An Adaptive Fuzzy Neural Network Model for Bankruptcy Prediction of Listed Companies on the Tehran Stock Exchange


1 Department of Industrial Engineering, Ayatollah Amoli Branch, Islamic Azad University,Amol, Iran

2 Department of Management, Firuzkuh Branch, Islamic Azad University, Firuzkuh, Iran

3 Department of Mathematics, Qaemshahr Branch, Islamic Azad University,Qaemshahr, Iran


Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks.  The present study proposes fuzzy neural networks to predict bankruptcy of the listed companies in the Tehran stock exchange. Four input variables including growth, profitability, productivity and asset quality were used for prediction purpose. Moreover, the Altman's Z'score is used as the output variable. The results reveal that the proposed fuzzy neural network model has a high performance for the bankruptcy prediction of the companies.


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