The Comparative Analysis of Altman Z-Score, Springate, Zmijewski, And Internal Growth Rate Model in Predicting the Financial Distress (Empirical Study on Mining Companies Listed on Indonesia Stock Exchange 2014-2017)

Sri Mulyati,Syahrul Ilyasa

doi:10.24002/kinerja.v24i1.3231

Abstract

This study aims to: (1) determine whether there are differences in scores between the Altman model, Springate, Zmijewski and Internal Growth Rate in predicting financial distress, (2) find out the most accurate prediction model in predicting financial distress of mining companies in Indonesia. The data used in this study is the company's financial statements published on Indonesia Stock Exchange. The population in this study is the mining companies listed on the Indonesia Stock Exchange during 2014-2017 which are 41 issuers. The sampling technique used purposive sampling so that 36 issuers were obtained as the research samples. This study compares the scores of four financial distress prediction models using statistical techniques and the accuracy of the prediction model by considering the level of accuracy and type I error. The conclusions from this study indicate the differences between the four prediction models. The Springate model is the best with an accuracy rate of 88.89% and an 8% type I error, the second is the Zmijewski model with an accuracy rate of 88.89% and a type I error rate of 42.86%, the third is the Altman model with 75% accuracy and error type I 46.67%, and the last is an internal growth rate model with an accuracy rate of 66.69% and type I error rate of 11.11%.Keywords: financial distress, financial statements, mining, prediction models

Highlights

Rapid business competition demands companies to continue developing innovations, improving their performance and expanding their businesses in order to continue to survive and compete
This study aims to determine whether there are differences in the scores of each model, and find out which model has the highest level of accuracy in predicting financial distress in mining sector companies listed on the Indonesia Stock Exchange
Aiming at investigating whether there are difference scores dealing with level of accuracy resulted from Altman Z-Score, Springate, Zmijewski and Interal Growth Rate model in predicting the financial distress and determining the most accurate prediction model in predicting financial distress of mining companies listed in Indonesia Stock Exchange from 2014 up to 2017, this study results in some conclusions

Summary

Introduction

Rapid business competition demands companies to continue developing innovations, improving their performance and expanding their businesses in order to continue to survive and compete. The company's ability to compete is determined by the company's performance itself. The company that is unable to compete in maintaining its performance will gradually be displaced from their industrial environment and will experience financial distress which will lead to bankruptcy. Bankruptcy is a condition where the company is no longer able to operate the company properly due to financial distress or financial distress experienced by the entity is already severe. In order to maintain the survival of the company, the management must improve its performance. According to Dermawan Sjahrijal (2008: 202) financial distress is a condition in which a company experiences financial distress and is threatened with bankruptcy. If the company goes bankrupt, there will be bankruptcy costs caused by the cost of being forced to sell the assets below the market price, the company's liquidity costs, the impairment of fixed assets that is expired before sold and others

Objectives

Methods

Findings

Conclusion