Predicting Bankruptcy of Pharmaceutical Companies Using The Altman Z-Score and Grover Methods

Abstract

The main objective of this study is to evaluate and contrast the effectiveness of two financial distress prediction models to predict bankruptcy, namely Altman Z-Score and Grover. The sampling method used was purposive sampling, where the samples were purposively selected from the population of pharmaceutical companies listed on the Indonesia Stock Exchange (IDX), which was listed in 2018. The results showed that the evaluated predictive models were able to forecast the incidence of financial distress to predict bankruptcy. In terms of accuracy, the Altman Z-Score model stands out as the most effective than the Grove model, with an accuracy rate of 86.67%. It is followed by the Grover model, which occupies the second position with an accuracy rate of 55.56%.