Penggunaan Binary Logit untuk Prediksi Financial Distress Perusahaan Yang Tercatat Di Bursa Efek Jakarta

Financial Distress Prediction In Indonesian Stock Exchange

Rowland Bismark Fernando Pasaribu

MPRA Paper from University Library of Munich, Germany

Abstract: This study aimed to establish the financial distress prediction in a public company listed on the Jakarta Stock Exchange specifically incorporated in the trading industry. The samples used in research are all public companies incorporated in the trading industry 2002-2006 period. This study used six initial discriminator and 34 financial ratios as an operational variable. The analysis technique used is a binary logit regression. Empirical result shows that companies that do not create economic value-added, illiquid, low operational efficiency and high levels of financial leverage have a large probability of financial distress.

Keywords: EVA; financial distress; financial ratios; binary logit (search for similar items in EconPapers)
JEL-codes: A13 G3 G32 O16 (search for similar items in EconPapers)
Date: 2008-08
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Published in Jurnal Ekonomi, Bisnis, dan Akuntansi VENTURA 2.11(2008): pp. 153-172

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https://mpra.ub.uni-muenchen.de/39816/2/MPRA_paper_39816.pdf revised version (application/pdf)

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