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Integrating Neural Network and Colonial Competitive Algorithm: A New Approach for Predicting Bankruptcy in Tehran Security Exchange

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Listed:
  • Sajad Abdipour
  • Ahmad Nasseri
  • Mojtaba Akbarpour
  • Hossein Parsian
  • Shahrzad Zamani

Abstract

Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by integrated Multi Layered Perceptron with Imperialist Competitive Algorithm (MLP-ICA) and Kohonen self organizing map. Research sample consist of 70 bankrupts and non-bankrupt company in 2001-2009 and in listed firms of Tehran Stock Exchange. Results indicate that MLP-ICA model outperform Kohonen self organizing map.

Suggested Citation

  • Sajad Abdipour & Ahmad Nasseri & Mojtaba Akbarpour & Hossein Parsian & Shahrzad Zamani, 2013. "Integrating Neural Network and Colonial Competitive Algorithm: A New Approach for Predicting Bankruptcy in Tehran Security Exchange," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 3(11), pages 1528-1539.
    • Handle: RePEc:asi:aeafrj:v:3:y:2013:i:11:p:1528-1539:id:1105
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    Cited by:

    1. Saba Moradi & Farimah Mokhatab Rafiei, 2019. "A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-27, December.
    2. Gintare Giriūniene & Lukas Giriūnas & Mangirdas Morkunas & Laura Brucaite, 2019. "A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania," Economies, MDPI, vol. 7(3), pages 1-20, August.

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