PREDICTION OF FINANCIAL FAILURE USING LOGISTIC REGRESSION ANALYSIS

Abstract

In the business world where there is intense competition, companies need to be financially strong in order to survive and make a difference. Financial failure causes companies to lose their assets and even go bankrupt. For this reason, the financial situation is an important issue that needs to be followed both for the company itself and for investors and creditors. In this study, it is aimed to determine the variables that play an important role in financial failure by using the data of companies operating in the manufacturing sector in Borsa Istanbul in the years 2021-2022. Whether companies were financially unsuccessful or not was determined by Altman's Z-Score model. Logistic regression analysis was used in the study, which aimed to predict financial failure one year in advance. In the model, 90.3% of companies that were not financially unsuccessful and 73.5% of companies that were financially unsuccessful were classified correctly. Overall, the correct classification success of the model is 84.4%. As a result of the study, it was seen that while the Total Asset Turnover increased, the probability of being classified as financial unsuccessful decreased. On the other hand, it was found that while the Liquid Assets Turnover and Long-Term Debt / Total Assets Ratio increased, the probability of being classified as financially unsuccessful increased.