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Investigating the sources of default risk: lessons from empirically evaluating credit risk models

Author

Listed:
  • Gurdip Bakshi
  • Dilip B. Madan
  • Frank X. Zhang

Abstract

From a credit risk perspective, little is known about the distress factors -- economy-wide or firm-specific -- that are important in explaining variations in defaultable coupon yields. This paper proposes and empirically tests a family of credit risk models. Empirically, we find that firm-specific distress factors play a role (beyond treasuries) in explaining defaultable coupon bond yields. Credit risk models that take into consideration leverage and book-to-market are found to reduce out-of-sample yield fitting errors (for the majority of firms). Moreover, the empirical evidence suggests that interest rate risk may be of first-order prominence for pricing and hedging. Measured by both out-of-sample pricing and hedging errors, the credit risk models perform relatively better for high grade bonds. Controlling for credit rating, the model performance is generally superior for longer maturity bonds compared to its shorter maturity counterparts. Using equity as an instrument reduces hedging errors. This paper provides an empirical investigation of credit risk models using observable economic factors.

Suggested Citation

  • Gurdip Bakshi & Dilip B. Madan & Frank X. Zhang, 2001. "Investigating the sources of default risk: lessons from empirically evaluating credit risk models," Finance and Economics Discussion Series 2001-15, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2001-15
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    References listed on IDEAS

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    Cited by:

    1. Rong Fan & Joseph Haubrich & Peter Ritchken & James Thomson, 2003. "Getting the Most Out of a Mandatory Subordinated Debt Requirement," Journal of Financial Services Research, Springer;Western Finance Association, vol. 24(2), pages 149-179, October.
    2. Frank X. Zhang, 2003. "What did the credit market expect of Argentina default? Evidence from default swap data," Finance and Economics Discussion Series 2003-25, Board of Governors of the Federal Reserve System (U.S.).
    3. Duffie, Darrell, 2005. "Credit risk modeling with affine processes," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2751-2802, November.
    4. Becchetti, Leonardo & Carpentieri, Andrea & Hasan, Iftekhar, 2009. "The determinants of option-adjusted delta credit spreads : a comparative analysis of the United States, the United Kingdom and the euro area," Research Discussion Papers 34/2009, Bank of Finland.
    5. Aneta Ptak-Chmielewska & Paweł Kopciuszewski, 2023. "Application of the Bayesian approach in loss given default modelling," Bank i Kredyt, Narodowy Bank Polski, vol. 54(6), pages 625-650.
    6. Chu, Quentin C. & Pittman, Deborah N. & Yu, Linda Q., 2003. "Real rates, nominal rates, and the Fisherian link," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 189-205.
    7. Quentin Chu & Deborah Pittman & Linda Yu, 2005. "Information Risk in TIPS Market: An Analysis of Nominal and Real Interest Rates," Review of Quantitative Finance and Accounting, Springer, vol. 24(3), pages 235-250, May.
    8. Becchetti, Leonardo & Carpentieri, Andrea & Hasan, Iftekhar, 2009. "The determinants of option-adjusted delta credit spreads: a comparative analysis of the United States, the United Kingdom and the euro area," Bank of Finland Research Discussion Papers 34/2009, Bank of Finland.
    9. Lekkos, Ilias, 2007. "Modelling multiple term structures of defaultable bonds with common and idiosyncratic state variables," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 783-817, December.
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    Keywords

    Credit; Risk; Econometric models;
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