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Exploring the relationship between credit spreads and default probabilities


  • Mark J Manning


Contrary to theory, recent empirical work suggests that changing default expectations can explain only a fraction of the variability in credit spreads. This paper takes a fresh look at this question, relating credit spreads for a sample of investment-grade bonds issued by UK industrial companies to default probabilities generated by the Bank of England's Merton model of corporate failure. For the highest quality corporate issues, where the probability of default is low, this factor explains relatively little of the variation in credit spreads. For such bonds, common market factors - perhaps related to liquidity conditions - appear to be of greater importance. This is consistent with previous empirical work. For lower-rated investment-grade bonds, however, the probability of default is found to be a more important determinant of credit spreads, explaining around a third of variability in a pooled regression. When coefficients are allowed to vary at the level of the individual issue, explanatory power rises to 50% for this group. This is much higher than previous studies have found, reflecting both the more direct application of the Merton model and the recognition that idiosyncrasies in factors such as liquidity conditions and expected recovery rates are likely to undermine results from pooled estimation.

Suggested Citation

  • Mark J Manning, 2004. "Exploring the relationship between credit spreads and default probabilities," Bank of England working papers 225, Bank of England.
  • Handle: RePEc:boe:boeewp:225

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    References listed on IDEAS

    1. Roberto Blanco & Simon Brennan & Ian W Marsh, 2004. "An empirical analysis of the dynamic relationship between investment-grade bonds and credit default swaps," Bank of England working papers 211, Bank of England.
    2. M. Tudela & G. Young, 2005. "A Merton-Model Approach To Assessing The Default Risk Of Uk Public Companies," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 737-761.
    3. Pesaran, M. H. & Shin, Y. & Smith, R. P., 1997. "Pooled Estimation of Long-run Relationships in Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9721, Faculty of Economics, University of Cambridge.
    4. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    5. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    6. Edwin J. Elton, 2001. "Explaining the Rate Spread on Corporate Bonds," Journal of Finance, American Finance Association, vol. 56(1), pages 247-277, February.
    7. Longstaff, Francis A & Schwartz, Eduardo S, 1995. " A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    8. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    9. Pierre Collin-Dufresne, 2001. "The Determinants of Credit Spread Changes," Journal of Finance, American Finance Association, vol. 56(6), pages 2177-2207, December.
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    Cited by:

    1. Georges Dionne & Geneviève Gauthier & Khemais Hammami & Mathieu Maurice & Jean-Guy Simonato, 2010. "Default Risk in Corporate Yield Spreads," Financial Management, Financial Management Association International, vol. 39(2), pages 707-731, June.
    2. Horst Rottmann & Franz Seitz, 2004. "Credit Spreads und ihre Determinanten in Deutschland," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(24), pages 10-14, December.
    3. repec:bpj:strimo:v:34:y:2017:i:1-2:p:55-67:n:1 is not listed on IDEAS
    4. Lutz Hahnenstein & Klaus Röder, 2007. "Who hedges more when leverage is endogenous? A testable theory of corporate risk management under general distributional conditions," Review of Quantitative Finance and Accounting, Springer, vol. 28(4), pages 353-391, May.
    5. International Monetary Fund, 2016. "United Kingdom; Financial Sector Assessment Program-Stress Testing the Banking Sector-Technical Note," IMF Staff Country Reports 16/163, International Monetary Fund.

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