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Credit Risk and Risk Neutral Default Probabilities: Information About Migrations and Defaults

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  • Delianedis, Gordon
  • Geske, Robert

Abstract

Default probabilities are important to the credit markets. Changes in default probabilities may forecast credit rating migrations to other rating levels or to default. Such rating changes can affect the firm’s cost of capital, credit spreads, bond returns, and the prices and hedge ratios of credit derivatives. While rating agencies such as Moodys and Standard & Poors compute historical default frequencies, option models can also be used to calculate forward looking or expected default frequencies. In this paper, we compute risk neutral probabilities or default (RNPD) using the diffusion models of Merton (1974) and Geske (1977). It is shown that the Geske model produces a term structure of RNPD’s, and the shape of this term structure may forecast impending credit events. Next, it is shown that these RNPD’s serve as bounds to estimates of actual default probabilities. Furthermore, the RNPD’s exhibit the same comparative statics as the estimates of actual default probabilities. Also, the risk neutral default probabilities may be more accurately estimated than actual default probabilities because they do not require an estimate of the firm’s drift. Given these similarities and advantages of RNPD’s, their estimates may possess significant information about credit events. To confirm this an event study of the relation between RNPD and rating migrations is conducted. We first show that these RNPD’s from both the Merton and Geske models do possess significant and very early information about credit rating migrations.While the sample of firms that actually default during this time period is small, changes in the shape of the term structure of default probabilities appears to detect impending migrations to default. This is shown to be consistent with an inverted term structure of default probabilities, where prior to an impending default, the short term default probability is higher than the forward default probability. Finally, since rating migrations to either lower ratings or to default can be detected months in advance these credit events may not be a surprise.

Suggested Citation

  • Delianedis, Gordon & Geske, Robert, 1998. "Credit Risk and Risk Neutral Default Probabilities: Information About Migrations and Defaults," University of California at Los Angeles, Anderson Graduate School of Management qt7dm2d31p, Anderson Graduate School of Management, UCLA.
  • Handle: RePEc:cdl:anderf:qt7dm2d31p
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    Cited by:

    1. Yu-Lin Huang, 2008. "The pricing of conditional performance guarantees with risky collateral," Construction Management and Economics, Taylor & Francis Journals, vol. 26(9), pages 967-978.
    2. Sanjiv Ranjan Das & Rangarajan K. Sundaram, 1998. "A Direct Approach to Arbitrage-Free Pricing of Derivatives," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-013, New York University, Leonard N. Stern School of Business-.
    3. Sironi, Andrea, 2002. "Strengthening banks' market discipline and leveling the playing field: Are the two compatible?," Journal of Banking & Finance, Elsevier, vol. 26(5), pages 1065-1091, May.
    4. Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
    5. Majumder, Debasish, 2006. "Inefficient markets and credit risk modeling: Why Merton's model failed," Journal of Policy Modeling, Elsevier, vol. 28(3), pages 307-318, April.
    6. Anderson, Ronald & Sundaresan, Suresh, 2000. "A comparative study of structural models of corporate bond yields: An exploratory investigation," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 255-269, January.
    7. Acharya, Viral V & Das, Sanjiv Ranjan & Sundaram, Rangarajan K, 2002. "Pricing Credit Derivatives with Rating Transitions," CEPR Discussion Papers 3329, C.E.P.R. Discussion Papers.
    8. Peña Sánchez de Rivera, Juan Ignacio & Forte, Santiago, 2003. "Debt refinancing and credit risk," DEE - Working Papers. Business Economics. WB wb031704, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    9. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    10. Berg, Tobias & Kaserer, Christoph, 2008. "Linking credit risk premia to the equity premium," CEFS Working Paper Series 2008-01, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    11. Maltritz, Dominik, 2008. "Modelling the dependency between currency and debt crises: An option based approach," Economics Letters, Elsevier, vol. 100(3), pages 344-347, September.
    12. Stefan Eichler & Dominik Maltritz, 2010. "On the look-out for a white knight: options-based calculation of probability and expected value of increased bids in hostile takeover battles," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1033-1036.
    13. Kanak Patel & Ricardo Pereira, 2007. "Expected Default Probabilities in Structural Models: Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 34(1), pages 107-133, January.
    14. Suresh Sundaresan, 2001. "Supervisor and Market Analysts: What Should Research be Seeking?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 20(2), pages 275-280, October.
    15. Posch, Peter N., 2011. "Time to change. Rating changes and policy implications," Journal of Economic Behavior & Organization, Elsevier, vol. 80(3), pages 641-656.
    16. Yu-lin Huang & Wei Lin, 2010. "Does debt structure matter? Estimating contractor default barrier by the down-and-out call option approach," Construction Management and Economics, Taylor & Francis Journals, vol. 28(9), pages 947-958.
    17. Mark S. Carey & Mark Hrycay, 2000. "Parameterizing credit risk models with rating data," Finance and Economics Discussion Series 2000-47, Board of Governors of the Federal Reserve System (U.S.).

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