Predicting Financial Distress with using combined model of Accounting and Market Data with Logistic Regression Approach

Today’s, bankruptcy and financial distress is one of the important factors for decision making process of market participants, so the need to predicting them with using a suitable model is the manifest of financial market analysts and investors because it have a significant effect on shareholder's wealth in the market. With such importance, the aim of this paper is to introduce a suitable model for predicting financial distress at Tehran stock exchange listed companies.For achieving this goal, thirteen variables including eight accounting and five market variables were used to determine financial distress with applying Logistic regression method from 2008 to 2016. For testing research hypothesis, the dates of 928 firm-year (522 distressed and 406 sound firm -year) was gathered listed in Tehran Stock Exchange (1040 firm-year).The results showed that a combination of accounting and market dates can predict distress in firms and can be a ground for further studies on financial distress.