IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-00587769.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-00587769/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    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.

    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. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    2. 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.
    3. 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.
    4. 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.
    5. John W. Pacey & Toan M. Pham, 1990. "The Predictiveness of Bankruptcy Models: Methodological Problems and Evidence," Australian Journal of Management, Australian School of Business, vol. 15(2), pages 315-337, December.
    6. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    7. 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.
    8. 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.
    9. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    10. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 15(1), pages 133-150, June.
    11. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    12. Ali DERAN & Omer ISKENDEROGLU & Incilay ERDURU, 2014. "Regional Differences and Financial Ratios: A Comparative Approach on Companies of ISE City Indexes," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 946-955.
    13. Sanjay Sehgal & Ritesh Kumar Mishra & Ajay Jaisawal, 2021. "A search for macroeconomic determinants of corporate financial distress," Indian Economic Review, Springer, vol. 56(2), pages 435-461, December.
    14. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    15. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    16. Onofrei, Mihaela & Lupu, Dan, 2014. "The modelling of forecasting the bankruptcy in Romania," MPRA Paper 95511, University Library of Munich, Germany.
    17. Paweł Zając & Piotr Gurgul, 2012. "Forecasting of migration matrices in business demography," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(2), pages 387-404, June.
    18. 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.
    19. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    20. Michal Pavlicko & Marek Durica & Jaroslav Mazanec, 2021. "Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries," Mathematics, MDPI, vol. 9(16), pages 1-26, August.

    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-00587769. 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.