabilities of default.

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File URL: http://arxiv.org/pdf/physics/0606071
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Paper provided by arXiv.org in its series Papers with number physics/0606071.

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Date of creation: Jun 2006
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Handle: RePEc:arx:papers:physics/0606071

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  1. Dirk Tasche, 2002. "Remarks on the monotonicity of default probabilities," Papers cond-mat/0207555, arXiv.org.
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Cited by:
  1. Raffaella Calabrese, 2012. "Improving Classifier Performance Assessment of Credit Scoring Models," Working Papers, Geary Institute, University College Dublin 201204, Geary Institute, University College Dublin.
  2. Raffaella Calabrese, 2011. "Cost-sensitive classification for rare events: an application to the credit rating model validation for SMEs," Working Papers, Geary Institute, University College Dublin 201134, Geary Institute, University College Dublin.
  3. Morone, Marco & Cornaglia, Anna, 2010. "An econometric model to quantify benchmark downturn LGD on residential mortgages," MPRA Paper 25588, University Library of Munich, Germany.
  4. Cornaglia, Anna & Morone, Marco, 2009. "Rating philosophy and dynamic properties of internal rating systems: A general framework and an application to backtesting," MPRA Paper 14711, University Library of Munich, Germany.
  5. Dirk Tasche, 2012. "Bounds for rating override rates," Papers 1203.2287, arXiv.org, revised Aug 2012.
  6. Divino, Jose Angelo & Rocha, LĂ­neke Clementino Sleegers, 2013. "Probability of default in collateralized credit operations," The North American Journal of Economics and Finance, Elsevier, Elsevier, vol. 25(C), pages 276-292.

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