Predicting the Factors Affecting on the Migration of Growth Firms with Financial Health in the Tehran Stock Exchange by Using the Random Forest Method

The purpose of this research is to investigate the factors affecting migration of growth companies with financial health in the Tehran Stock Exchange. In order to make better decisions and also to innovate, this research was conducted only on companies with financial health based on the Black, Scholes and Merton (BSM) model. The statistical population of this study is all companies listed on the Tehran Stock Exchange between 2012 and the end of 2019; therefore, all companies have been operating on the stock exchange during these years and their fiscal year ends in March, Participated in this research. After extracting the statistical sample, the researcher calculated the financial health of the statistical sample companies based on the model introduced by Black, Scholes and Merton (BSM) model, and then by using the Fama and French model, companies with growth migration were identified. Due to superiority of artificial intelligence methods over statistical linear models as well as the benefits of nonlinear methods in prediction, the present study presented a model for predicting the migration of growth stocks using nonlinear algorithm of random forests. Based on the results of the present study, it can be acknowledged that by using historical information, we can suggest factors for modeling growth migration.