Predict of Financial Distress by Logistic Regression, DEA-R and CAMELS Indicators

It is very important to choose an appropriate and efficient monitoring system to evaluate the performance of a bank’s financial distress, including the most important monitoring systems that have been proposed to evaluate the performance of a bank’s financial distress; The use of CAMELS monitoring system, which includes six indicators of capital adequacy, asset quality, management soundness, earning quality, liquidity, market risk sensitivity, so the purpose of this study is to evaluate the financial distress of banks based on CAMELS indicators. In this regard, 12 financial variables based on CAMELS indices have been used, which have been implemented on 17 banks listed on the Tehran Stock Exchange. The sample selected in the model fit includes two groups of healthy and financially distressed, which are separated based on the CAMELS index. The accuracy of both models has been investigated. The results indicate that the overall accuracy of the logistic regression model is higher than the Data Envelopment Analysis model in assessing financial distress. Also, the results of this study showed that CAMELS financial ratios can be a good assessor for banks’ financial distress.