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Times-To-Default:Life Cycle, Global and Industry Cycle Impact

Author

Listed:
  • Fabien Couderc

    (University of Geneva & FAME)

  • Olivier Renault

    (Warwick Business School,UK)

Abstract

This paper studies times-to-default of individual firms across risk classes. Using Standard & Poor’s ratings database we investigate common drivers of default probabilities and address two shortcomings of many papers in the credit literature. First, we identify relevant determinants of default intensities using business cycle and credit market proxies in addition to financial markets indicators, and reveal the time-span of their impacts. We show that misspecifications of financial based factor models are largely corrected by non financial information. Second, we show that past economic conditions are of prime importance in explaining probability changes: current shocks and long term trends jointly determine default probabilities. Finally, we exhibit industry contagion indicators which might be helpful to capture leading and persistency patterns of the default cycle.

Suggested Citation

  • Fabien Couderc & Olivier Renault, 2005. "Times-To-Default:Life Cycle, Global and Industry Cycle Impact," FAME Research Paper Series rp142, International Center for Financial Asset Management and Engineering.
    • Handle: RePEc:fam:rpseri:rp142
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    File URL: http://www.swissfinanceinstitute.ch/rp142.pdf
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    Cited by:

    1. Correia, Ricardo & Población, Javier, 2015. "A structural model with Explicit Distress," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 112-130.
    2. Apergis, Nicholas, 2019. "Oil prices and corporate high-yield spreads: Evidence from panels of nonenergy and energy European firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 34-40.
    3. Marco Muscettola, 2019. "Distinctiveness of Highly Risky Italian Firms That are Saved-A Logistic Approach," Applied Economics and Finance, Redfame publishing, vol. 6(1), pages 64-73, January.
    4. Ming-Chin Hung & Yung-Kang Ching & Shih-Kuei Lin, 2021. "Impact of COVID-19 on the Robustness of the Probability of Default Estimation Model," Mathematics, MDPI, vol. 9(23), pages 1-13, November.

    More about this item

    Keywords

    censored durations; proportional hazard; business cycle; credit cycle; default determinants; default prediction;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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