PhD

Financially distressed companies always bring about enormous financial and economic losses to many stakeholders, such as management, stockholders, employees and customers together with a substantial social and economic cost to the country. Therefore, a distress prediction model that can predict the event and identify the determinants in advance would serve to reduce such losses by providing a pre-warning signal to stakeholders. Preventive actions can then be taken by stakeholders if they can obtain early warning signal of probable failure that will lead to the efficient allocation of available resources to reduce losses. For these reasons, identifying the financial distress determinants that can give accurate prediction has become an essential aspect of finance. Our study will try to identify the financial distress determinants in Malaysia by applying logistic regression analysis (LRA) method together with multivariate discriminant analysis (MDA) and artificial intelligence algorithm (ANN) for robustness. Twenty-one independent variables were selected in our study that can be categorised as financial ratio variables, market variables and non-financial data variables. Data samples were derived from 158 Malaysian public listed companies and the assessment period was from the year 2001 until 2012 ...