Identifying the determinants of financial distress for public listed companies in Malaysia

Companies that face financial distress are always regarded as the root cause of enormous financial and economic losses for many stakeholders and at the same time, contribute to social unrest within the society. Identifying the determinants of financial distress in advance will bring many advanta...

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Main Author: Ahmad Monir Abdullah,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2020
Online Access:http://journalarticle.ukm.my/16767/1/35017-138453-1-PB.pdf
http://journalarticle.ukm.my/16767/
https://ejournal.ukm.my/pengurusan/issue/view/1328
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spelling my-ukm.journal.167672021-06-14T03:47:49Z http://journalarticle.ukm.my/16767/ Identifying the determinants of financial distress for public listed companies in Malaysia Ahmad Monir Abdullah, Companies that face financial distress are always regarded as the root cause of enormous financial and economic losses for many stakeholders and at the same time, contribute to social unrest within the society. Identifying the determinants of financial distress in advance will bring many advantages to stakeholders so that they can manage their companies effectively. This study aimed to identify the determinants of financial distress for Malaysian public listed companies (PLC) by utilising financial ratios and market data. Additionally, this study focuses on finding a better distress prediction model between the traditional statistical approach that utilises a logistic regression and an artificial neural networks (ANN) model. Sixteen ratios were selected in the study and two techniques were used to assess the data of 192 Malaysian PLC. The empirical findings from this research show that current assets turnover (CAT), working capital to total assets (WCTA,) and retained earnings to total assets (RETA) display the highest ability to distinguish between financially distressed and non-distressed groups. The results also indicate that the mentioned variables possessed a high discriminant and predictive power. This study also found that the ANN model has a higher predictive accuracy compared to the logistic regression model. Penerbit Universiti Kebangsaan Malaysia 2020 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/16767/1/35017-138453-1-PB.pdf Ahmad Monir Abdullah, (2020) Identifying the determinants of financial distress for public listed companies in Malaysia. Jurnal Pengurusan, 59 . pp. 1-15. ISSN 0127-2713 https://ejournal.ukm.my/pengurusan/issue/view/1328
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Companies that face financial distress are always regarded as the root cause of enormous financial and economic losses for many stakeholders and at the same time, contribute to social unrest within the society. Identifying the determinants of financial distress in advance will bring many advantages to stakeholders so that they can manage their companies effectively. This study aimed to identify the determinants of financial distress for Malaysian public listed companies (PLC) by utilising financial ratios and market data. Additionally, this study focuses on finding a better distress prediction model between the traditional statistical approach that utilises a logistic regression and an artificial neural networks (ANN) model. Sixteen ratios were selected in the study and two techniques were used to assess the data of 192 Malaysian PLC. The empirical findings from this research show that current assets turnover (CAT), working capital to total assets (WCTA,) and retained earnings to total assets (RETA) display the highest ability to distinguish between financially distressed and non-distressed groups. The results also indicate that the mentioned variables possessed a high discriminant and predictive power. This study also found that the ANN model has a higher predictive accuracy compared to the logistic regression model.
format Article
author Ahmad Monir Abdullah,
spellingShingle Ahmad Monir Abdullah,
Identifying the determinants of financial distress for public listed companies in Malaysia
author_facet Ahmad Monir Abdullah,
author_sort Ahmad Monir Abdullah,
title Identifying the determinants of financial distress for public listed companies in Malaysia
title_short Identifying the determinants of financial distress for public listed companies in Malaysia
title_full Identifying the determinants of financial distress for public listed companies in Malaysia
title_fullStr Identifying the determinants of financial distress for public listed companies in Malaysia
title_full_unstemmed Identifying the determinants of financial distress for public listed companies in Malaysia
title_sort identifying the determinants of financial distress for public listed companies in malaysia
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2020
url http://journalarticle.ukm.my/16767/1/35017-138453-1-PB.pdf
http://journalarticle.ukm.my/16767/
https://ejournal.ukm.my/pengurusan/issue/view/1328
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score 13.211869