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An investigation into unifying early warning prediction models
Forecasting financial distress has been regarded as a serious and significant problem, and if not signalled in time, has catastrophic ramifications on worldwide economies. Financial distress models are in existence and have been tested with varying results of success. However, there are varying defi...
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| Format: | Thesis |
| Language: | Eng |
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College of Accounting
2024
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| _version_ | 1867614113944829952 |
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| access_status_str | Open Access |
| author | Grieve, Jason |
| author2 | Singh-Sewpersadh, Navitha |
| author_browse | Grieve, Jason Singh-Sewpersadh, Navitha |
| author_facet | Singh-Sewpersadh, Navitha Grieve, Jason |
| author_sort | Grieve, Jason |
| collection | Thesis |
| description | Forecasting financial distress has been regarded as a serious and significant problem, and if not signalled in time, has catastrophic ramifications on worldwide economies. Financial distress models are in existence and have been tested with varying results of success. However, there are varying definitions of financial distress which have contributed to the in-cohesiveness of financial distress literature where users have a limited ability to know what condition of financial distress is being forecast. Following a comprehensive literature review, it was found that financial distress models (Altman, 1968; Beaver, 1966; Gupta, 1983; Ohlson, 1980; Taffler, 1983; Zmijewski, 1984) have not been unified into an early warning signal (EWS) framework according to the specific financial distress conditions they have abilities to predict. Findings also found that risk (Beneish, 1999; Schilit, 2003) and earnings management measures (Sloan, 1996) play a significant role in financial distress forecasting but have also yet to be unified into an EWS framework. This study aims to unify financial distress, risk prediction and earnings management measurements into an EWS framework developed by Tavlin et al. (1989) to enable users the ability to identify the type of EWSs predicted and contributing reasons reducing the fragmentation of the extant literature. The investigation period of the study was for six years (2016 to 2021) using paired sampling methodology with a final sample of 72 delisted and 72 listed companies from the Johannesburg Stock Exchange (JSE). The study employed descriptive analysis to interrogate the results. The results indicated that financial distress models (Altman, 1968; Beaver, 1966; Gupta, 1983; Taffler, 1983; Zmijewski, 1984) and risk and earnings management measures (Beneish, 1999; Schilit, 2003; Sloan, 1996) could be unified into an EWS framework. Key words: bankruptcy prediction; credit risk; probability of default (PD); early warning signals; financial distress, JSE; risk; earnings management |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/39447 |
| institution | University of Cape Town (South Africa) |
| language | Eng |
| last_indexed | 2026-06-10T12:46:53.427Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | College of Accounting |
| publisherStr | College of Accounting |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/39447 An investigation into unifying early warning prediction models Grieve, Jason Singh-Sewpersadh, Navitha Commerce Forecasting financial distress has been regarded as a serious and significant problem, and if not signalled in time, has catastrophic ramifications on worldwide economies. Financial distress models are in existence and have been tested with varying results of success. However, there are varying definitions of financial distress which have contributed to the in-cohesiveness of financial distress literature where users have a limited ability to know what condition of financial distress is being forecast. Following a comprehensive literature review, it was found that financial distress models (Altman, 1968; Beaver, 1966; Gupta, 1983; Ohlson, 1980; Taffler, 1983; Zmijewski, 1984) have not been unified into an early warning signal (EWS) framework according to the specific financial distress conditions they have abilities to predict. Findings also found that risk (Beneish, 1999; Schilit, 2003) and earnings management measures (Sloan, 1996) play a significant role in financial distress forecasting but have also yet to be unified into an EWS framework. This study aims to unify financial distress, risk prediction and earnings management measurements into an EWS framework developed by Tavlin et al. (1989) to enable users the ability to identify the type of EWSs predicted and contributing reasons reducing the fragmentation of the extant literature. The investigation period of the study was for six years (2016 to 2021) using paired sampling methodology with a final sample of 72 delisted and 72 listed companies from the Johannesburg Stock Exchange (JSE). The study employed descriptive analysis to interrogate the results. The results indicated that financial distress models (Altman, 1968; Beaver, 1966; Gupta, 1983; Taffler, 1983; Zmijewski, 1984) and risk and earnings management measures (Beneish, 1999; Schilit, 2003; Sloan, 1996) could be unified into an EWS framework. Key words: bankruptcy prediction; credit risk; probability of default (PD); early warning signals; financial distress, JSE; risk; earnings management 2024-04-25T12:21:39Z 2024-04-25T12:21:39Z 2023 2024-04-24T13:15:19Z Thesis / Dissertation Masters MCom http://hdl.handle.net/11427/39447 Eng application/pdf College of Accounting Faculty of Commerce |
| spellingShingle | Commerce Grieve, Jason An investigation into unifying early warning prediction models |
| thesis_degree_str | Master's |
| title | An investigation into unifying early warning prediction models |
| title_full | An investigation into unifying early warning prediction models |
| title_fullStr | An investigation into unifying early warning prediction models |
| title_full_unstemmed | An investigation into unifying early warning prediction models |
| title_short | An investigation into unifying early warning prediction models |
| title_sort | investigation into unifying early warning prediction models |
| topic | Commerce |
| url | http://hdl.handle.net/11427/39447 |
| work_keys_str_mv | AT grievejason aninvestigationintounifyingearlywarningpredictionmodels AT grievejason investigationintounifyingearlywarningpredictionmodels |