Bankruptcy Prediction of Companies listed Corporations in Tehran Stock Exchange by Using Decision Tree and Logistic Regression

The main goal of this study is the prediction of companies listed in Tehran Stock Exchange using decision tree and logistic regression، which are data mining methods and can help facilitate prediction. Financial ratios are independent variables and healthy and bankrupt companies are dependent variables. Statistical population of the research is information about financial statements of companies listed in Tehran Stock Exchange during 1999 – 2010. No sampling was used in this study; we have two groups of healthy and bankrupt companies. Bankrupt companies group was selected based on article 141 of Commercial law and the healthy group was selected based on profitability criteria. Results suggest that both decision tree and logistic regression methods predict bankruptcy with different accuracy. Area under ROC curve in logistic regression model is more than in decision tree model.