Analysis of Precision Using the Altman Modification, Springate, Zmijewski, and Grover Model for Financial Distress Prediction

Jessica Magdalena, Toto Rusmanto

Abstract

This study measures the accuracy of financial distress predictions by using the Zmijewski, Modified Altman, and Springate, Grover models. This research will take 2013-2017 as test data and compare it with the company's actual conditions in 2018 and 2019 to determine whether the three models can predict the company's financial difficulties to assess the accuracy of the model. This research was conducted using descriptive methods and quantitative approaches. This study took a sample of industries related to Real Estate and Property that were displayed on the Indonesia Stock Exchange (IDX) from 2013-2017 using a purposive sampling technique. Except for the modified Altman and Grover models, the results show discrepancies between the models and apparent accuracy from the 2018–2019 actuals and estimates for 2013–2017. The results of research conducted and tested using Stata 17 show that the model with the lowest accuracy is obtained by Springate with a score of 72%, type error I is 3%, and II is 26%. The second lowest model is obtained by the modified Altman model with a total score of 77% and type I error of 13%. The model with the second highest score was achieved by Grover with a score of 87% and type I error of 13%. The highest model in this test was achieved by Zmijewski with a model accuracy rate of 90% and type I and II errors of 5%.

 

Keywords: financial distress, the Altman modification, Springate, Zmijewski, Grover.

 

DOI: https://doi.org/10.55463/hkjss.issn.1021-3619.60.92


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