Comparison of financial distress prediction methods: Altman Z-Score, Zmijewski, Springate, and Grover in Indonesian retail trading companies

Abstract

This study seeks to identify the most accurate method for predicting financial distress among retail trade sub-sector companies listed on the Indonesia Stock Exchange by comparing the Altman Z-Score, Zmijewski, Springate, and Grover methods. The research population comprises retail trade sub-sector companies listed on the Indonesia Stock Exchange during the 2019-2021 period, encompassing a total of 18 companies. A purposive sampling technique was employed, resulting in a sample size of 18 companies. The study utilized a four-mean difference test alongside an accuracy level test to evaluate the predictive performance of each method. The findings indicate that the Altman Z-Score method outperforms the Grover, Zmijewski, and Springate methods in accurately predicting financial distress within the examined companies.