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La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux

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  • Catherine Refait

Abstract

[fre] La prédiction de la faillite des entreprises fait l ’ objet de nombreux travaux empiriques , depuis une trentaine d ’ années . Elle se fonde sur l ’ analyse économique et financière d ’ entreprises défaillantes et d ’ entreprises non défaillantes , afin de déterminer les variables , principalement comptables , qui distinguent au mieux les deux catégories de firmes . Nous proposons un état des lieux afin de rendre compte de l ’ efficacité relative des différentes méthodes de classification utilisées . Dans ce but , nous exposons la démarche commune tout en mettant en évidence les différentes modalités d ’ application empirique . Nous présentons le principe des techniques disponibles et une comparaison de leur performance , en mettant l ’ accent , de manière non exhaustive , à la fois sur les études fondatrices et sur les études les plus récentes . Mots-clés : prévision , faillite d ’ entreprise , analyse financière [eng] A Review of Business Failure Prediction Based on Financial Analysis of the Firm . . Many studies of business failure prediction have been carried out in the last thirty years or so . Prediction is based on an economic and financial analysis of failing and non-failing firms with the aim of determining the variables , mainly of an accounting nature , that best distinguish the two categories . The purpose of this review is to assess the relative effectiveness of the different classification methods employed . To that end we identify the common elements while highlighting the different ways in which they are applied empirically . We describe the principle of the available techniques and compare their performance , focusing non-exhaustively on both the founding studies and on more recent research . Key-words : prediction , business failure , financial analysis

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  • Catherine Refait, 2004. "La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux," Économie et Prévision, Programme National Persée, vol. 162(1), pages 129-147.
  • Handle: RePEc:prs:ecoprv:ecop_0249-4744_2004_num_162_1_6937
    DOI: 10.3406/ecop.2004.6937
    Note: DOI:10.3406/ecop.2004.6937
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    1. Barney, Douglas K. & Finley Graves, O. & Johnson, John D., 1999. "The farmers home administration and farm debt failure prediction," Journal of Accounting and Public Policy, Elsevier, vol. 18(2), pages 99-139.
    2. Richard S. BARR & Lawrence M. SEIFORD & Thomas F. SIEMS, 1994. "Forecasting Bank Failure : A Non-Parametric Frontier Estimation Approach," Discussion Papers (REL - Recherches Economiques de Louvain) 1994041, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    3. Varetto, Franco, 1998. "Genetic algorithms applications in the analysis of insolvency risk," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1421-1439, October.
    4. Altman, Edward I & Loris, Bettina, 1976. "A Financial Early Warning System for Over-the-Counter Broker-Dealers," Journal of Finance, American Finance Association, vol. 31(4), pages 1201-1217, September.
    5. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    6. Burgstahler, David & Jiambalvo, James & Noreen, Eric, 1989. "Changes in the probability of bankruptcy and equity value," Journal of Accounting and Economics, Elsevier, vol. 11(2-3), pages 207-224, July.
    7. Clark, Truman A & Weinstein, Mark I, 1983. "The Behavior of the Common Stock of Bankrupt Firms," Journal of Finance, American Finance Association, vol. 38(2), pages 489-504, May.
    8. Altman, Edward I., 1977. "Predicting performance in the savings and loan association industry," Journal of Monetary Economics, Elsevier, vol. 3(4), pages 443-466, October.
    9. Altman, Edward I. & Brenner, Menachem, 1981. "Information Effects and Stock Market Response to Signs of Firm Deterioration," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(1), pages 35-51, March.
    10. Mensah, Ym, 1984. "An Examination Of The Stationarity Of Multivariate Bankruptcy Prediction Models - A Methodological Study," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 380-395.
    11. Henebry, Kathleen L., 1996. "Do cash flow variables improve the predictive accuracy of a Cox proportional hazards model for bank failure?," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(3), pages 395-409.
    12. Aharony, Joseph & Jones, Charles P & Swary, Itzhak, 1980. "An Analysis of Risk and Return Characteristics of Corporate Bankruptcy Using Capital Market Data," Journal of Finance, American Finance Association, vol. 35(4), pages 1001-1016, September.
    13. Izan, H. Y., 1984. "Corporate distress in Australia," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 303-320, June.
    14. Foglia, A. & Laviola, S. & Marullo Reedtz, P., 1998. "Multiple banking relationships and the fragility of corporate borrowers," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1441-1456, October.
    15. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    16. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    17. Hervé Alexandre, 2000. "L'individu face au marché : investisseurs, spéculateurs et crises boursières," Post-Print hal-01622769, HAL.
    18. Li, Kai, 1999. "Bayesian analysis of duration models: an application to Chapter 11 bankruptcy," Economics Letters, Elsevier, vol. 63(3), pages 305-312, June.
    19. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    20. 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.
    21. repec:dau:papers:123456789/6078 is not listed on IDEAS
    22. Platt, Harlan D. & Platt, Marjorie B., 1991. "A note on the use of industry-relative ratios in bankruptcy prediction," Journal of Banking & Finance, Elsevier, vol. 15(6), pages 1183-1194, December.
    23. Grice, John Stephen & Dugan, Michael T, 2001. "The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher," Review of Quantitative Finance and Accounting, Springer, vol. 17(2), pages 151-166, September.
    24. Houghton, Ka, 1984. "Accounting Data And The Prediction Of Business Failure - The Setting Of Priors And The Age Of Data," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 361-368.
    25. 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.
    26. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    27. Vidar Gudmundsson, Sveinn, 1999. "Airline failure and distress prediction: a comparison of quantitative and qualitative models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 35(3), pages 155-182, September.
    28. Bardos, Mireille, 1998. "Detecting the risk of company failure at the Banque de France," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1405-1419, October.
    29. Honjo, Yuji, 2000. "Business failure of new firms: an empirical analysis using a multiplicative hazards model," International Journal of Industrial Organization, Elsevier, vol. 18(4), pages 557-574, May.
    30. Frydman, Halina & Altman, Edward I & Kao, Duen-Li, 1985. "Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress," Journal of Finance, American Finance Association, vol. 40(1), pages 269-291, March.
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    2. Sami BEN JABEUR, 2014. "Prévision de la détresse financière des entreprises françaises: Approche par la régression logistique PLS," Working Papers 2014-321, Department of Research, Ipag Business School.
    3. Sami Ben Jabeur & Youssef Fahmi, 2014. "Les modèles de prévision de la défaillance des entreprises françaises : une approche comparative," Working Papers 2014-317, Department of Research, Ipag Business School.
    4. 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.
    5. Sami BEN JABEUR & Youssef FAHMI, 2014. "Default Prediction for Small-Medium Enterprises in France: A comparative approach," Working Papers 2014-319, Department of Research, Ipag Business School.
    6. Sami BEN JABEUR & Youssef FAHMI, 2014. "Predicting Business Failure Using Data-Mining Methods," Working Papers 2014-308, Department of Research, Ipag Business School.

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