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On the Determinants of the Implied Default Barrier

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  • Georges Dionne
  • Sadok Laajimi

Abstract

We use the maximum likelihood (ML) estimation approach to estimate the default barriers from market values of equities for a sample of 762 public industrial Canadian firms. The ML approach allows us to estimate the asset instantaneous drift, volatility and barrier level simultaneously, when the firm's equity is priced as a Down-and-Out European call (DOC) option. We find that the estimated barrier is positive and significant in our sample. Moreover, we compare the default prediction accuracy of the DOC framework with the KMV-Merton approach. Using probit estimation, we find that the default probability from the two structural models provides similar in-sample fits, but the barrier option framework achieves better out-of-sample forecasts. Regression analysis shows that leverage is not the only determinant of the default barrier. The implied default threshold is also positively related to financing costs, and negatively to liquidity, asset volatility and firm size. We also find that liquidation costs, renegotiation frictions and equity holders' bargaining power increase the implied default barrier level.

Suggested Citation

  • Georges Dionne & Sadok Laajimi, 2009. "On the Determinants of the Implied Default Barrier," Cahiers de recherche 0914, CIRPEE.
  • Handle: RePEc:lvl:lacicr:0914
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    Cited by:

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    2. Zvika Afik & Ohad Arad & Koresh Galil, 2012. "Using Merton model: an empirical assessment of alternatives," Working Papers 1202, Ben-Gurion University of the Negev, Department of Economics.
    3. Perko, Igor, 2017. "Behaviour-based short-term invoice probability of default evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1045-1054.
    4. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
    5. Amaya, Diego & Boudreault, Mathieu & McLeish, Don L., 2019. "Maximum likelihood estimation of first-passage structural credit risk models correcting for the survivorship bias," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 297-313.
    6. Afik, Zvika & Arad, Ohad & Galil, Koresh, 2016. "Using Merton model for default prediction: An empirical assessment of selected alternatives," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 43-67.
    7. Lovreta, Lidija & Silaghi, Florina, 2020. "The surface of implied firm’s asset volatility," Journal of Banking & Finance, Elsevier, vol. 112(C).
    8. Brian Kantor & Christopher Holdsworth, 2010. "Lessons from the Global Financial Crisis (Or Why Capital Structure Is Too Important to Be Left to Regulation)," Journal of Applied Corporate Finance, Morgan Stanley, vol. 22(3), pages 112-122, June.

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    More about this item

    Keywords

    Barrier option; default barrier; bankruptcy prediction; maximum likelihood estimation; strategic default;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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