Financial Modelling of Metal and Mineral Mining Companies in Indonesia using Altman Z-scores

Abstract

Predictions about a company's financial condition related to bankruptcy are important information for interested parties, such as creditors, investors, government, auditors, and the company's internal management. This research models the financial condition of metal and mineral mining companies through the Altman Z-Score model and panel data regression analysis. This study focuses on a sample of nine companies involved in metal and mineral mining from 2017 to 2022. In this study, the Altman method was used to determine a company's health category using the Z-score standard. Panel Data Regression modelling showed that the fixed model was the best. The partial test results indicated that WCTA and RETA did not affect the Altman Z-score. However, when considering all the ratios simultaneously (WCTA, RETA, MVBV, and STA), they contribute to predicting a company's financial condition. These results highlight the importance of understanding the variables that influence a company's health and progress. Notably, the variables of WCTA, RETA, and STA play a crucial role in determining the Altman Z-score and contribute to our understanding of a company's financial condition.