Articlediamond2018

KETEPATAN MODEL ALTMAN, SPRINGATE, ZMIJEWSKI, DAN GROVER DALAM MEMPREDIKSI FINANCIAL DISTRESS

19 citations0/0 files storedJurnal Reviu Akuntansi dan Keuangan

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

Abstract

This study aims to identify and analyze the accuracy models of financial distress between the model results of Altman, Springate, Zmijewski, and Grover. The model used by investors, creditors and the company itself who will invest in the company and evaluate the financial performance. Samples from this study are 1.321 firm-year, collected from Indonesia Stock Exchange for the period 2012-2016 and were selected using purposive sampling method. The data used in this study are financial reports of each company. The data obtained were tested with logistic regression. This study shows that the model of Altman, Springate, Zmijewski, and Grover has a significant impact and can be used for predicting the condition of financial distress. However, the Springate model is the most appropriate model for predicting the condition of financial distress because it has the highest level of coefficient determination compared to other models.

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References

2003Analisis Rasio Keuangan untuk Memprediksi Kondisi Financial Distress Perusahaan Manufaktur yang Terdaftar di Bursa Efek Jakarta 1999An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables 2003RE-ESTIMATIONS OF THE ZMIJEWSKI AND OHLSON BANKRUPTCY PREDICTION MODELS 2012The Accuracy of Altman’s Models in Predicting Hotel Bankruptcy 2017Prediksi Financial Distress Pada Perusahaan Manufaktur Di Bursa Efek Indonesia 2017ANALISIS PERBANDINGAN MODEL SPRINGATE DAN ALTMAN Z SCORE TERHADAP POTENSI FINANCIAL DISTRESS (STUDI KASUS PADA PERUSAHAAN SEKTOR KOSMETIK YANG TERDAFTAR DI BURSA EFEK INDONESIA)2016Investigate the Ability of Bankruptcy Prediction Models of Altman and Springate and Zmijewski and Grover in Tehran Stock Exchange 2015Bankruptcy Prediction Analysis of Manufacturing Companies Listed in Indonesia Stock Exchange

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