IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v242y2015i1p286-303.html
   My bibliography  Save this article

Bankruptcy prediction using terminal failure processes

Author

Listed:
  • du Jardin, Philippe

Abstract

Traditional bankruptcy prediction models, designed using classification or regression techniques, achieve short-term performances (1 year) that are fairly good, but that often worsen when the prediction horizon exceeds 1 year. We show how to improve the performance of such models beyond 1 year using models that take into account the evolution of firm’s financial health over a short period of time. For this purpose, we design models that fit the underlying failure process of different groups of firms. Our results demonstrate that such models lead to better prediction accuracy at a 3-year horizon than that achieved with common models.

Suggested Citation

  • du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
  • Handle: RePEc:eee:ejores:v:242:y:2015:i:1:p:286-303
    DOI: 10.1016/j.ejor.2014.09.059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171400798X
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment," European Journal of Operational Research, Elsevier, vol. 199(2), pages 561-575, December.
    2. 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.
    3. Nico Dewaelheyns & Cynthia Van Hulle, 2006. "Corporate Failure Prediction Modeling: Distorted by Business Groups' Internal Capital Markets?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5-6), pages 909-931.
    4. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    5. repec:bla:joares:v:10:y:1972:i:1:p:167-179 is not listed on IDEAS
    6. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    7. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    8. Anthony Brabazon & Peter Keenan, 2004. "A hybrid genetic model for the prediction of corporate failure," Computational Management Science, Springer, vol. 1(3), pages 293-310, October.
    9. 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.
    10. 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.
    11. Lensberg, Terje & Eilifsen, Aasmund & McKee, Thomas E., 2006. "Bankruptcy theory development and classification via genetic programming," European Journal of Operational Research, Elsevier, vol. 169(2), pages 677-697, March.
    12. 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.
    13. Cielen, Anja & Peeters, Ludo & Vanhoof, Koen, 2004. "Bankruptcy prediction using a data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 526-532, April.
    14. Laitinen, Ek, 1993. "Financial predictors for different phases of the failure process," Omega, Elsevier, vol. 21(2), pages 215-228, March.
    15. Laitinen, Erkki K. & Laitinen, Teija, 2000. "Bankruptcy prediction: Application of the Taylor's expansion in logistic regression," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 327-349.
    16. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    17. repec:bla:joares:v:22:y:1984:i::p:59-82 is not listed on IDEAS
    18. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    19. Erkki K. Laitinen & Teija Laitinen, 1998. "Cash Management Behavior and Failure Prediction," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(7&8), pages 893-919.
    20. repec:bla:joares:v:23:y:1985:i:1:p:146-160 is not listed on IDEAS
    21. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    22. Altman, Edward I, 1984. " A Further Empirical Investigation of the Bankruptcy Cost Question," Journal of Finance, American Finance Association, vol. 39(4), pages 1067-1089, September.
    23. du Jardin, Philippe & Séverin, Eric, 2012. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.
    24. Rada Dakovic & Claudia Czado & Daniel Berg, 2010. "Bankruptcy prediction in Norway: a comparison study," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1739-1746.
    25. Pinches, George E & Mingo, Kent A & Caruthers, J Kent, 1973. "The Stability of Financial Patterns in Industrial Organizations," Journal of Finance, American Finance Association, vol. 28(2), pages 389-396, May.
    26. 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.
    27. Zopounidis, Constantin & Doumpos, Michael, 2002. "Multi-group discrimination using multi-criteria analysis: Illustrations from the field of finance," European Journal of Operational Research, Elsevier, vol. 139(2), pages 371-389, June.
    28. P. Du Jardin & E. Séverin, 2011. "Predicting Corporate Bankruptcy Using Self-Organising map: An empirical study to Improve the Forecasting horizon of financial failure model," Post-Print hal-00801878, HAL.
    29. 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.
    30. Chris Charalambous & Andreas Charitou & Froso Kaourou, 2000. "Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction," Annals of Operations Research, Springer, vol. 99(1), pages 403-425, December.
    31. 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.
    32. P. Du Jardin & E. Séverin, 2012. "Forecasting financial failure using a Kohonen map: a comparative study to improve bankruptcy model over time," Post-Print hal-00801853, HAL.
    33. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
    34. 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.
    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. repec:eee:joreco:v:36:y:2017:i:c:p:197-202 is not listed on IDEAS
    2. repec:gam:jijfss:v:7:y:2019:i:2:p:20-:d:220886 is not listed on IDEAS
    3. repec:gam:jrisks:v:7:y:2019:i:3:p:77-:d:246370 is not listed on IDEAS
    4. repec:eee:ejores:v:272:y:2019:i:1:p:162-175 is not listed on IDEAS
    5. repec:eee:jbrese:v:98:y:2019:i:c:p:380-390 is not listed on IDEAS
    6. repec:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-018-2814-2 is not listed on IDEAS
    7. repec:pal:jorsoc:v:68:y:2017:i:9:d:10.1057_s41274-016-0166-3 is not listed on IDEAS
    8. repec:kap:compec:v:54:y:2019:i:1:d:10.1007_s10614-017-9698-0 is not listed on IDEAS
    9. repec:spr:empeco:v:54:y:2018:i:3:d:10.1007_s00181-017-1246-1 is not listed on IDEAS
    10. repec:kap:compec:v:54:y:2019:i:1:d:10.1007_s10614-017-9681-9 is not listed on IDEAS
    11. Spyridou, Anastasia, 2019. "Evaluating Factors of Small and Medium Hospitality Enterprises Business Failure: a conceptual approach," MPRA Paper 93997, University Library of Munich, Germany.

    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:eee:ejores:v:242:y:2015:i:1:p:286-303. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eor .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.