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Bayesian corporate bond pricing and credit default swap premium models for deriving default probabilities and recovery rates

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  • Tomohiro Ando

    (Keio University, Kanagawa, Japan)

Abstract

This paper develops a Bayesian method by jointly formulating a corporate bond (CB) pricing model and credit default swap (CDS) premium pricing models to estimate the term structure of default probabilities and the recovery rate. These parameters are formulated by incorporating firm characteristics such as industry, credit rating and Balance Sheet/Profit and Loss information. A cross-sectional model valuing all given CB prices and CDS premiums is considered. The quantities derived are regarded as what market participants infer in forming CB prices and CDS premiums. We also develop a statistical significance test procedure without any distributional assumptions for the specified model. An empirical analysis is conducted using Japanese CB and CDS market data.

Suggested Citation

  • Tomohiro Ando, 2014. "Bayesian corporate bond pricing and credit default swap premium models for deriving default probabilities and recovery rates," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 454-465, March.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:3:p:454-465
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    Cited by:

    1. Mercadier, Mathieu & Lardy, Jean-Pierre, 2019. "Credit spread approximation and improvement using random forest regression," European Journal of Operational Research, Elsevier, vol. 277(1), pages 351-365.
    2. Jonathan Crook & David Edelman, 2014. "Special issue credit risk modelling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 321-322, March.

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