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Quality Control for Structural Credit Risk Models

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  • Elena Andreou
  • Eric Ghysels

Abstract

Over the last four decades, a large number of structural models have been developed to estimate and price credit risk. The focus of the paper is on a neglected issue pertaining to fundamental shifts in the structural parameters governing default. We propose formal quality control procedures that allow risk managers to monitor fundamental shifts in the structural parameters of credit risk models. The procedures are sequential - hence apply in real time. The basic ingredients are the key processes used in credit risk analysis, such as most prominently the Merton distance to default process as well as financial returns. Moreover, while we propose different monitoring processes, we also show that one particular process is optimal in terms of minimal detection time of a break in the drift process and relates to the Radon-Nikodym derivative for a change of measure.

Suggested Citation

  • Elena Andreou & Eric Ghysels, 2007. "Quality Control for Structural Credit Risk Models," University of Cyprus Working Papers in Economics 3-2007, University of Cyprus Department of Economics.
    • Handle: RePEc:ucy:cypeua:3-2007
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    File URL: https://papers.econ.ucy.ac.cy/RePEc/papers/07-03.pdf
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    Cited by:

    1. Lorne N. Switzer & Jun Wang, 2013. "Default Risk Estimation, Bank Credit Risk, and Corporate Governance," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 22(2), pages 91-112, May.
    2. Harry J. Turtle & Chengping Zhang, 2015. "Structural breaks and portfolio performance in global equity markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 909-922, June.
    3. Vasyl Golosnoy, 2018. "Sequential monitoring of portfolio betas," Statistical Papers, Springer, vol. 59(2), pages 663-684, June.

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