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A contaminated generalized t model for cryptocurrency returns
Mini Dissertation (MSc Advanced Data Analytics))--University of Pretoria, 2025.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2025
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| _version_ | 1867613466319126528 |
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| access_status_str | Open Access |
| author2 | Bekker, Andriette, 1958- |
| author_browse | Bekker, Andriette, 1958- |
| author_facet | Bekker, Andriette, 1958- |
| 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 | Mini Dissertation (MSc Advanced Data Analytics))--University of Pretoria, 2025. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/100454 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:35.732Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| 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:2263/100454 A contaminated generalized t model for cryptocurrency returns Bekker, Andriette, 1958- thembinkosimanyeruke@gmail.com Ferreira, Johan Arashi, Mohammad Manyeruke, Thembinkosi Johannes UCTD Sustainable Development Goals (SDGs) Adjustable kurtosis Contaminated distribution Generalized elliptical family Highly peaked Heavy tailed Mini Dissertation (MSc Advanced Data Analytics))--University of Pretoria, 2025. In financial analytics, a key aim of currency data analysis is to determine the distribution of returns. Considering the extensive utilization of cryptocurrencies, it is essential to offer a highly flexible model for distributions with heavier tails to analyze bitcoin data. A recent study by Punzo and Bagnato (2021) demonstrated that cryptocurrency returns have traits of high peakedness, heavy tails, and large excess kurtosis. To improve control over tail behaviour in flexible models, we recommend employing the generalized elliptical family of distributions for cryptocurrency returns. We systematically construct this family of distributions, obtaining the Bernoulli-Laplace distribution from Punzo and Bagnato (2021) and the contaminated generalized t distribution as constituents of this family. Both distributions have heavy tails, pronounced peaks, and large adjustable kurtosis. Additionally, the suggested framework allows for the division of the real line into two regions: one containing typical points and the other containing atypical points. We illustrate the effectiveness of the suggested framework utilizing four cryptocurrencies: USDJ USD, Frax USD, Gnosis USD, and Ethereum USD, in comparison to alternative distributions frequently employed in financial literature. The findings demonstrated that the suggested framework surpasses the other evaluated distributions. Moreover, the contaminated generalized t distribution is optimal for data with significant excess kurtosis, whereas the Bernoulli-Laplace distribution is preferable for data with comparatively lower kurtosis, while still leptokurtic. Statomet FNB Broader Africa Statistics MSc (Advanced Data Analytics) Unrestricted Faculty of Natural and Agricultural Sciences SDG-01: No poverty SDG-02: Zero hunger SDG-08: Decent work and economic growth SDG-09: Industry, innovation and infrastructure 2025-02-03T19:09:54Z 2025-02-03T19:09:54Z 2025-05 2025-02 Mini Dissertation * A2025 http://hdl.handle.net/2263/100454 N/A 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 | UCTD Sustainable Development Goals (SDGs) Adjustable kurtosis Contaminated distribution Generalized elliptical family Highly peaked Heavy tailed A contaminated generalized t model for cryptocurrency returns |
| title | A contaminated generalized t model for cryptocurrency returns |
| title_full | A contaminated generalized t model for cryptocurrency returns |
| title_fullStr | A contaminated generalized t model for cryptocurrency returns |
| title_full_unstemmed | A contaminated generalized t model for cryptocurrency returns |
| title_short | A contaminated generalized t model for cryptocurrency returns |
| title_sort | contaminated generalized t model for cryptocurrency returns |
| topic | UCTD Sustainable Development Goals (SDGs) Adjustable kurtosis Contaminated distribution Generalized elliptical family Highly peaked Heavy tailed |
| url | http://hdl.handle.net/2263/100454 |