| Abstract [eng] |
The main purpose of this master thesis is to determine whether macroeconomic indicators affect the accuracy of bankruptcy prediction models for companies in the transport and storage sector. The work consists three main parts: a literature review and analysis of previous scientific research, the research methodology, and the empirical study. In the first part of the study, a review of scientific literature was conducted, focusing on bankruptcy prediction models and providing a comparative analysis of them. To assess corporate bankruptcy trends and highlight the increasing number of bankruptcies, an overview of bankruptcies in Lithuania's transportation and storage sector was carried out. Furthermore, trends in the number of bankrupt companies were compared with trends in macroeconomic indicators to evaluate whether there is a noticeable correlation between them. Although the topic of bankruptcy prediction has been widely explored, the analysis of previous studies revealed that no specific model has been identified as the most suitable for companies in the transportation and storage sector. Also that little attention has been paid to evaluating whether macroeconomic indicators significantly impact the accuracy of bankruptcy prediction. The second part of the thesis describes the research methodology, developed based on the reviewed scientific literature. The research process includes two stages: first, assessing the accuracy of bankruptcy prediction models and second, modifying the most accurate model by incorporating macroeconomic indicators to evaluate whether their inclusion has a significant impact on model accuracy. The third part of the thesis presents the evaluation of bankruptcy prediction models using discriminant and logistic analysis. The evaluation was based on data from 160 active and 66 bankrupt companies. The results of the first research phase indicated that Altman's bankruptcy prediction model was the most accurate for forecasting bankruptcies in the transportation and storage sector. In the second stage, macroeconomic indicators were incorporated into Altman’s model in two ways. In the first approach, the unemployment rate was added, and the results showed that it generally had a small or negative effect on model accuracy. In the second modification, inflation was integrated into the model, and the results indicated that inflation mostly had a positive impact, although its influence on model accuracy varied depending on specific inflation trends. The third model modification, which excluded macroeconomic indicators, demonstrated that the modified model had a high potential for bankruptcy prediction, achieving better results each year compared to the original Altman model in identifying bankrupt companies. The conclusions and recommendations of this study summarize the key findings from the literature review and the research results. |
