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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://shs.hal.science/halshs-00587769
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    References listed on IDEAS

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    1. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    2. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    3. 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.
    4. Micha, Bernard, 1984. "Analysis of business failures in France," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 281-291, June.
    5. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    6. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    7. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    8. Beaver, Wh, 1968. "Market Prices, Financial Ratios, And Prediction Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 179-192.
    9. 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.
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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. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    4. Firescu Victoria & Popescu Jenica & Popa Bogdan, 2017. "Comparative Analysis Of Bankruptcy Risk For Some Romanian Societies Listed On Bucharest Stock Exchange," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 138-146, December.
    5. 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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