The Assessment of Financial Distress in Tehran Stock Exchange: A Comparative Study Between Data Envelopment Analysis (DEA) and Logistic Regression (LR)

Financial distress evaluation is important because firm failure imposes significant direct and indirect costs on a firm’s stakeholders. Hence, using financial ratios has been considered by bank loan officers, creditors, stockholders, financial analysts, and the general public in order to provide them with timely and accurate assessment. Timely evaluation can help decision makers to find the optimal way and predict bankruptcy. There are different models for financial distress evaluation, which are mainly applied in decision making by financial market players. It has been attempted to improve the accuracy of these models by more developed techniques. The main goal of this research is to examine the capability of the additive model of Data Envelopment Analysis (DEA) model in assessing corporate financial distress by comparing it with logistic regression (LR). The results showed that in within-sample evaluation, LR outperforms DEA (Additive model) in correctly identifying the default firms significantly.