IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v169y2006i2p677-697.html
   My bibliography  Save this article

Bankruptcy theory development and classification via genetic programming

Author

Listed:
  • Lensberg, Terje
  • Eilifsen, Aasmund
  • McKee, Thomas E.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:169:y:2006:i:2:p:677-697
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(04)00451-5
    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. McKee, Thomas E. & Lensberg, Terje, 2002. "Genetic programming and rough sets: A hybrid approach to bankruptcy classification," European Journal of Operational Research, Elsevier, vol. 138(2), pages 436-451, April.
    2. 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.
    3. Sweeney, Amy Patricia, 1994. "Debt-covenant violations and managers' accounting responses," Journal of Accounting and Economics, Elsevier, vol. 17(3), pages 281-308, May.
    4. 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.
    5. 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.
    6. 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.
    7. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    8. 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.
    9. Zmijewski, Mark E. & Hagerman, Robert L., 1981. "An income strategy approach to the positive theory of accounting standard setting/choice," Journal of Accounting and Economics, Elsevier, vol. 3(2), pages 129-149, August.
    10. Altman, Edward I, 1969. "Corporate Bankruptcy Potential, Stockholder Returns and Share Valuation," Journal of Finance, American Finance Association, vol. 24(5), pages 887-900, December.
    11. Frederick M. Richardson & Gregory D. Kane & Patricia Lobingier, 1998. "The Impact of Recession on the Prediction of Corporate Failure," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(1&2), pages 167-186.
    12. 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.
    13. Beaver, Wh, 1968. "Market Prices, Financial Ratios, And Prediction Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 179-192.
    14. Frederick M. Richardson & Gregory D. Kane & Patricia Lobingier, 1998. "The Impact of Recession on the Prediction of Corporate Failure," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(1‐2), pages 167-186, January.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
    4. 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.
    5. 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.
    6. Philippe Jardin & David Veganzones & Eric Séverin, 2019. "Forecasting Corporate Bankruptcy Using Accrual-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 7-43, June.
    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. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    9. Aaro Hazak & Kadri Männasoo, 2007. "Indicators of corporate default : an EU based empirical study," Bank of Estonia Working Papers 2007-10, Bank of Estonia, revised 04 Sep 2007.
    10. 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.
    11. du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
    12. Soo Young Kim, 2018. "Predicting hospitality financial distress with ensemble models: the case of US hotels, restaurants, and amusement and recreation," Service Business, Springer;Pan-Pacific Business Association, vol. 12(3), pages 483-503, September.
    13. 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.
    14. Qunfeng LIAO & Seyed MEHDIAN, 2016. "Measuring Financial Distress And Predicting Corporate Bankruptcy: An Index Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 17, pages 33-51, June.
    15. Paul P. M. Pompe & Jan Bilderbeek, 2005. "Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(2), pages 95-112, June.
    16. 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.
    17. 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.
    18. Sun, Lili & Shenoy, Prakash P., 2007. "Using Bayesian networks for bankruptcy prediction: Some methodological issues," European Journal of Operational Research, Elsevier, vol. 180(2), pages 738-753, July.
    19. Josep M. Argilés, 1998. "Accounting information and the prediction of farm viability," Economics Working Papers 277, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Bhimani, Alnoor & Gulamhussen, Mohamed Azzim & Lopes, Samuel Da-Rocha, 2010. "Accounting and non-accounting determinants of default: An analysis of privately-held firms," Journal of Accounting and Public Policy, Elsevier, vol. 29(6), pages 517-532, November.

    More about this item

    Statistics

    Access and download statistics

    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:169:y:2006:i:2:p:677-697. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.