Predicting Financial Distress with a Combined ModelCase Study: Companies Listed on the Tehran Stock Exchange

This study was aimed to predict financial distress using financial, economic and stock market variables in the form of binary logistic regression models, Merton and hybrid models. For this purpose, the information of 168 distressed companies selected based on specific criteria of distress and 168 healthy companies listed on the Tehran Stock Exchange between2006-2019 and two years ago, one year ago and distress year has been used. In this study, from 17 financial ratios, 4 economic variables and 4 stock market variables have been used. The innovation of the present study is the development of a hybrid financial distress prediction model that for the first time combines the financial, economic and stock market variables of the accounting model with the default variable of the structural model.The results showed that the hybrid model has better explanatory power than Merton and binary logistic regression model and although the existence of the variable probability of Merton model improves the explanatory power of the hybrid model, but the explanatory power of binary logistic regression model is better than the Merton model