Comparing the Identifying Criteria for Financially Distressed Companies using Logistic Regression and Artificial Intelligence Methods

In current competitive environment, the risk of financial distress of companies has increased, in this situation, individuals and corporations and financial institutions make a lot of effort to learn about the status of Investee companies to protect their capital. The assessment and recognition of the firm's financial condition requires utilizing efficient measures with less error probability, Therefore, the purpose of this study is to compare the different criteria for identifying financially distressed companies. For this purpose, after reviewing and identifying the most important criteria and models for identifying distressed companies from non-distressed corporations, the distressed companies of Tehran Stock Exchange during the years 2006 to 2018 were separated from healthy firms and compared with the results of logistic regression and artificial intelligence methods, Article 141 of the trade law, Altman (1968), Altman (1995) and Asquith et al (1994). The results of this study showed that during the period under review and in the conditions of the Iranian companies based on Tehran Stock Exchange that Asquith et al (1994) criteria is the best way to identify distressed companies and to predict the financial position of companies and the Altman criteria (1995), Article 141 of the trade law and Altman (1968) are among the top priorities in identifying distressed enterprises.