CORPORATE FAILURE PREDICTION IN MALAYSIA

  • Lai Yeen Khong Lecturer, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman (UTAR)
  • Cheng Suet Low Lecturer, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman (UTAR)
  • Ling Peck Tee Lecturer, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman (UTAR)
  • Leng wan Lim Lecturer, Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman (UTAR)

Abstract

Abstract This study is to develop a financial prediction equation that based on public listed companies in Malaysia. Logistic regression analysis was employed to develop the equation. Eleven financial ratios were found useful in developing the financial distress prediction models. The sample consists forty eight public listed companies in Malaysia and the data covers the period from 2010 to 2014. SPSS software was used to perform the statistical analysis. The result indicated that the selected financial ratios were significant for corporate failure prediction in Malaysia. The developed equation is able to predict financial failure with an eighty eight percent accuracy rate. The accuracy is higher than those previous studies which used discriminate analysis technique. As the financial crisis of 1997 had created a major impact for Malaysia corporations, a financial distress prediction model is needed to prevent the public funds lost. This study was conducted using the recent data on public listed companies in Malaysia. Hence, this model is more relevant in predicting corporate failure in Malaysia.

Index Terms financial prediction equation, Logistic regression analysis, Corporate failure, Financial failure, Discriminate analysis technique

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Published
2015-10-05
How to Cite
Khong, L., Low, C., Tee, L., & Lim, L. (2015). CORPORATE FAILURE PREDICTION IN MALAYSIA. Journal of Research in Business, Economics and Management, 4(2), 343-375. Retrieved from http://scitecresearch.com/journals/index.php/jrbem/article/view/411
Issue
Vol 4 No 2: JRBEM
Section
Articles

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