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ANALISIS PREDIKTOR DELISTING TERBAIK ANTARA MODEL ALTMAN Z-SCORE MODIFIKASI, SPRINGATE, DAN ZMIJEWSKI

RACHMANIA, FADILAH BENITA (2016) ANALISIS PREDIKTOR DELISTING TERBAIK ANTARA MODEL ALTMAN Z-SCORE MODIFIKASI, SPRINGATE, DAN ZMIJEWSKI. Undergraduate thesis, STIE PERBANAS SURABAYA.

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Abstract

The purpose of this study is to figure out the best delisting predictors of Altman Z-Score, Springate and Zmijewski model of modification. The objects of this study are a number of delisted companies that trade shares (delisted) in Indonesian Stock Exchange in 2008-2014. As areference for the delisted companies, the researcher chose some companies that were still listed on Indonesian Stock Exchange with two times sample from delisted companies and with the same business types. Comparison samples were taken based on the size of the companies and the same delisting period. The method of analysis used logistic regression model. The results of the research showed that the Altman Z-Score Modification(III) and Springate model were the only model of the three delisting predictor models that could be used to predict the delisted company during the period of observation. It turned out that Altman Z-Score Modification(III) and Springate model showed complete ratio compared to Zmijewski model. Meanwhile, the Springate model showed better result than the Zmijewski Model. The Springate model showed two similar ratios with Altman Z-Score Modification but in different criteria. The Zmijewski model could not predict the delisted companies because one ratio of the Zmijewski model showed a bad result to make X-Score positive and it is contradictory with signalling theory. Keywords: Delisting, The Altman Z-Score Modification Model, The Springate Model, The Zmijewski Model

Item Type: Thesis (Undergraduate)
Subjects: 600 - TECHNOLOGY > 657 - ACCOUNTING > 657.042 - FINANCIAL ACCOUNTING
Divisions: Bachelor of Accountancy
Depositing User: Perpustakaan Universitas Hayam Wuruk Perbanas Surabaya
Date Deposited: 05 Jul 2017 01:13
Last Modified: 05 Jul 2017 01:13
URI: http://eprints.perbanas.ac.id/id/eprint/1735

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