{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/41666"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/41666","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Testing the accuracy of the emerging market scoring model for measuring and predicting financial distress for South African firms","abstract":"This study investigated the accuracy of the Emerging Market Scoring Model (EMS model) for measuring and predicting financial distress for South African firms. The EMS model was applied to a 62-firm sample composed of two independent groups of 31 firms each, known as the extender and non-extender groups, for the period ranging from the financial years ended 2017 to 2020. Firms in the extender group extended the release of their financial results for the financial year ended 2020, signalling possible financial distress. For comparison, these were matched with 31 firms that did not extend the release of their financial results for the financial year ended 2020. The accuracy with which the EMS model predicted the financial distress of the extender group firms over the period was tested, by categorising firms into a financial health zone known as the EM score. A t-test was conducted to test whether a statistically significant difference existed between the mean EM scores of the two sample groups. The Fisher's exact test was conducted to test for the existence of a statistically significant non-random relationship between the two sample groups and the EMS model's categorical outputs. The EMS model displayed low predictive accuracy over the period, largely attributed to the limitations of the study. The t-test found a statistically significant difference between the extender and non-extender sample groups' mean EM scores over the period, while the Fisher's exact test did not find a statistically significant relationship between the two sample groups and the EMS model's categorical outputs. The study's results were therefore inconclusive that the EMS model is an accurate measure and predictor of financial distress for South African firms, although the results were promising enough to warrant future research. The study seeks to fill a methodological gap by testing a model that has enjoyed limited usage in South Africa, with the potential to aid stakeholders in proactively identifying and improving the financial health of firms, thereby alleviating the societal costs of business failure.","abstract_html":"This study investigated the accuracy of the Emerging Market Scoring Model (EMS model) for measuring and predicting financial distress for South African firms. The EMS model was applied to a 62-firm sample composed of two independent groups of 31 firms each, known as the extender and non-extender groups, for the period ranging from the financial years ended 2017 to 2020. Firms in the extender group extended the release of their financial results for the financial year ended 2020, signalling possible financial distress. For comparison, these were matched with 31 firms that did not extend the release of their financial results for the financial year ended 2020. The accuracy with which the EMS model predicted the financial distress of the extender group firms over the period was tested, by categorising firms into a financial health zone known as the EM score. A t-test was conducted to test whether a statistically significant difference existed between the mean EM scores of the two sample groups. The Fisher's exact test was conducted to test for the existence of a statistically significant non-random relationship between the two sample groups and the EMS model's categorical outputs. The EMS model displayed low predictive accuracy over the period, largely attributed to the limitations of the study. The t-test found a statistically significant difference between the extender and non-extender sample groups' mean EM scores over the period, while the Fisher's exact test did not find a statistically significant relationship between the two sample groups and the EMS model's categorical outputs. The study's results were therefore inconclusive that the EMS model is an accurate measure and predictor of financial distress for South African firms, although the results were promising enough to warrant future research. The study seeks to fill a methodological gap by testing a model that has enjoyed limited usage in South Africa, with the potential to aid stakeholders in proactively identifying and improving the financial health of firms, thereby alleviating the societal costs of business failure.","abstract_has_math":false,"creators":["Cosmos, Jason"],"institution":"Department of Finance and Tax","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["de Jager, Phillip"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-22T22:23:13Z","subjects":["Altman Z-score","EMS model","financial distress","financial health","South Africa"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/41666","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["de Jager, Phillip"]},{"key":"dc:creator","label":"Author","values":["Cosmos, Jason"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-09-01T13:53:30Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-09-01T13:53:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Finance and Tax"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Thesis / Dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters","MCom"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Altman