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An empirical evaluation of structural credit risk models

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  • Nikola A. Tarashev

Abstract

This paper evaluates empirically the performance of six structural credit risk models by comparing the probabilities of default (PDs) they deliver to ex post default rates. In contrast to previous studies pursuing similar objectives, the paper employs firm-level data and finds that theory-based PDs tend to match closely the actual level of credit risk and to account for its time path. At the same time, nonmodelled macro variables from the financial and real sides of the economy help to substantially improve the forecasts of default rates. The finding suggests that theory-based PDs fail to fully reflect the dependence of credit risk on the business and credit cycles. Most of the upbeat conclusions regarding the performance of the PDs are due to models with endogenous default. For their part, frameworks that assume exogenous default tend to underpredict credit risk. Three borrower characteristics influence materially the predictions of the models: the leverage ratio; the default recovery rate; and the risk-free rate of return.

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Bibliographic Info

Paper provided by Bank for International Settlements in its series BIS Working Papers with number 179.

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Length: 48 pages
Date of creation: Jul 2005
Date of revision:
Handle: RePEc:bis:biswps:179

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Keywords: Basel II; Probability of default; Credit risk models; Macroeconomic factors of credit risk;

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  1. Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series, CIRJE, Faculty of Economics, University of Tokyo CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
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  3. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, American Finance Association, vol. 62(1), pages 93-117, 02.
  4. Young Ho Eom, 2004. "Structural Models of Corporate Bond Pricing: An Empirical Analysis," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 17(2), pages 499-544.
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  6. Hayne E. Leland., 1994. "Corporate Debt Value, Bond Covenants, and Optimal Capital Structure," Research Program in Finance Working Papers, University of California at Berkeley RPF-233, University of California at Berkeley.
  7. Amato, Jeffery D. & Furfine, Craig H., 2004. "Are credit ratings procyclical?," Journal of Banking & Finance, Elsevier, Elsevier, vol. 28(11), pages 2641-2677, November.
  8. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers, Massachusetts Institute of Technology (MIT), Sloan School of Management 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  9. Leland, Hayne E & Toft, Klaus Bjerre, 1996. " Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Journal of Finance, American Finance Association, American Finance Association, vol. 51(3), pages 987-1019, July.
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Cited by:
  1. Borio, Claudio & Zhu, Haibin, 2012. "Capital regulation, risk-taking and monetary policy: A missing link in the transmission mechanism?," Journal of Financial Stability, Elsevier, Elsevier, vol. 8(4), pages 236-251.
  2. Wikil Kwak & Yong Shi & Gang Kou, 2012. "Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach," Review of Quantitative Finance and Accounting, Springer, Springer, vol. 38(4), pages 441-453, May.
  3. Borio, Claudio, 2006. "Monetary and financial stability: Here to stay?," Journal of Banking & Finance, Elsevier, Elsevier, vol. 30(12), pages 3407-3414, December.
  4. Gianni De Nicoló & Alexander F. Tieman, 2006. "Economic Integration and Financial Stability," IMF Working Papers 06/296, International Monetary Fund.
  5. Wilson Sy, 2007. "A Causal Framework for Credit Default Theory," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 204, Quantitative Finance Research Centre, University of Technology, Sydney.
  6. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, Bank for International Settlements, March.

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