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The performance of credit rating systems in the assessment of collateral used in Eurosystem monetary policy operations

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Author Info

  • François Coppens

    () (National Bank of Belgium, Microeconomic Information Department)

  • Fernando Gonzáles

    (European Central Bank)

  • Gerhard Winkler

    () (Oesterreichische Nationalbank)

Abstract

The aims of this paper are twofold: first, we attempt to express the threshold of a single “A” rating as issued by major international rating agencies in terms of annualised probabilities of default. We use data from Standard & Poor’s and Moody’s publicly available rating histories to construct confidence intervals for the level of probability of default to be associated with the single “A” rating. The focus on the single A rating level is not accidental, as this is the credit quality level at which the Eurosystem considers financial assets to be eligible collateral for its monetary policy operations. The second aim is to review various existing validation models for the probability of default which enable the analyst to check the ability of credit assessment systems to forecast future default events. Within this context the paper proposes a simple mechanism for the comparison of the performance of major rating agencies and that of other credit assessment systems, such as the internal ratings-based systems of commercial banks under the Basel II regime. This is done to provide a simple validation yardstick to help in the monitoring of the performance of the different credit assessment systems participating in the assessment of eligible collateral underlying Eurosystem monetary policy operations. Contrary to the widely used confidence interval approach, our proposal, based on an interpretation of p-values as frequencies, guarantees a convergence to an ex ante fixed probability of default (PD) value. Given the general characteristics of the problem considered, we consider this simple mechanism to also be applicable in other contexts.

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Bibliographic Info

Paper provided by National Bank of Belgium in its series Working Paper Research with number 118.

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Length: 39 pages
Date of creation: Sep 2007
Date of revision:
Handle: RePEc:nbb:reswpp:200710-12

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Keywords: credit risk; rating; probability of default (PD); performance checking; backtesting;

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References

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  1. Michael B. Gordy, 1998. "A comparative anatomy of credit risk models," Finance and Economics Discussion Series 1998-47, Board of Governors of the Federal Reserve System (U.S.).
  2. Richard Cantor & Frank Packer & Kevin Cole, 1997. "Split ratings and the pricing of credit risk," Research Paper 9711, Federal Reserve Bank of New York.
  3. Crouhy, Michel & Galai, Dan & Mark, Robert, 2001. "Prototype risk rating system," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 47-95, January.
  4. Dirk Tasche, 2003. "A traffic lights approach to PD validation," Papers cond-mat/0305038, arXiv.org.
  5. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
  6. Krahnen, Jan Pieter & Weber, Martin, 2001. "Generally accepted rating principles: A primer," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 3-23, January.
  7. Hull, John & Predescu, Mirela & White, Alan, 2004. "The relationship between credit default swap spreads, bond yields, and credit rating announcements," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2789-2811, November.
  8. Christensen, Jens H.E. & Hansen, Ernst & Lando, David, 2004. "Confidence sets for continuous-time rating transition probabilities," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2575-2602, November.
  9. Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
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Cited by:
  1. Van Beveren, Ilke & Bernard, Andrew B & Blanchard, Emily J & Vandenbussche, Hylke, 2011. "Carry-along trade," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/387875, Katholieke Universiteit Leuven.
  2. Joachim Keller, 2008. "Agency problems in structured finance – a case study of European CLOs," Working Paper Document 137, National Bank of Belgium.
  3. François Coppens & Fabienne Verduyn, 2009. "Analysis of business demography using markov chains : an application to Belgian data," Working Paper Research 170, National Bank of Belgium.

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