Comparison of Bankruptcy and Sustainability Prediction: Altman Z Score Versus Grover Model

Abstract

This study aims to prove whether the Altman Z-Score and Grover models can predict bankruptcy and whether there are differences in scores between the two models.  Besides, it aims to identify which prediction model is the most accurate in predicting bankruptcy and sustainability in retail companies. This research was conducted by taking a sample of financial statement data of 57 on the Indonesia Stock Exchange (BEI) in 2016-2018 which were divided into two groups: 27 financial statement data that went bankrupt (Financial Distress) and 30 financial statement data that are still ongoing (Non-Financial Distress), with a total sample of financial statement data of 57. The data collection method uses the purposive sampling method and the data is analysed using logistic regression and paired sample t-test. The accuracy of the prediction model is analysed utilising the SPSS software with the condition that the data must be normally distributed. The result shows that the Altman Z-Score and Grover models can be used to predict bankruptcy. This shows that the financial ratios used in the Altman Z-Score and Grover models can describe the condition of bankruptcy. The results of this study also show that there are differences in scores between the Altman Z-Score model and Grover in predicting bankruptcy, and the Altman Z-Score Model is the most suitable bankruptcy prediction model applied to retail companies listed on the Indonesia Stock Exchange with an accuracy rate of 60%.