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

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  • Wikil Kwak
  • Yong Shi
  • Gang Kou

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  • 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
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    References listed on IDEAS

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    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. Joon-Kyung Kim & Chung H. Lee, 2002. "Insolvency in the Corporate Sector and Financial Crisis in Korea," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 7(2), pages 267-281.
    3. Lili Sun, 2007. "A re-evaluation of auditors’ opinions versus statistical models in bankruptcy prediction," Review of Quantitative Finance and Accounting, Springer, vol. 28(1), pages 55-78, January.
    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. 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.
    6. 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.
    7. 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.
    8. Yong Shi, 2001. "Multiple Criteria and Multiple Constraint Levels Linear Programming:Concepts, Techniques and Applications," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 4000, February.
    9. Hsin-Hung Chen, 2008. "The Timescale Effects of Corporate Governance Measure on Predicting Financial Distress," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 35-46.
    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. 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.
    12. Yong Shi & Yi Peng & Gang Kou & Zhengxin Chen, 2005. "Classifying Credit Card Accounts For Business Intelligence And Decision Making: A Multiple-Criteria Quadratic Programming Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 581-599.
    13. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    14. 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.
    15. 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.
    16. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    17. Mossman, Charles E, et al, 1998. "An Empirical Comparison of Bankruptcy Models," The Financial Review, Eastern Finance Association, vol. 33(2), pages 35-53, May.
    18. Yong Shi & Yi Peng & Weixuan Xu & Xiaowo Tang, 2002. "Data Mining Via Multiple Criteria Linear Programming: Applications In Credit Card Portfolio Management," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 131-151.
    19. Gregory Kane & Frederick Richardson & Uma Velury, 2006. "The Relevance of Stock and Flow-Based Reporting Information In Assessing the Likelihood of Emergence from Corporate Financial Distress," Review of Quantitative Finance and Accounting, Springer, vol. 26(1), pages 5-22, February.
    20. Gang Kou & Yi Peng & Yong Shi & Morgan Wise & Weixuan Xu, 2005. "Discovering Credit Cardholders’ Behavior by Multiple Criteria Linear Programming," Annals of Operations Research, Springer, vol. 135(1), pages 261-274, March.
    21. Eliezer Fich & Steve Slezak, 2008. "Can corporate governance save distressed firms from bankruptcy? An empirical analysis," Review of Quantitative Finance and Accounting, Springer, vol. 30(2), pages 225-251, February.
    22. 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.
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    Cited by:

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    2. Cao Dinh Kien & Nguyen Huu That, 2022. "Innovation Capabilities in the Banking Sector Post-COVID-19 Period: The Moderating Role of Corporate Governance in an Emerging Country," IJFS, MDPI, vol. 10(2), pages 1-14, June.
    3. Vicente García & Ana I. Marqués & J. Salvador Sánchez & Humberto J. Ochoa-Domínguez, 2019. "Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1019-1031, March.
    4. 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.
    5. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    6. Evangelos C. Charalambakis & Ian Garrett, 2019. "On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 467-491, February.
    7. 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.
    8. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
    9. Qazi Awais Amin & Tom Williamson, 2021. "Firms cash management, adjustment cost and its impact on firms’ speed of adjustment: a cross country analysis," Review of Quantitative Finance and Accounting, Springer, vol. 56(1), pages 53-89, January.
    10. 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.

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    More about this item

    Keywords

    Korean; Bankruptcy; Data mining; Multiple criteria linear programming; C61; G33;
    All these keywords.

    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

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