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An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange
Includes bibliographical references.
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Department of Finance and Tax
2014
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| _version_ | 1867613341593108480 |
|---|---|
| access_status_str | Open Access |
| author | Tully, Robyn |
| author_browse | Tully, Robyn |
| author_facet | Tully, Robyn |
| author_sort | Tully, Robyn |
| collection | Thesis |
| description | Includes bibliographical references. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/8562 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:36.552Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Finance and Tax |
| publisherStr | Department of Finance and Tax |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/8562 An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange Tully, Robyn Mathematical Finance Includes bibliographical references. Cluster analysis is becoming an increasingly popular method in modern finance because of its ability to summarise large amounts of data and so help individual and institutional investors to make timeous and informed investment decisions. This is no less true for investors in smaller, emerging markets - such as the Johannesburg Stock Exchange - than it is for those in the larger global markets. This study examines the application of two clustering techniques to the Johannesburg Stock Exchange. First, the application of Salvador and Chan's (2003) L method stopping rule to a hierarchical clustering of time series return data was analysed as a method for determining the number of latent groups in the data set. Using Ward's method and the Euclidean distance function, this method appears to be able detect the correct number of clusters on the JSE. Second, the ability of three different clustering algorithms to generate consistent clusters and cluster members over time on the Johannesburg Stock Exchange was analysed. The variation of information was used to measure the consistency of cluster members through time. Hierarchical clustering using Ward's method and the Euclidean distance measure proved to produce the most consistent results, while the K-means algorithms generated the least consistent cluster members. 2014-10-17T10:12:53Z 2014-10-17T10:12:53Z 2014 Master Thesis Masters MPhil http://hdl.handle.net/11427/8562 eng application/pdf Department of Finance and Tax Faculty of Commerce University of Cape Town |
| spellingShingle | Mathematical Finance Tully, Robyn An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| thesis_degree_str | Master's |
| title | An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| title_full | An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| title_fullStr | An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| title_full_unstemmed | An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| title_short | An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange |
| title_sort | assessment of the application of cluster analysis techniques to the johannesburg stock exchange |
| topic | Mathematical Finance |
| url | http://hdl.handle.net/11427/8562 |
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