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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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  • Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
  • Handle: RePEc:arx:papers:physics/0606071
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    References listed on IDEAS

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    1. Robert Rauhmeier & Harald Scheule, 2005. "Rating Properties and their Implication on Basel II-Capital," Published Paper Series 2005-2, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Dirk Tasche, 2002. "Remarks on the monotonicity of default probabilities," Papers cond-mat/0207555, arXiv.org.
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    Cited by:

    1. Tomislav Grebenar, 2018. "Behavioural Model of Assessment of Probability of Default and the Rating of Non-Financial Corporations," Working Papers 56, The Croatian National Bank, Croatia.
    2. Dirk Tasche, 2012. "Bounds for rating override rates," Papers 1203.2287, arXiv.org, revised Aug 2012.
    3. Rungporn Roengpitya, 2012. "Proposal of New Hybrid PD Estimation Models for the Low Default Portfolios (LDPs), Empirical Comparisons and Policy Implications," Working Papers 2012-03, Monetary Policy Group, Bank of Thailand.
    4. Divino, Jose Angelo & Rocha, Líneke Clementino Sleegers, 2013. "Probability of default in collateralized credit operations," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 276-292.
    5. Dirk Tasche, 2012. "The art of probability-of-default curve calibration," Papers 1212.3716, arXiv.org, revised Nov 2013.
    6. François Coppens & Fernando Gonzáles & Gerhard Winkler, 2007. "The performance of credit rating systems in the assessment of collateral used in Eurosystem monetary policy operations," Working Paper Research 118, National Bank of Belgium.
    7. Nehrebecka Natalia, 2018. "An Evaluation of the Discriminatory Power of Selected Polish Bankruptcy Prediction Models As Part of the Validation Process," Financial Sciences. Nauki o Finansach, Sciendo, vol. 23(4), pages 63-88, December.
    8. Patnaik, Ila & Mittal, Shalini & Pandey, Radhika, 2019. "Examining the trade-off between price and financial stability in India," Working Papers 19/248, National Institute of Public Finance and Policy.
    9. R. John Irwin & Timothy C. Irwin, 2013. "Appraising Credit Ratings: Does The Cap Fit Better Than The Roc?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 396-408, October.
    10. Morone, Marco & Cornaglia, Anna, 2010. "An econometric model to quantify benchmark downturn LGD on residential mortgages," MPRA Paper 25588, University Library of Munich, Germany.
    11. Raffaella Calabrese, 2011. "Cost-sensitive classification for rare events: an application to the credit rating model validation for SMEs," Working Papers 201134, Geary Institute, University College Dublin.
    12. Raffaella Calabrese, 2012. "Improving Classifier Performance Assessment of Credit Scoring Models," Working Papers 201204, Geary Institute, University College Dublin.
    13. Rungporn Roengpitya & Pratabjai Nilla-or, 2012. "Challenges on the Validation of PD Models for Low Default Portfolios (LDPs) and Regulatory Policy Implications," Working Papers 2012-02, Monetary Policy Group, Bank of Thailand.
    14. 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.
    15. Marcin Chlebus, 2014. "One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 37.

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