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On the determinants of the implied default barrier

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  • Dionne, Georges

    (HEC Montreal, Canada Research Chair in Risk Management)

  • Laajimi, Sadok

    (HEC Montreal, Canada Research Chair in Risk Management)

Abstract

Many structural models specify the default barrier, but few have explored its empirical significance and determinants. The effect of liquidity shortage is not well measured, nor is the effect of strategic default well identified. We use the maximum likelihood (ML) approach to estimate the default barrier model and the Merton-KMV model using market values of equities in a sample of 762 public industrial firms. The estimated barrier is below leverage in our sample. The default probability from the two structural models provides similar in-sample fits, but the default barrier framework achieves better out-of-sample forecasts. Our analysis also focuses on the factors that influence the level of the implied default barrier when leverage is endogenous, and shows that endogenous leverage is not the only determinant of the default barrier as predicted by the standard structural credit model. The implied default threshold is positively related to financing costs, and negatively related to liquidity, asset volatility, and firm size. Three strategic default variables (liquidation costs, renegotiation frictions and equity holders’ bargaining power) increase the implied default barrier level. This evidence supports strategic default models.

Suggested Citation

  • Dionne, Georges & Laajimi, Sadok, 2011. "On the determinants of the implied default barrier," Working Papers 09-2, HEC Montreal, Canada Research Chair in Risk Management.
  • Handle: RePEc:ris:crcrmw:2009_002
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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; liquidity shortage;
    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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