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La pertinence des cash-flows d'exploitation et de l'information financière traditionnelle dans la prévision de la détresse financière des entreprises tunisiennes

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  • Saoussen Boujelben

    (ISCAE de Tunis - ISCAE)

  • Fedhila Hassouna

    (ISCAE de Tunis - ISCAE)

Abstract

L'objectif de cet article est de valider la pertinence des cash-flows d'exploitation dans le domaine de prévision des difficultés financières. Il s'agit de vérifier si l'information renseignant sur les cash-flows d'exploitation prévoit mieux la cessation de paiement que l'information comptable basée sur les accruals. L'étude empirique ainsi menée sur 278 observations, a permis de se prononcer sur la supériorité des modèles LOGIT basés sur les cash-flows, par rapport à ceux basés sur l'information financière traditionnelle en terme de prévision de la cessation de paiement, et ce par la simple référence à leurs pouvoirs prédictifs. Toutefois, cette supériorité n'a été statistiquement validée par le test de Davidson & Mackinon (1981) que pour la prévision deux et trois ans à l'avance.

Suggested Citation

  • Saoussen Boujelben & Fedhila Hassouna, 2007. "La pertinence des cash-flows d'exploitation et de l'information financière traditionnelle dans la prévision de la détresse financière des entreprises tunisiennes," Post-Print halshs-00544881, HAL.
    • Handle: RePEc:hal:journl:halshs-00544881
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00544881
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    References listed on IDEAS

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    1. Casey, C & Bartczak, N, 1985. "Using Operating Cash Flow Data To Predict Financial Distress - Some Extensions," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 384-401.
    2. Andreas Charitou & Colin Clubb, 1999. "Earnings, Cash Flows and Security Returns Over Long Return Intervals: Analysis and UK Evidence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 26(3‐4), pages 283-312, April.
    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. Thomas Plenborg, 1999. "An examination of the information content of Danish earnings and cash flows," Accounting and Business Research, Taylor & Francis Journals, vol. 30(1), pages 43-55.
    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. Andreas Charitou & Colin Clubb, 1999. "Earnings, Cash Flows and Security Returns Over Long Return Intervals: Analysis and UK Evidence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 26(3-4), pages 283-312.
    8. Nelson, Karen K. & Barth, Mary E. & Cram, Donald, 2001. "Accruals and the Prediction of Future Cash Flows," Research Papers 1594r, Stanford University, Graduate School of Business.
    9. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    10. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    11. Finger, Ca, 1994. "The Ability Of Earnings To Predict Future Earnings And Cash Flow," Journal of Accounting Research, Wiley Blackwell, vol. 32(2), pages 210-223.
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