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The impact of news on the South African sovereign bond market

Thesis (PhD (Financial Management Sciences))--University of Pretoria, 2022.

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Other Authors: Brummer, L.M., 1940-
Format: Thesis
Language:English
Published: University of Pretoria 2023
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access_status_str Open Access
author2 Brummer, L.M., 1940-
author_browse Brummer, L.M., 1940-
author_facet Brummer, L.M., 1940-
collection Thesis
dc_rights_str_mv © 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.
description Thesis (PhD (Financial Management Sciences))--University of Pretoria, 2022.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:36:18.085Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/90028 The impact of news on the South African sovereign bond market Brummer, L.M., 1940- ann.vanderwesthuizen@up.ac.za Van Schalkwyk, Cornelis Hendrik Van der Westhuizen, Elizabeth-Ann Reverse event study Headline news News classification GARCH models Machine-learning South African sovereign bond yield curve UCTD Thesis (PhD (Financial Management Sciences))--University of Pretoria, 2022. A 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). Financial Management PhD (Financial Management Sciences) Unrestricted 2023-03-08T13:16:40Z 2023-03-08T13:16:40Z 2023 2022 Thesis * A2023 https://repository.up.ac.za/handle/2263/90028 https://doi.org/10.25403/UPresearchdata.21900771 en © 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. application/pdf University of Pretoria
spellingShingle Reverse event study
Headline news
News classification
GARCH models
Machine-learning
South African sovereign bond yield curve
UCTD
The impact of news on the South African sovereign bond market
title The impact of news on the South African sovereign bond market
title_full The impact of news on the South African sovereign bond market
title_fullStr The impact of news on the South African sovereign bond market
title_full_unstemmed The impact of news on the South African sovereign bond market
title_short The impact of news on the South African sovereign bond market
title_sort impact of news on the south african sovereign bond market
topic Reverse event study
Headline news
News classification
GARCH models
Machine-learning
South African sovereign bond yield curve
UCTD
url https://repository.up.ac.za/handle/2263/90028
https://doi.org/10.25403/UPresearchdata.21900771