Using Profitability and Debt ratios through Discriminant Analysis and Logistic Regression to Predict Financial Situation - An Applied Study on Financial Companies' Services on the Amman Stock Exchange

الملخص

This research aimed to evaluate the effectiveness of using quantitative methods, specifically logistic regression and discriminant analysis models, in predicting the financial status of companies based on key profitability and leverage ratios. The research relied on historical financial data from a sample of 18 financial services companies listed on the Amman Stock Exchange.

This study adopted a descriptive approach to monitor and track financial ratios, particularly profitability and leverage ratios, over an eight-year period from 2014 to 2021. Data was collected from the website of the Securities Depository Center at the Amman Stock Exchange.  Subsequently, several quantitative statistical methods were used to analyze and evaluate these ratios and to predict the future financial status of these companies.

The results showed that the accuracy of predicting companies' classification and financial status ranged between 72.2% and 75% in both the logistic regression and discriminant analysis methods, and was 73.6% in the decision tree method.  Furthermore, earnings per share and the market-to-book ratio had a statistically significant effect on the response variable (companies' financial status), while the debt coverage ratio did not play a role in improving the model used.