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Using Merton model: an empirical assessment of alternatives

Author

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  • Zvika Afik

    (Guilford Glazer faculty of Business and Management, Ben- Gurion University of the Negev, Israel)

  • Ohad Arad

    (Ben Gurion University of the Negev, Beer-Sheva, Israel)

  • Koresh Galil

    (Ben Gurion University of the Negev, Beer-Sheva, Israel)

Abstract

Merton (1974) suggested a structural model for default prediction which allows using timely information from the equity market. The literature describes several specifications to the application of the model, including methods presumably used by practitioners. However, recent studies demonstrate that these methods result in inferior estimates compared to simpler substitutes. We empirically examine various specification alternatives and find that the prediction goodness is only slightly sensitive to different choices of default barrier, whereas the choice of assets expected return and assets volatility is significant. Equity historical return and historical volatility produce underbiased estimates for assets expected return and assets volatility, especially for defaulting firms. Acknowledging these characteristics we suggest specifications that improve the model accuracy.

Suggested Citation

  • 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.
    • Handle: RePEc:bgu:wpaper:1202
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    References listed on IDEAS

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    Cited by:

    1. Jed DeVaro & Jin-Hyuk Kim & Nick Vikander, 2014. "Pay-for-(Persistent)-Luck: CEO Bonuses Under Relational and Formal Contracting," Discussion Papers 14-13, University of Copenhagen. Department of Economics.
    2. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
    3. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    4. Sim, Jaehun & Kim, Chae-Soo, 2019. "The value of renewable energy research and development investments with default consideration," Renewable Energy, Elsevier, vol. 143(C), pages 530-539.
    5. Jayasekera, Ranadeva, 2018. "Prediction of company failure: Past, present and promising directions for the future," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 196-208.
    6. Buddi Wibowo, 2017. "Systemic risk, bank’s capital buffer, and leverage," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 9(2), pages 150-158, April.
    7. Doumpos, Michael & Niklis, Dimitrios & Zopounidis, Constantin & Andriosopoulos, Kostas, 2015. "Combining accounting data and a structural model for predicting credit ratings: Empirical evidence from European listed firms," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 599-607.

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    More about this item

    Keywords

    Credit risk; Default prediction; Merton model; Bankruptcy prediction; Default barrier; Assets volatility;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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