Predicting Companies Financial Distress by Using Ant Colony Algorithm

Document Type : Research Paper

Authors

1 MSc. in Business Management, Faculty of Management, University of Tehran, Tehran, Iran

2 Assistant Prof., Faculty of Management, University of Tehran, Tehran, Iran

Abstract

Financial distress prediction of companies is one of the important issues that can contribute to the success and survival of companies; because providing warning and timely signals can make companies aware of financial distress and bankruptcy and, therefore, by a correct management, they can prevent waste of resources and the damage caused by bankruptcy.
Ant Colony Algorithm (ACA) is an intelligent method that was recently used to solve problems including classifications and predictions which had desired results. This study aims to investigate the financial distress prediction of companies using ant colony algorithm. The statistical population includes companies listed in Tehran Stock Exchange and the sample consists of 174 healthy and distressed companies. Predictor variables were selected from previous studies according to the ratios that were proposed as key variables in prediction model.
The results of the study indicate that the ACA approach in predicting financial distress of companies had significantly better performance than multiple discriminant analysis (MDA).

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References

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Financial Research Journal
Volume 18, Issue 2
May 2016
Pages 347-368

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