Predicting financial distress risk of firms listed in Tehran Stock Exchange using factor analysis, decision tree and logistic regression models

This research predicts financial distress of companies listed on Tehran Stock Exchange using Factor Analysis, Decision Tree, and Logistic Regression models. For this purpose, 33 financial ratios have been investigated in the 5-year time horizon. In order to reduce the dimensions of the data and to find the internal relationship the variables, factor analysis model has been used. Then, the variables according to their relationships with financial distress are classified in eight factors. In the following, the results of the decision tree and the logistic regression models are compared with each other. The results show that both models have the ability to predict financial distress, but the decision tress model has a higher predictive power than the logistic regression model.