Analysis financial distress agriculture and food materials industry with an emphasis on the role of Macroeconomic and accounting variables

Analysis financial distress is an important phenomenon for investors, creditors and other users of financial information. Determining the probability of a company’s distress before occurrence of distress and bankruptcy is considered a very interesting and attractive subject and can be useful for both managers, and investors and creditors. In this study, using the information of 6 financial years during the period 2011 to 2016 in industry agriculture and food materials industry, the factors affecting financial distress and predicting it through methods based on machine learning (NBC and AdaBoost) have been studied. The results of the study indicate direct impack and inflationon, indirect impact of the ratio of non-executive directors, Stock returns, the ratio of operating cash flow financial distress. The results also show that AdaBoost method, using financial and economic data, has higher capability in predicting financial distress compared to NBC method.