Modelling PN4 classification among Malaysian listed companies
Emerald Group Publishing Limited
Faculty of Business and Law
School of Accounting, Finance and Economics
Prior studies have demonstrated that simple linear discriminant models can be highly successful in identifying financially distressed companies, and therefore useful in predicting corporate failures. Such models have been shown to be both industry and country specific even though their variable selection has been narrow. These models have remained incredibly robust over time despite variations in the definition of the 'distressed' state employed for modelling purposes. This paper extends such analysis to the main and second boards of the Kuala Lumpur Stock Exchange (KLSE) in Malaysia, with particular reference to their designation of PN4 companies (those classified as 'distressed' in accordance with Practice Note No. 4 introduced in February 2001). The findings of the study show that a single discriminant model has high classificatory power for both boards of the KLSE, and that the optimum model comprises financial ratio variables common to other published models. Previous findings are therefore shown to be substantially generalisable to a new environment and to a different definition of distress.