Z-score","EMS model","financial distress","financial health","South Africa"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/41666"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This study investigated the accuracy of the Emerging Market Scoring Model (EMS model) for measuring and predicting financial distress for South African firms. The EMS model was applied to a 62-firm sample composed of two independent groups of 31 firms each, known as the extender and non-extender groups, for the period ranging from the financial years ended 2017 to 2020. Firms in the extender group extended the release of their financial results for the financial year ended 2020, signalling possible financial distress. For comparison, these were matched with 31 firms that did not extend the release of their financial results for the financial year ended 2020. The accuracy with which the EMS model predicted the financial distress of the extender group firms over the period was tested, by categorising firms into a financial health zone known as the EM score. A t-test was conducted to test whether a statistically significant difference existed between the mean EM scores of the two sample groups. The Fisher's exact test was conducted to test for the existence of a statistically significant non-random relationship between the two sample groups and the EMS model's categorical outputs. The EMS model displayed low predictive accuracy over the period, largely attributed to the limitations of the study. The t-test found a statistically significant difference between the extender and non-extender sample groups' mean EM scores over the period, while the Fisher's exact test did not find a statistically significant relationship between the two sample groups and the EMS model's categorical outputs. The study's results were therefore inconclusive that the EMS model is an accurate measure and predictor of financial distress for South African firms, although the results were promising enough to warrant future research. The study seeks to fill a methodological gap by testing a model that has enjoyed limited usage in South Africa, with the potential to aid stakeholders in proactively identifying and improving the financial health of firms, thereby alleviating the societal costs of business failure."]},{"key":"dc:title","label":"Title","values":["Testing the accuracy of the emerging market scoring model for measuring and predicting financial distress for South African firms"]}]}],"canonical_facts":{"dc:contributor.advisor":["de Jager, Phillip"],"dc:creator":["Cosmos, Jason"],"dc:date.accessioned":["2025-09-01T13:53:30Z"],"dc:date.available":["2025-09-01T13:53:30Z"],"dc:date.issued":["2025"],"dc:description.abstract":["This study investigated the accuracy of the Emerging Market Scoring Model (EMS model) for measuring and predicting financial distress for South African firms. The EMS model was applied to a 62-firm sample composed of two independent groups of 31 firms each, known as the extender and non-extender groups, for the period ranging from the financial years ended 2017 to 2020. Firms in the extender group extended the release of their financial results for the financial year ended 2020, signalling possible financial distress. For comparison, these were matched with 31 firms that did not extend the release of their financial results for the financial year ended 2020. The accuracy with which the EMS model predicted the financial distress of the extender group firms over the period was tested, by categorising firms into a financial health zone known as the EM score. A t-test was conducted to test whether a statistically significant difference existed between the mean EM scores of the two sample groups. The Fisher's exact test was conducted to test for the existence of a statistically significant non-random relationship between the two sample groups and the EMS model's categorical outputs. The EMS model displayed low predictive accuracy over the period, largely attributed to the limitations of the study. The t-test found a statistically significant difference between the extender and non-extender sample groups' mean EM scores over the period, while the Fisher's exact test did not find a statistically significant relationship between the two sample groups and the EMS model's categorical outputs. The study's results were therefore inconclusive that the EMS model is an accurate measure and predictor of financial distress for South African firms, although the results were promising enough to warrant future research. The study seeks to fill a methodological gap by testing a model that has enjoyed limited usage in South Africa, with the potential to aid stakeholders in proactively identifying and improving the financial health of firms, thereby alleviating the societal costs of business failure."],"dc:identifier.uri":["http://hdl.handle.net/11427/41666"],"dc:language.iso":["en"],"dc:publisher.department":["Department of Finance and Tax"],"dc:publisher.institution":["University of Cape Town"],"dc:subject":["Altman Z-score","EMS model","financial distress","financial health","South Africa"],"dc:title":["Testing the accuracy of the emerging market scoring model for measuring and predicting financial distress for South African firms"],"dc:type":["Thesis / Dissertation"],"dc:type.qualificationlevel":["Masters","MCom"]},"updated_at":"2026-07-22T22:23:13Z"}