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Recovery Rates, Default Probabilities And The Credit Cycle

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  • Max Bruche

    ()

  • Carlos González Aguado

    ()
    (CEMFI, Centro de Estudios Monetarios y Financieros)

Abstract

Default probabilities and recovery rate densities are not constant over the credit cycle; yet many models assume that they are. This paper proposes and estimates a model in which these two variables depend on an unobserved credit cycle, modelled by a twostate Markov chain. The proposed model is shown to produce a better fit to observed recoveries than a standard static approach. The model indicates that ignoring the dynamic nature of credit risk could lead to a severe underestimation of e.g. the 95% VaR, such that the actual VaR could be higher by a factor of up to 1.7. Also, the model indicates that the credit cycle is related to but distinct from the business cycle as e.g. determined by the NBER, which might explain why previous studies have found the power of macroeconomic variables in explaining default probabilities and recoveries to be low.

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Bibliographic Info

Paper provided by CEMFI in its series Working Papers with number wp2006_0612.

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Date of creation: Sep 2006
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Handle: RePEc:cmf:wpaper:wp2006_0612

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Keywords: Credit; recovery rate; default probability; business cycle; capital requirements; Markov chain.;

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References

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  1. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
  2. Olivier RENAULT & Olivier SCAILLET, 2003. "On the Way to Recovery: A Nonparametric Bias Free Estimation of Recovery Rate Densities," FAME Research Paper Series rp83, International Center for Financial Asset Management and Engineering.
  3. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
  4. Bangia, Anil & Diebold, Francis X. & Kronimus, Andre & Schagen, Christian & Schuermann, Til, 2002. "Ratings migration and the business cycle, with application to credit portfolio stress testing," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 445-474, March.
  5. Giacomo Giampieri & Mark Davis & Martin Crowder, 2005. "Analysis of default data using hidden Markov models," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 27-34.
  6. Bruce E. Hansen, 1995. "Erratum: The Likelihood ratio Test Under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Boston College Working Papers in Economics 296., Boston College Department of Economics.
  7. Diana Bonfim, 2007. "Credit Risk Drivers: Evaluating the Contribution of Firm Level Information and of Macroeconomic Dynamics," Working Papers w200707, Banco de Portugal, Economics and Research Department.
  8. Nickell, Pamela & Perraudin, William & Varotto, Simone, 2000. "Stability of rating transitions," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 203-227, January.
  9. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
  10. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-24, January.
  11. Jarrow, Robert A & Turnbull, Stuart M, 1995. " Pricing Derivatives on Financial Securities Subject to Credit Risk," Journal of Finance, American Finance Association, vol. 50(1), pages 53-85, March.
  12. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
  13. Carling, Kenneth & Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2007. "Corporate credit risk modeling and the macroeconomy," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 845-868, March.
  14. Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
  15. Long Chen & Pierre Collin-Dufresne & Robert S. Goldstein, 2009. "On the Relation Between the Credit Spread Puzzle and the Equity Premium Puzzle," Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3367-3409, September.
  16. Shleifer, Andrei & Vishny, Robert W, 1992. " Liquidation Values and Debt Capacity: A Market Equilibrium Approach," Journal of Finance, American Finance Association, vol. 47(4), pages 1343-66, September.
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