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Exploring the decay parameter for the exponentially weighted moving average volatility methodology
Dissertation (MSc (Financial Engineering))--University of Pretoria, 2023.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2023
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| _version_ | 1867613632911638528 |
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| access_status_str | Open Access |
| author2 | Van Vuuren, Gary |
| author_browse | Van Vuuren, Gary |
| author_facet | Van Vuuren, Gary |
| collection | Thesis |
| dc_rights_str_mv | © 2023 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 | Dissertation (MSc (Financial Engineering))--University of Pretoria, 2023. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/92903 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:39:14.512Z |
| 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:2263/92903 Exploring the decay parameter for the exponentially weighted moving average volatility methodology Van Vuuren, Gary sibandasharmaine@gmail.com Sibanda, Sharmaine Fanuel Promise Moving averages Volatility Simple Moving Average Exponentially Weighted Moving Average Market Risk UCTD Lambda SDG-09: Industry, innovation and infrastructure Natural and agricultural sciences theses SDG-09 SDG-17: Partnerships for the goals Natural and agricultural sciences theses SDG-17 Dissertation (MSc (Financial Engineering))--University of Pretoria, 2023. Volatility estimation is a crucial task for financial institutions, as it affects various aspects of their operations, such as risk management, capital allocation, investment strategy and derivative valuation. However, the traditional method of using equally weighted moving averages to estimate volatility can be inaccurate and incorrectly used, especially in volatile market conditions. It yields financial losses for financial institutions in that the volatility estimates do not correctly reflect financial markets in real time. In this dissertation, we implement the exponentially weighted moving average model instead, which assigns more weight to recent data than older data. We explore how the choice of the decay factor λ influences the performance of the exponentially weighted moving average model in different market scenarios. The optimal value of λ varies depending on the market volatility. We therefore demonstrate that the model can provide more reliable and timely volatility estimates than the equally weighted moving average model. These are useful for different applications in financial, such as Value at Risk or Expected Shortfall. Mathematics and Applied Mathematics MSc (Financial Engineering) Unrestricted 2023-10-16T13:20:22Z 2023-10-16T13:20:22Z 2024-04 2023 Dissertation * A2024 http://hdl.handle.net/2263/92903 10.25403/UPresearchdata.24316501 en © 2023 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 | Moving averages Volatility Simple Moving Average Exponentially Weighted Moving Average Market Risk UCTD Lambda SDG-09: Industry, innovation and infrastructure Natural and agricultural sciences theses SDG-09 SDG-17: Partnerships for the goals Natural and agricultural sciences theses SDG-17 Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title | Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title_full | Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title_fullStr | Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title_full_unstemmed | Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title_short | Exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| title_sort | exploring the decay parameter for the exponentially weighted moving average volatility methodology |
| topic | Moving averages Volatility Simple Moving Average Exponentially Weighted Moving Average Market Risk UCTD Lambda SDG-09: Industry, innovation and infrastructure Natural and agricultural sciences theses SDG-09 SDG-17: Partnerships for the goals Natural and agricultural sciences theses SDG-17 |
| url | http://hdl.handle.net/2263/92903 |