Analysis of Financial Distress Potential Using the Altman Z-Score and Springate Methods in Predicting Company Bankruptcy - Afifah, Nindy Tri; Fatihudin, Didin; Roosmawarni, Anita (The Journal of Financial, Accounting, and Economics, 2024)
This study aims to identify the potential for financial distress in oil and gas sub-sector companies listed on the Indonesia Stock Exchange using two prediction models, namely Altman Z-Score and Springate. This study also tests whether there is a significant difference between the two methods in detecting bankruptcy risk. The sampling method used is purposive sampling, with the population consisting of all oil and gas sub-sector companies listed on the IDX during the period 2011–2015, and six companies were obtained as samples that met the criteria. This study was motivated by the decline in national oil and gas reserves, technical-operational challenges, and global oil price volatility which have a significant impact on the financial stability of companies in this sector. The data analysis methods used include the application of the Altman Z-Score and Springate models to calculate the financial distress score for each company, followed by a Paired Sample T-Test to determine significant differences between the two methods. The results of the study indicate that most companies show indications of being in a high-risk zone for financial distress, both based on the Altman Z-Score and Springate analyses. In addition, statistically significant differences were found between the prediction results of the two models, indicating differences in sensitivity in detecting bankruptcy risk. The implications of this study indicate the importance for oil and gas company management, investors, and regulators to use more than one analysis model in identifying and anticipating financial crises early in order to maintain the sustainability of the national energy industry.