IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-00582740.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-00582740/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    4. Hamer, Michelle M., 1983. "Failure prediction: Sensitivity of classification accuracy to alternative statistical methods and variable sets," Journal of Accounting and Public Policy, Elsevier, vol. 2(4), pages 289-307.
    5. Paul D. Allison, 1999. "Comparing Logit and Probit Coefficients Across Groups," Sociological Methods & Research, , vol. 28(2), pages 186-208, November.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antonio David Somoza Lopez & Josep Vallverdu Calafell, 2003. "Una comparacion de la seleccion de los ratios contables en los modelos contable-financieros de prediccion de la insolvencia empresarial," Working Papers in Economics 94, Universitat de Barcelona. Espai de Recerca en Economia.
    2. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    3. Laitinen, Erkki K., 2007. "Classification accuracy and correlation: LDA in failure prediction," European Journal of Operational Research, Elsevier, vol. 183(1), pages 210-225, November.
    4. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    5. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    6. Hunter, John & Isachenkova, Natalia, 2006. "Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 911-919, November.
    7. Paolo Angelis & Fulvio Gismondi & Riccardo Ottaviani, 1994. "A non-parametric statistical model for the control of Italian insurance companies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 17(1), pages 69-84, March.
    8. Teija Laitinen & Maria Kankaanpaa, 1999. "Comparative analysis of failure prediction methods: the Finnish case," European Accounting Review, Taylor & Francis Journals, vol. 8(1), pages 67-92.
    9. Marek Vochozka, 2010. "Vývoj metod komplexního hodnocení výkonnosti podniku [Development of Methods for Comprehensive Evaluation of Business Performance]," Politická ekonomie, Prague University of Economics and Business, vol. 2010(5), pages 675-688.
    10. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2019. "Limitation of Financial Health Prediction in Companies from Post-Communist Countries," JRFM, MDPI, vol. 12(1), pages 1-14, January.
    11. Goriunov Dmytro & Venzhyk Katerina, 2013. "Loan Default Prediction in Ukrainian Retail Banking," EERC Working Paper Series 13/07e, EERC Research Network, Russia and CIS.
    12. Kerstin Lopatta & Mario Albert Gloger & Reemda Jaeschke, 2017. "Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings," Accounting Perspectives, John Wiley & Sons, vol. 16(4), pages 315-343, December.
    13. Akarsh Kainth & Ranik Raaen Wahlstrøm, 2021. "Do IFRS Promote Transparency? Evidence from the Bankruptcy Prediction of Privately Held Swedish and Norwegian Companies," JRFM, MDPI, vol. 14(3), pages 1-15, March.
    14. Piesse, J. & Wood, D., 1992. "Issues in assessing MDA models of corporate failure: A research note," The British Accounting Review, Elsevier, vol. 24(1), pages 33-42.
    15. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    16. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
    17. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
    18. Poon, Winnie P. H. & Firth, Michael & Fung, Hung-Gay, 1999. "A multivariate analysis of the determinants of Moody's bank financial strength ratings," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(3), pages 267-283, August.
    19. Hu, Yu-Chiang & Ansell, Jake, 2007. "Measuring retail company performance using credit scoring techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1595-1606, December.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:halshs-00582740. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.