IDEAS home Printed from https://ideas.repec.org/a/kap/rqfnac/v38y2012i4p441-453.html
   My bibliography  Save this article

Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach

Author

Listed:
  • Wikil Kwak

    ()

  • Yong Shi
  • Gang Kou

Abstract

No abstract is available for this item.

Suggested Citation

  • Wikil Kwak & Yong Shi & Gang Kou, 2012. "Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach," Review of Quantitative Finance and Accounting, Springer, vol. 38(4), pages 441-453, May.
  • Handle: RePEc:kap:rqfnac:v:38:y:2012:i:4:p:441-453 DOI: 10.1007/s11156-011-0238-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11156-011-0238-z
    Download Restriction: Access to full text is restricted to subscribers.

    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. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    2. 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.
    3. Nikola A. Tarashev, 2008. "An Empirical Evaluation of Structural Credit-Risk Models," International Journal of Central Banking, International Journal of Central Banking, vol. 4(1), pages 1-53, March.
    4. Takahashi, Kichinosuke & Kurokawa, Yukiharu & Watase, Kazunori, 1984. "Corporate bankruptcy prediction in Japan," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 229-247, June.
    5. 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.
    6. Li-Chiu Chi & Tseng-Chung Tang, 2006. "Bankruptcy Prediction: Application of Logit Analysis in Export Credit Risks," Australian Journal of Management, Australian School of Business, vol. 31(1), pages 17-27, June.
    7. Bongini, Paola & Ferri, Giovanni & Hahm, Hongjoo, 2000. "Corporate Bankruptcy in Korea: Only the Strong Survive?," The Financial Review, Eastern Finance Association, vol. 35(4), pages 31-50, November.
    8. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    9. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    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. Özgür Arslan-Ayaydin & Chris Florackis & Aydin Ozkan, 2014. "Financial flexibility, corporate investment and performance: evidence from financial crises," Review of Quantitative Finance and Accounting, Springer, vol. 42(2), pages 211-250, February.
    2. Evangelos C. Charalambakis & Ian Garrett, 2016. "On the prediction of financial distress in developed and emerging markets: Does the choice of accounting and market information matter? A comparison of UK and Indian Firms," Review of Quantitative Finance and Accounting, Springer, vol. 47(1), pages 1-28, July.
    3. Jairaj Gupta & Andros Gregoriou & Jerome Healy, 2015. "Forecasting bankruptcy for SMEs using hazard function: To what extent does size matter?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 845-869, November.

    More about this item

    Keywords

    Korean; Bankruptcy; Data mining; Multiple criteria linear programming; C61; G33;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:kap:rqfnac:v:38:y:2012:i:4:p:441-453. 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: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://springer.com .

    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.