Decisions in new businesses
seyed hesam vaghfi
Abstract
Financial distress analysis is an essential phenomenon for financiers, creditors and those who use financial data. Predicting the possibility of a company’s distress is an interesting issue and is beneficial for managers, investors and creditors. This study localizes a method to identify the distressed ...
Read More
Financial distress analysis is an essential phenomenon for financiers, creditors and those who use financial data. Predicting the possibility of a company’s distress is an interesting issue and is beneficial for managers, investors and creditors. This study localizes a method to identify the distressed companies in three levels, using the data of 1488 company from 1390 to 1395 and finally the financial distress for the next year and two years later is predicted by means of macroeconomic and accounting variable in the capital market of Iran by means of Matlab 2017, using the artificial intelligence algorithm of Gaussian kernel backup vector machine and Chide rule-oriented algorithm. One of the innovations of this study about the localization of the distress model in Iran using the worldwide and Iranian model together is using macroeconomic and accounting variables and artificial intelligence methods in three levels. The results of this study show that the non-linear algorithm for vector machine supporting the Gaussian kernel has more ability to predict the distress of companies, compared to the Chide rule-oriented algorithm. Key words: Financial Bankruptcy, artificial intelligence, Macro-economic and Accounting variables.JEL: C53،A12،B26،G33،M41