Empirical Analysis of Factors Affecting Financial Distress at Companies: An Emphasis on Data Mining Models

This study aimed to analyze the effects of macroeconomic factors (e.g., inflation, economic growth, currency exchange rate, and market competitiveness), managerial characteristics (e.g., ability, optimism, entrenchment, and myopia), and corporate governance (e.g., institutional shareholders, ownership concentration, number of shareholders, and managerial independence) on the financial distress risks of companies listed in the Tehran Stock Exchange. For this purpose, data mining models (e.g., Artificial neural networks and decision trees) were used along with the regression method to analyze a sample of ۱۴۰ TSE-listed companies within the ۲۰۰۷–۲۰۲۰ period. The research results indicated that macroeconomic factors (i.e., external factors) and managerial characteristics (i.e., internal factors) were identified as the first and second most effective factors in the financial distress risk of companies, respectively. However, corporate governance variables were identified as the least effective factors. According to the results of ranking the effects of research variables on financial distress risk, the most effective variables were identified as market competitiveness, managerial myopia, and inflation.

Keywords:

Data Mining , Empirical Analysis , Financial distress