Predicting Financial Distress amongst Public Listed Companies in Malaysia - the Accuracy and Effectiveness of Altman’s Z-Score Model
This paper focuses on predicting financial distress amongst Public Listed Companies (“PLCs”) in Malaysia using Altman’s Z-Score. Financial distress prediction models were pioneered by Beaver’s univariate test (1966) and Altman’s discriminant analysis (1968). Over the last four decades, prediction of...
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| Format: | Journal |
| Language: | English |
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AeU
2015
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| Subjects: | |
| Online Access: | http://ur.aeu.edu.my/37/1/Yee%20Hun%20Leek.doc http://ur.aeu.edu.my/37/ |
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| Summary: | This paper focuses on predicting financial distress amongst Public Listed Companies (“PLCs”) in Malaysia using Altman’s Z-Score. Financial distress prediction models were pioneered by Beaver’s univariate test (1966) and Altman’s discriminant analysis (1968). Over the last four decades, prediction of financial distress has been of considerable interest to various users and stakeholders. In view of the significant impact of Asian financial crisis in 1997-1998, dotcom bubble that peaked in 2000, global financial crisis in 2007-2009, and the current world economic downturn, timely identification of financial distress could serve as an effective “early warning system” for signs of business collapses.
Malaysia, as a developing country, is exposed to the vulnerability of global economy due to the country’s open and export dependent economy. The economic crisis began to adversely affect Malaysia’s economy in July 1997 due to Asian financial crisis which has resulted PLCs in Malaysia to fall into financial distress as these companies were unable to cope with the unexpected downturn. Malaysia is currently facing the challenging uncertain world economies, volatile price of commodities and foreign currencies. This paper focuses on predicting financial distress amongst PLCs in Malaysia using Altman’s Z-Score Model to assess its predictive accuracy. An effective prediction model is of paramount importance to gauge the warning signals of financial distress to strategize the survival techniques applicable to PLCs in Malaysia.
The sample size of this study comprised all 35 financial distress PLCs pursuant to Practice Note 17 (PN17) of Bursa Malaysia as at 1 September 2010 matched with 35 non-financial distress PLCs with similar industry and size. This study found that Altman’s Z-Score model is insufficient for predicting financial distress among the Malaysian PLCs.
The aims of this paper are to seek comments on the accuracy and effectiveness of Altman’s Z-Score Model to predict financial distress of PLCs in Malaysia and to explore other financial and non-financial factors in formulating a more effective prediction model applicable to PLCs in Malaysia |
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