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Scoring Et Anticipation De Defaillance Des Entreprises : Une Approche Par La Regression Logistique

Author

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  • Patrick Boisselier

    (CRIFP - Centre de Recherche en Ingénierie Financière et Finances Publiques - UNS - Université Nice Sophia Antipolis (1965 - 2019))

  • Dominique Dufour

    (CRIFP - Centre de Recherche en Ingénierie Financière et Finances Publiques - UNS - Université Nice Sophia Antipolis (1965 - 2019))

Abstract

L'anticipation de la défaillance des entreprises a été étudiée en détail et de manière récurrente dans la littérature comptable et financière. Cette analyse peut s'appuyer sur la mise en oeuvre de différents modèles statistiques. L'analyse discriminante popularisée par les travaux de la Banque de France en est une illustration. Dans ce travail, l'application de la technique de la régression logistique à deux échantillons d'entreprises -saines et faillies en 2002- nous permet d'obtenir des résultats significatifs et de proposer un modèle de prévision

Suggested Citation

  • Patrick Boisselier & Dominique Dufour, 2003. "Scoring Et Anticipation De Defaillance Des Entreprises : Une Approche Par La Regression Logistique," Post-Print halshs-00582740, HAL.
    • Handle: RePEc:hal:journl:halshs-00582740
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00582740
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    References listed on IDEAS

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    Cited by:

    1. A?da Kammoun & Imen Triki, 2016. "Credit Scoring Models for a Tunisian Microfinance Institution: Comparison between Artificial Neural Network and Logistic Regression," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 61-78, February.
    2. Bruno Drouot, 2012. "Les facteurs explicatifs de la dépendance économique des patrons pêcheurs à une ressource naturelle : le cas de la pêcherie de bar commun en France," Post-Print hal-01870830, HAL.

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