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Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange
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_ | 1867613635860234240 |
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| access_status_str | Open Access |
| author2 | Mare, Eben |
| author_browse | Mare, Eben |
| author_facet | Mare, Eben |
| 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 | Dissertation (MSc (Financial Engineering))--University of Pretoria, 2023. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/90133 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:39:17.410Z |
| 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:2263/90133 Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange Mare, Eben yashin.gopi@gmail.com Gopi, Yashin UCTD Minimal Spanning Tree (MST) Planar Maximally Filtered Graph (PMFG) Directed Bubble Hierarchical Tree (DBHT) Network Filter Johannesburg Stock Exchange Econophysics Correlation-based Network Network Topology Measures Dissertation (MSc (Financial Engineering))--University of Pretoria, 2023. Researchers from the field of econophysics have favoured the idea that financial markets are a complex adaptive system, consisting of entities that behave and interact in a diverse manner, leading to non-linear, emergent behaviour of the system. In the last twenty years, there has been an increasing focus on modelling complex adaptive systems using network theory. Correlation-based networks, where stocks are represented as entities in the network, and the relationships amongst the stocks are based on the strength of the co-movements of the stocks, have been widely studied. Network filtering tools, such as the Minimal Spanning Tree (MST), and the Planar Maximally Filtered Graph (PMFG), have been useful to attenuate the impact of noise in these networks, thereby allowing important macroscopic and mesoscopic structures to emerge. One of the main benefits of the PMFG is that it is accompanied by a hierarchical clustering algorithm called the Directed Bubble Hierarchical Tree (DBHT). This method has the benefit of being fully unsupervised in that it does not require the user to decide a priori on the number of clusters that the data should be split into. These techniques have been applied here to analyse the complex interactions amongst stocks on the Johannesburg Stock Exchange. A structure emerged in which shares from similar ICB sectors tended to cluster together. However, the so-called Rand Hedge shares, and shares which exhibited low liquidity, tended to override the sector effect and clustered together. From a dynamic perspective, the MST and PMFG seemed to shrink during market crashes, while the Basic Materials sector was typically the most important or central sector over time. Over the long-term, the DBHT divided the stocks in the South African stock market into six clusters. This technique was compared to other popular hierarchical clustering algorithms, and the amount of economic information that each method extracted was quantified. The most recent PMFG and DBHT showed a changed structure as compared to the long-term data, highlighting that the way that market participants view South African shares can change over time. Mathematics and Applied Mathematics MSc (Financial Engineering) Unrestricted 2023-03-16T09:27:07Z 2023-03-16T09:27:07Z 2023-04 2023 Dissertation * S2023 http://hdl.handle.net/2263/90133 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 | UCTD Minimal Spanning Tree (MST) Planar Maximally Filtered Graph (PMFG) Directed Bubble Hierarchical Tree (DBHT) Network Filter Johannesburg Stock Exchange Econophysics Correlation-based Network Network Topology Measures Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title | Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title_full | Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title_fullStr | Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title_full_unstemmed | Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title_short | Application of network filtering techniques in finding hidden structures on the Johannesburg Stock Exchange |
| title_sort | application of network filtering techniques in finding hidden structures on the johannesburg stock exchange |
| topic | UCTD Minimal Spanning Tree (MST) Planar Maximally Filtered Graph (PMFG) Directed Bubble Hierarchical Tree (DBHT) Network Filter Johannesburg Stock Exchange Econophysics Correlation-based Network Network Topology Measures |
| url | http://hdl.handle.net/2263/90133 |