{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/31119"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/31119","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Comparison of sovereign risk and its determinants","abstract":"This paper aims to measure, compare and model Sovereign Risk. The risk position of South Africa compared to Emerging Markets as well as in comparison to Developed Markets is considered. Particular interest is taken in how the South African Sovereign Risk environment, and its associated determinants, differs and conforms to that of other Emerging Markets. This effectively highlights how the South African economy is similar to the Emerging Markets and where it behaves differently. Regression, optimisation techniques, dimension reduction techniques as well as Machine Learning techniques, through the use of sentiment analysis, is utilised in this research.","abstract_html":"This paper aims to measure, compare and model Sovereign Risk. The risk position of South Africa compared to Emerging Markets as well as in comparison to Developed Markets is considered. Particular interest is taken in how the South African Sovereign Risk environment, and its associated determinants, differs and conforms to that of other Emerging Markets. This effectively highlights how the South African economy is similar to the Emerging Markets and where it behaves differently. Regression, optimisation techniques, dimension reduction techniques as well as Machine Learning techniques, through the use of sentiment analysis, is utilised in this research.","abstract_has_math":false,"creators":["Smith, Anri"],"institution":"Department of Statistical Sciences","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Barr, Graham"],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019","date_published":"2019","updated_at":"2026-07-22T22:23:35Z","subjects":["sovereign risk","emerging markets","developed markets","machine learning","sentiment analysis"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/31119","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Barr, Graham"]},{"key":"dc:creator","label":"Author","values":["Smith, Anri"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2020-02-14T09:21:53Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2020-02-14T09:21:53Z"]},{"key":"dc:date.issued","label":"Date","values":["2019"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Statistical Sciences"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["sovereign risk","emerging markets","developed markets","machine learning","sentiment analysis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/31119"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This paper aims to measure, compare and model Sovereign Risk. The risk position of South Africa compared to Emerging Markets as well as in comparison to Developed Markets is considered. Particular interest is taken in how the South African Sovereign Risk environment, and its associated determinants, differs and conforms to that of other Emerging Markets. This effectively highlights how the South African economy is similar to the Emerging Markets and where it behaves differently. Regression, optimisation techniques, dimension reduction techniques as well as Machine Learning techniques, through the use of sentiment analysis, is utilised in this research."]},{"key":"dc:title","label":"Title","values":["Comparison of sovereign risk and its determinants"]}]}],"canonical_facts":{"dc:contributor.advisor":["Barr, Graham"],"dc:creator":["Smith, Anri"],"dc:date.accessioned":["2020-02-14T09:21:53Z"],"dc:date.available":["2020-02-14T09:21:53Z"],"dc:date.issued":["2019"],"dc:description.abstract":["This paper aims to measure, compare and model Sovereign Risk. The risk position of South Africa compared to Emerging Markets as well as in comparison to Developed Markets is considered. Particular interest is taken in how the South African Sovereign Risk environment, and its associated determinants, differs and conforms to that of other Emerging Markets. This effectively highlights how the South African economy is similar to the Emerging Markets and where it behaves differently. Regression, optimisation techniques, dimension reduction techniques as well as Machine Learning techniques, through the use of sentiment analysis, is utilised in this research."],"dc:identifier.uri":["http://hdl.handle.net/11427/31119"],"dc:publisher.department":["Department of Statistical Sciences"],"dc:subject":["sovereign risk","emerging markets","developed markets","machine learning","sentiment analysis"],"dc:title":["Comparison of sovereign risk and its determinants"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:35Z"}