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La Prediction De Faillite Des Entreprises Tunisiennes Par La Regression Logistique

Author

Listed:
  • Hamadi Matoussi

    (ISCAE - ISCAE)

  • Rim Mouelhi

    (ISCAE - ISCAE)

  • Sayah Salah

    (ESSEC - Université de Tunis)

Abstract

Nous avons cherché dans ce papier à modéliser la probabilité de défaillance des entreprises tunisiennes au terme d'une regression logistique. Il ressort des résultats obtenus un taux de bon classement des entreprises dans leur groupe d'origine de l'ordre de 87% deux ans avant et de 91% un an avant la défaillance. Ce taux est de l'ordre de 94% dans l'échantillon de contrôle. Nous soulignons, par ailleurs, le poids des ratios de trésorerie, de solvabilité, d'équilibre et d'autonomie financière dans la détermination de la probabilité de défaillance ; ce qui est conforme à l'analyse financière classique basée sur la méthode des ratios

Suggested Citation

  • Hamadi Matoussi & Rim Mouelhi & Sayah Salah, 1999. "La Prediction De Faillite Des Entreprises Tunisiennes Par La Regression Logistique," Post-Print halshs-00587769, HAL.
  • Handle: RePEc:hal:journl:halshs-00587769
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00587769
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    File URL: https://halshs.archives-ouvertes.fr/halshs-00587769/document
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    References listed on IDEAS

    as
    1. repec:bla:joares:v:10:y:1972:i:1:p:167-179 is not listed on IDEAS
    2. Micha, Bernard, 1984. "Analysis of business failures in France," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 281-291, June.
    3. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    4. repec:bla:joares:v:22:y:1984:i::p:59-82 is not listed on IDEAS
    5. Dambolena, Ismael G & Khoury, Sarkis J, 1980. " Ratio Stability and Corporate Failure," Journal of Finance, American Finance Association, vol. 35(4), pages 1017-1026, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Blazy, Régis & Letaief, Aziza, 2017. "When secured and unsecured creditors recover the same: The emblematic case of the Tunisian corporate bankruptcies," Emerging Markets Review, Elsevier, vol. 30(C), pages 19-41.
    2. Zaghdoudi Khemais & Djebali Nesrine & Mezni Mohamed, 2016. "Credit Scoring and Default Risk Prediction: A Comparative Study between Discriminant Analysis & Logistic Regression," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(4), pages 39-53, April.
    3. Hamadi Matoussi & Aida Abdelmoula, 2008. "Using A Neural Network-Based Methodology for Credit–Risk Evaluation of A Tunisian Bank," Working Papers 408, Economic Research Forum, revised 06 Jan 2008.

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