The impact of news on the South African sovereign bond market

dc.contributor.advisorBrummer, L.M., 1940-
dc.contributor.coadvisorVan Schalkwyk, Cornelis Hendrik
dc.contributor.emailann.vanderwesthuizen@up.ac.zaen_US
dc.contributor.postgraduateVan der Westhuizen, Elizabeth-Ann
dc.date.accessioned2023-03-08T13:16:40Z
dc.date.available2023-03-08T13:16:40Z
dc.date.created2023
dc.date.issued2022
dc.descriptionThesis (PhD (Financial Management Sciences))--University of Pretoria, 2022.en_US
dc.description.abstractA reverse event study approach is used to investigate how the South African sovereign bond yield curve react to headline news. Abnormal return dates in the zero-coupon yields are identified using GARCH models on the daily return series and news items that are classified into categories using supervised machine learning. A regression model is fitted to determine the link between the abnormal daily returns and news categories. The results indicate that for abnormal increases in returns, indicating an increase in yield (negative news) the entire yield curve was impacted by political news and the medium term (5-year) was also impacted by international news. For abnormal decreases in returns, indicating a decrease in yields (positive news) political news had the greatest impact on the long end (15-and 20-year) of the yield curve, and economic news had the greatest impact on the medium term (10-year).en_US
dc.description.availabilityUnrestricteden_US
dc.description.degreePhD (Financial Management Sciences)en_US
dc.description.departmentFinancial Managementen_US
dc.identifier.citation*en_US
dc.identifier.doihttps://doi.org/10.25403/UPresearchdata.21900771en_US
dc.identifier.otherA2023
dc.identifier.urihttps://repository.up.ac.za/handle/2263/90028
dc.language.isoenen_US
dc.publisherUniversity of Pretoria
dc.rights© 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subjectReverse event studyen_US
dc.subjectHeadline news
dc.subjectNews classification
dc.subjectGARCH models
dc.subjectMachine-learning
dc.subjectSouth African sovereign bond yield curve
dc.subjectUCTD
dc.titleThe impact of news on the South African sovereign bond marketen_US
dc.typeThesisen_US

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