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The Dynamics of Credit Spreads and Ratings Migrations

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  • Farnsworth, Heber
  • Li, Tao

Abstract

There is a large and growing literature on how to model the dynamics of the default-free term structure to fit the observed historical data. Much less is known about how best to model the dynamics of defaultable yield curves. This paper develops a class of defaultable term structure models that is tractable enough to be empirically implemented and flexible enough to capture some important behaviors of the credit spreads in the data. We compare two non-nested models within this class using a Bayesian estimation technique, which helps to solve the problem of latent state variables. The Bayesian approach also enables us to test the two non-nested models on the basis of the Bayes factor. The results strongly suggest that models with constant transition probabilities will not be able to fit the observed dynamics of inter-rating spreads.

Suggested Citation

  • Farnsworth, Heber & Li, Tao, 2007. "The Dynamics of Credit Spreads and Ratings Migrations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 595-620, September.
    • Handle: RePEc:cup:jfinqa:v:42:y:2007:i:03:p:595-620_00
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    Citations

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    Cited by:

    1. Silvia Centanni & Immacolata Oliva & Paola Tardelli, 2017. "Credit Risk in an Economy with New Firms Arrivals," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 891-912, September.
    2. Dionne, Georges & Gauthier, Geneviève & Hammami, Khemais & Maurice, Mathieu & Simonato, Jean-Guy, 2011. "A reduced form model of default spreads with Markov-switching macroeconomic factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1984-2000, August.
    3. Chateau, Jean-Pierre D., 2011. "Contribution à la réglementation de Bâle-3 : de la consistance interne du continuum du crédit commercial en marquant à la « valeur de modèle » le risque de crédit des engagements de crédit," L'Actualité Economique, Société Canadienne de Science Economique, vol. 87(4), pages 445-479, décembre.
    4. Enrico Laghi & Michele Di Marcantonio & Eugenio D'Amico, 2014. "Estimating credit default swap spreads using accounting data, market quotes and credit ratings: the European Banks Case," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2014(2-3-4), pages 59-81.
    5. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    6. Haitao Li & Tao Li & Cindy Yu, 2013. "No-Arbitrage Taylor Rules with Switching Regimes," Management Science, INFORMS, vol. 59(10), pages 2278-2294, October.
    7. Shouzhen Zeng & Junfang Hu & Fengjuan Gu & Llopis- Albert Carlos, 2023. "Financial information, green certification, government subsidies and green bond credit spreads–evidence from China," International Entrepreneurship and Management Journal, Springer, vol. 19(1), pages 321-341, March.
    8. Thomas Lagner & Dodozu Knyphausen‐Aufseß, 2012. "Rating Agencies as Gatekeepers to the Capital Market: Practical Implications of 40 Years of Research," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 21(3), pages 157-202, August.
    9. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.

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