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A Simple Continuous Measure of Credit Risk

Author

Listed:
  • Hans Byström
  • Oh-Kang Kwon

Abstract

This paper introduces a simple continuous measure of credit risk that associates to each firm a risk parameter related to the firm's risk-neutral default intensity. These parameters can be computed from quoted bond prices and allow assignment of credit ratings much finer than those provided by various rating agencies. We estimate the risk measures on a daily basis for a sample of US firms and compare them with the corresponding ratings provided by Moody's and the distance to default measures calculated using the Merton (1974) model. The three measures group the sample of firms into various risk classes in a similar but far from identical way, possibly reflecting the models' different forecasting horizons. Among the three measures, the highest rank correlation is found between our continuous measure and Moody's ratings. The techniques in this paper can be used to extract the entire distribution of inter-temporal risk-neutral default intensities which is useful for time-to-default estimators as well as for pricing credit derivatives.

Suggested Citation

  • Hans Byström & Oh-Kang Kwon, 2003. "A Simple Continuous Measure of Credit Risk," Research Paper Series 111, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:111
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    File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp111.pdf
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    Cited by:

    1. Aleksandra Wójcicka, 2012. "Calibration of a credit rating scale for Polish companies," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(3), pages 63-73.
    2. Su-Lien Lu, 2013. "Measuring credit risk by using a parameterized model under risk-neutral measure," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 719-723, May.
    3. Mariusz Górajski & Dobromił Serwa & Zuzanna Wośko, 2019. "Measuring expected time to default under stress conditions for corporate loans," Empirical Economics, Springer, vol. 57(1), pages 31-52, July.
    4. Panagiotis K. Staikouras, 2012. "A Theoretical and Empirical Review of the EU Regulation on Credit Rating Agencies: In Search of Truth, Not Scapegoats," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 21(2), pages 71-155, May.
    5. Carl Chiarella & Christina Nikitopoulos Sklibosios & Erik Schlögl, 2007. "A Markovian Defaultable Term Structure Model With State Dependent Volatilities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 155-202.
    6. Christina Nikitopoulos-Sklibosios, 2005. "A Class of Markovian Models for the Term Structure of Interest Rates Under Jump-Diffusions," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 6, July-Dece.
    7. Aleksandra Wójcicka-Wójtowicz, 2018. "Credit risk mangement in finance - a review of various approaches," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(4), pages 99-106.
    8. Christina Nikitopoulos-Sklibosios, 2005. "A Class of Markovian Models for the Term Structure of Interest Rates Under Jump-Diffusions," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2005, January-A.
    9. Baker, H. Kent & Kumar, Satish & Goyal, Kirti & Sharma, Anuj, 2021. "International review of financial analysis: A retrospective evaluation between 1992 and 2020," International Review of Financial Analysis, Elsevier, vol. 78(C).

    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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