Bankruptcy prediction using altman z-score model: a case of public listed manufacturing companies in Malaysia
Date
2015-11
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Over the years, serious attention has been to bankruptcy prediction models and the problems associated with predicting failure in corporate firms. Corporate failure prediction has become a very vital issue in finance especially given the fact that so many researchers have given so many different types of prediction model. In addition, the multiple discriminant analysis seems to be the best model that achieves a very high result of accuracy levels. In this study, 34 public listed manufacturing companies in Malaysia where used from 2010-2014. Companies were chosen from companies listed under the PN17 companies while healthy companies where matched using paired sample t-test using random stratified sampling method. Initially, the main aim or objective of this study was to examine the reliability and relationship of Altman’Z-score model to corporate failure and to investigate if all failing companies where listed under the PN-17 on the Kuala Lumpur stock exchange (KLSE) now popularly known as Bursa Malaysia. Findings showed that not all failed companies where listed under PN17 companies in bursa Malaysia. While all but one of the companies under the PN17 companies where in the safe zone in the fifth year. The Study findings showed four out of five financial ratios where significantly related in the prediction of corporate failure under the Z-score model. Also the regression analysis showed that the model is a great fit with significance of 0.000 and accuracy levels of 86% and 99.6%.