Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry.
The Altman models have been widely cited in both trade publications, finance and accounting textbooks. The models are seen as providing the basis for predicting financial distress of a company, a tool to assist in credit evaluation, an internal control guideline for management and an aid in portfoli...
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English English English |
| Published: |
2009
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| Online Access: | https://eprints.nottingham.ac.uk/23202/ |
| _version_ | 1848792529328144384 |
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| author | Prom, Augustus Lawrence |
| author_facet | Prom, Augustus Lawrence |
| author_sort | Prom, Augustus Lawrence |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The Altman models have been widely cited in both trade publications, finance and accounting textbooks. The models are seen as providing the basis for predicting financial distress of a company, a tool to assist in credit evaluation, an internal control guideline for management and an aid in portfolio selection for investors.
Edward I Altman is internationally renowned as an expert on corporate bankruptcy and credit risk analysis. He is one of the main researchers that formed the foundation for other academics in the field of Corporate Bankruptcy Prediction.
Altman came up with his first model in 1968 which was called 5 Variable Z Score model which was used for the manufacturing industry in the USA. After a few years he came up with another model in 1983 which was called the 4 Variable Z score Model. The reason behind the 4 variable model was to apply it to the private firm industry. Both models came up with successful Bankruptcy prediction results with an accuracy of up to 95% for both models at a year prior to bankruptcy and around 70% prediction accuracy 5 years prior to Bankruptcy.
The aim of this research is to re-examine the Altman models to find out if they can still be used in recent periods, to confirm if they can be used within the Service industry rather than the Manufacturing or Private firm industry and to find out which of the model performs better at predicting bankruptcy in the Service Industry.
The author finds that both models can predict a year prior to Bankruptcy in the Service Industry at an accuracy rate of 82.3% for the 5 Variable Model and 81.5% for the 4 Variable model. Both models decreased to around 70% accurate prediction 5 years prior to Bankruptcy which is quite consistent with the literature. This means that after applying Altman’s models to the service industry, both have Underperformed Altman’s original results. This is discussed further in the study and possible reasons given for the lower accuracy rate.
These results confirm that Altman’s models can be used in recent periods and it can be applied to the service industry. In terms of performance of the different models in the Service Industry, the results indicate that it depends on which year the prediction is being used for. If it is a Year prior or 5 years prior, the 5 Variable model is recommended and if it is 2, 3 or 4 years prior, the 4 Variable model is recommended.
The study concludes by proposing some recommendations for further research which can further explain the models underperformance in the service industry and add more insight to the current literature on Corporate Bankruptcy prediction. |
| first_indexed | 2025-11-14T18:45:51Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-23202 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-14T18:45:51Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-232022022-03-21T16:05:49Z https://eprints.nottingham.ac.uk/23202/ Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. Prom, Augustus Lawrence The Altman models have been widely cited in both trade publications, finance and accounting textbooks. The models are seen as providing the basis for predicting financial distress of a company, a tool to assist in credit evaluation, an internal control guideline for management and an aid in portfolio selection for investors. Edward I Altman is internationally renowned as an expert on corporate bankruptcy and credit risk analysis. He is one of the main researchers that formed the foundation for other academics in the field of Corporate Bankruptcy Prediction. Altman came up with his first model in 1968 which was called 5 Variable Z Score model which was used for the manufacturing industry in the USA. After a few years he came up with another model in 1983 which was called the 4 Variable Z score Model. The reason behind the 4 variable model was to apply it to the private firm industry. Both models came up with successful Bankruptcy prediction results with an accuracy of up to 95% for both models at a year prior to bankruptcy and around 70% prediction accuracy 5 years prior to Bankruptcy. The aim of this research is to re-examine the Altman models to find out if they can still be used in recent periods, to confirm if they can be used within the Service industry rather than the Manufacturing or Private firm industry and to find out which of the model performs better at predicting bankruptcy in the Service Industry. The author finds that both models can predict a year prior to Bankruptcy in the Service Industry at an accuracy rate of 82.3% for the 5 Variable Model and 81.5% for the 4 Variable model. Both models decreased to around 70% accurate prediction 5 years prior to Bankruptcy which is quite consistent with the literature. This means that after applying Altman’s models to the service industry, both have Underperformed Altman’s original results. This is discussed further in the study and possible reasons given for the lower accuracy rate. These results confirm that Altman’s models can be used in recent periods and it can be applied to the service industry. In terms of performance of the different models in the Service Industry, the results indicate that it depends on which year the prediction is being used for. If it is a Year prior or 5 years prior, the 5 Variable model is recommended and if it is 2, 3 or 4 years prior, the 4 Variable model is recommended. The study concludes by proposing some recommendations for further research which can further explain the models underperformance in the service industry and add more insight to the current literature on Corporate Bankruptcy prediction. 2009-09-24 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/23202/1/Dissertation_E-Copy.pdf application/pdf en https://eprints.nottingham.ac.uk/23202/2/Data_for_Failed_firms.pdf application/pdf en https://eprints.nottingham.ac.uk/23202/3/Data_for_non_-_failed_firms.pdf Prom, Augustus Lawrence (2009) Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. [Dissertation (University of Nottingham only)] (Unpublished) |
| spellingShingle | Prom, Augustus Lawrence Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title | Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title_full | Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title_fullStr | Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title_full_unstemmed | Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title_short | Predicting Corporate Bankruptcy: A Re-examination of the Altman's Z Score models in the service industry. |
| title_sort | predicting corporate bankruptcy: a re-examination of the altman's z score models in the service industry. |
| url | https://eprints.nottingham.ac.uk/23202/ |