Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern
The framework used in this study, to predict financial distress amongst the Public Listed Companies (PLCs) in Malaysia, utilizes the 5-variables Altman’s Z-Score Model as the base model and the Auditors’ Opinion on going concern as the 6th variable. Multiple Discriminant Analysis (MDA) and Logistic...
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| Format: | Thesis |
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Curtin University
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/75450 |
| _version_ | 1848763495186694144 |
|---|---|
| author | Yee, Hun Leek |
| author_facet | Yee, Hun Leek |
| author_sort | Yee, Hun Leek |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The framework used in this study, to predict financial distress amongst the Public Listed Companies (PLCs) in Malaysia, utilizes the 5-variables Altman’s Z-Score Model as the base model and the Auditors’ Opinion on going concern as the 6th variable. Multiple Discriminant Analysis (MDA) and Logistic Regression Analysis (LRA) have been employed, and the revised 6-variables model developed using LRA has the highest accuracy to predict financial distress amongst the PLCs in Malaysia. |
| first_indexed | 2025-11-14T11:04:22Z |
| format | Thesis |
| id | curtin-20.500.11937-75450 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:04:22Z |
| publishDate | 2018 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-754502019-05-22T05:39:50Z Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern Yee, Hun Leek The framework used in this study, to predict financial distress amongst the Public Listed Companies (PLCs) in Malaysia, utilizes the 5-variables Altman’s Z-Score Model as the base model and the Auditors’ Opinion on going concern as the 6th variable. Multiple Discriminant Analysis (MDA) and Logistic Regression Analysis (LRA) have been employed, and the revised 6-variables model developed using LRA has the highest accuracy to predict financial distress amongst the PLCs in Malaysia. 2018 Thesis http://hdl.handle.net/20.500.11937/75450 Curtin University fulltext |
| spellingShingle | Yee, Hun Leek Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title | Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title_full | Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title_fullStr | Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title_full_unstemmed | Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title_short | Predicting Financial Distress Amongst Public Listed Companies in Malaysia using Altman’s Z-Score Model and Auditors’ Opinion on Going Concern |
| title_sort | predicting financial distress amongst public listed companies in malaysia using altman’s z-score model and auditors’ opinion on going concern |
| url | http://hdl.handle.net/20.500.11937/75450 |