predicting the performance of the stocks of private commercial Banks listed on Damascus stock exchange using logistic regression

الملخص

The main objective of this research is to evaluate the effectiveness of using the logistic regression model in predicting the performance of stocks by applying it to the eleven private commercial banks listed on the Damascus Securities Exchange, during the time period from 2011 to 2019, and the study was done through Extracting the data contained in the financial reports published by the study sample banks, and calculating eleven financial ratios that represent the independent variables of the study, and the dependent variable was represented in the performance of the stock (good, bad), and the data was entered into the SPSS statistical program in a stepwise manner, and the appropriate model was obtained at the fourth step. Among the most important results that were reached through the results of the statistical analysis is that it is possible to predict the performance of the stocks of private commercial banks listed in the Damascus Stock Exchange using the logistic regression model, and that the accuracy of the model reached 80.8%, and that the financial ratios that contribute to separation and discrimination Among the stocks with good performance and stocks with bad performance, in order of relative importance is represented by: market to book value, debt to assets ratio, earnings per share, debt to equity ratio, and the research presented a set of proposals, the most important of which was the need for those in charge of managing banks to pay attention to the variables that show through the current study the existence of a relationship between them and the performance of stocks in the way that It is positively reflected on the performance of its shares in the financial market, and the expansion of the use of the logistic regression model in predicting the performance of shares by investors, enabling them to make their investment decisions efficiently and effectively