Going Concern Prediction of Iranian Companies by Using Fuzzy C-Means

Mahdi Moradi, Mahdi Salehi, Hadi Sadoghi Yazdi, Mohammad Ebrahim Gorgani

Ferdowsi University of Mashhad.
National Iranian Oil Company.

DOI: 10.4236/ojacct.2012.12005                

Abstract

Decision-making problems in the area of financial status evaluation have been considered very important. Making incorrect decisions in firms is very likely to cause financial crises and distress. Predicting going concern of factories and manufacturing companies is the desire of managers, investors, auditors, financial analysts, governmental officials, employees. This research introduces a new approach for modeling of company’s behavior based on Fuzzy Clustering Means (FCM). Fuzzy clustering is one of well-known unsupervised clustering techniques, which allows one piece of data belongs to two or more clusters. The data used in this research was obtained from Iran Stock Market and Accounting Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set. Our experimental results showed that FCM approach obtains good prediction accuracy in developing a financial distress prediction model. Also, in effective features determination test the results show that features based on cash flows play more important role in clustering two classes.

Keywords

Going Concern Prediction; Fuzzy C-Means

Conflicts of Interest

The authors declare no conflicts of interest.

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