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Forecasting Corporate Distress in the Asian and Pacific Region

Author

Listed:
  • Russ Moro
  • Wolfgang Härdle
  • Saeideh Aliakbari
  • Linda Hoffmann

Abstract

This study analyses credit default risk for firms in the Asian and Pacific region by applying two methodologies: a Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of default, leverage ratios and the company size display a higher discriminating power compared to others. An analysis of the dependencies between PD and financial ratios is provided along with a comparison with Europe (Germany). With respect to forecasting accuracy the SVM has a lower model risk than the Logit on average and displays a more robust performance. This result holds true across different years.

Suggested Citation

  • Russ Moro & Wolfgang Härdle & Saeideh Aliakbari & Linda Hoffmann, 2011. "Forecasting Corporate Distress in the Asian and Pacific Region," SFB 649 Discussion Papers SFB649DP2011-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    • Handle: RePEc:hum:wpaper:sfb649dp2011-023
    as

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    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-023.pdf
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    References listed on IDEAS

    as
    1. Rodrigo Herrera & Bernhard Schipp, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers SFB649DP2011-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    More about this item

    Keywords

    Credit risk; Bankruptcy; Asian companies; SVM;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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