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Default Prediction for Small-Medium Enterprises in France: A comparative approach

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  • Sami BEN JABEUR
  • Youssef FAHMI

Abstract

The aim of this paper is to compare between three statistical methods in predicting corporate financial distress. We will use the Discriminant Analysis, Logit model and Random Forest. These approaches are based on a sample of 800 companies during

Suggested Citation

  • Sami BEN JABEUR & Youssef FAHMI, 2014. "Default Prediction for Small-Medium Enterprises in France: A comparative approach," Working Papers 2014-319, Department of Research, Ipag Business School.
  • Handle: RePEc:ipg:wpaper:2014-319
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    File URL: https://faculty-research.ipag.edu/wp-content/uploads/recherche/WP/IPAG_WP_2014_319.pdf
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    References listed on IDEAS

    as
    1. Catherine Refait, 2004. "La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux," Économie et Prévision, Programme National Persée, vol. 162(1), pages 129-147.
    2. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    4. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    5. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    6. Chou, Hsin-I & Li, Hui & Yin, Xiangkang, 2010. "The effects of financial distress and capital structure on the work effort of outside directors," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 300-312, June.
    7. Wruck, Karen Hopper, 1990. "Financial distress, reorganization, and organizational efficiency," Journal of Financial Economics, Elsevier, vol. 27(2), pages 419-444, October.
    8. Bardos, Mireille, 1998. "Detecting the risk of company failure at the Banque de France," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1405-1419, October.
    9. Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "Estimating financial distress likelihood," Journal of Business Research, Elsevier, vol. 61(9), pages 995-1003, September.
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