2010•Unpublished venueRequires access

Prediction of financial distress companies in the mixed sector in Malaysia: a revisit using PN4 data

Mohd Norfian Alifiah, Norhana Binti Salamudin, Ismail Ahmad

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Abstract

This study revisited the prediction of financial distress companies in the mixed sector in Malaysia. This is achieved by using PN4 companies as the dependent variable and financial ratios as the independent variables. Logit Analysis was used because the dependent variable is binary or dichotomous in nature. It shows the probability of a company being financially distressed and it provides the coefficient value (positive or negative) of the independent variables (s) that are used as predictors. The results show that debt ratio and working capital ratio were significant in predicting financial distress companies in the mixed sector in Malaysia. The findings from the internal validation reveal that the prediction model provided a more than 50% chance that the model is accurate. However, the findings from the external validation indicate that the model might not be able to be used outside the estimation time period because the overall percentage accuracy was only slightly higher than 50% for five years before distress. This study not only provides the prediction model of financial distress companies in the mixed sector in Malaysia but it also validates the findings internally and externally. Internal and external validations were seldom conducted in previous studies due to lack of data.

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What this paper is about

This study revisited the prediction of financial distress companies in the mixed sector in Malaysia. This is achieved by using PN4 companies as the dependent variable and financial ratios as the independent variables. Logit Analysis was used because the dependent variable is binary or dichotomous in nature. It shows the probability of a company being financially distressed and it provides the coefficient value (positive or negative) of the independent variables (s) that are used as predictors. The results show that debt ratio and working capital ratio were significant in predicting financial distress companies in the mixed sector in Malaysia. The findings from the internal validation reveal that the prediction model provided a more than 50% chance that the model is accurate. However, the findings from the external validation indicate that the model might not be able to be used outside the estimation time period because the overall percentage accuracy was only slightly higher than 50% for five years before distress. This study not only provides the prediction model of financial distress companies in the mixed sector in Malaysia but it also validates the findings internally and externally. Internal and external validations were seldom conducted in previous studies due to lack of data.

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Available abstract

This study revisited the prediction of financial distress companies in the mixed sector in Malaysia. This is achieved by using PN4 companies as the dependent variable and financial ratios as the independent variables. Logit Analysis was used because the dependent variable is binary or dichotomous in nature. It shows the probability of a company being financially distressed and it provides the coefficient value (positive or negative) of the independent variables (s) that are used as predictors. The results show that debt ratio and working capital ratio were significant in predicting financial distress companies in the mixed sector in Malaysia. The findings from the internal validation reveal that the prediction model provided a more than 50% chance that the model is accurate. However, the findings from the external validation indicate that the model might not be able to be used outside the estimation time period because the overall percentage accuracy was only slightly higher than 50% for five years before distress. This study not only provides the prediction model of financial distress companies in the mixed sector in Malaysia but it also validates the findings internally and externally. Internal and external validations were seldom conducted in previous studies due to lack of data.

Key concepts: Logistic regression, Financial ratio, Financial distress, Logit, Distress, Debt ratio, Variables, Actuarial science

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