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An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction

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  • Ouenniche, Jamal
  • Pérez-Gladish, Blanca
  • Bouslah, Kais

Abstract

Since the publication of the seminal paper by Hwang and Yoon (1981) proposing Technique for Order Performance by the Similarity to Ideal Solution (TOPSIS), a substantial number of papers used this technique in a variety of applications requiring a ranking of alternatives. Very few papers use TOPSIS as a classifier (e.g. Wu and Olson, 2006; Abd-El Fattah et al., 2013) and report a good performance as in-sample classifiers. However, in practice, its use in predicting discrete variables such as risk class belonging is limited by the lack of an out-of-sample evaluation framework. In this paper, we fill this gap by proposing an integrated in-sample and out-of-sample framework for TOPSIS classifiers and test its performance on a UK dataset of bankrupt and non-bankrupt firms listed on the London Stock Exchange (LSE) during 2010–2014. Empirical results show an outstanding predictive performance both in-sample and out-of-sample and thus opens a new avenue for research and applications in risk modelling and analysis using TOPSIS as a non-parametric classifier and makes it a real contender in industry applications in banking and investment. In addition, the proposed framework is robust to a variety of implementation decisions.

Suggested Citation

  • Ouenniche, Jamal & Pérez-Gladish, Blanca & Bouslah, Kais, 2018. "An out-of-sample framework for TOPSIS-based classifiers with application in bankruptcy prediction," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 111-116.
  • Handle: RePEc:eee:tefoso:v:131:y:2018:i:c:p:111-116
    DOI: 10.1016/j.techfore.2017.05.034
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    References listed on IDEAS

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    1. Huang, Jen-Hung & Peng, Kua-Hsin, 2012. "Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries," Tourism Management, Elsevier, vol. 33(2), pages 456-465.
    2. Khademi-Zare, Hassan & Zarei, Mahnaz & Sadeghieh, Ahmad & Saleh Owlia, Mohammad, 2010. "Ranking the strategic actions of Iran mobile cellular telecommunication using two models of fuzzy QFD," Telecommunications Policy, Elsevier, vol. 34(11), pages 747-759, December.
    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. Wu, Cheng-Shiung & Lin, Chin-Tsai & Lee, Chuan, 2010. "Optimal marketing strategy: A decision-making with ANP and TOPSIS," International Journal of Production Economics, Elsevier, vol. 127(1), pages 190-196, September.
    5. Taffler, Richard J., 1984. "Empirical models for the monitoring of UK corporations," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 199-227, June.
    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. Desheng Wu & David L. Olson, 2006. "A TOPSIS Data Mining Demonstration and Application to Credit Scoring," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 2(3), pages 16-26, July.
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