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Exploring the relationship between credit spreads and default probabilities

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  • Mark J Manning

Abstract

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.

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  • 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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    File URL: http://www.bankofengland.co.uk/research/Documents/workingpapers/2004/WP225.pdf
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    References listed on IDEAS

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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 and their determinants in Germany," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(24), pages 10-14, December.
    3. Moro Russ A. & Härdle Wolfgang K. & Schäfer Dorothea, 2017. "Company rating with support vector machines," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 55-67, June.
    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 2016/163, International Monetary Fund.

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