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The detection of phase transitions in the South African market
This dissertation details the performance of two specific trading strategies which are based on the Johansen-Ledoit-Sornette (JLS) model. Both positive and negative bubbles are modelled as a log-periodic power law (LPPL) ending in a finite time singularity. The stock prices of the constituents of th...
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| Format: | Thesis |
| Language: | English |
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Division of Actuarial Science
2016
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| _version_ | 1867613343105155072 |
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| access_status_str | Open Access |
| author | Van Gysen, Michael |
| author2 | Mahomed, Obeid |
| author_browse | Mahomed, Obeid Van Gysen, Michael |
| author_facet | Mahomed, Obeid Van Gysen, Michael |
| author_sort | Van Gysen, Michael |
| collection | Thesis |
| description | This dissertation details the performance of two specific trading strategies which are based on the Johansen-Ledoit-Sornette (JLS) model. Both positive and negative bubbles are modelled as a log-periodic power law (LPPL) ending in a finite time singularity. The stock prices of the constituents of the FTSE/JSE Top40 index are taken as inputs to the JLS model from 3 June 2003 to 31 August 2015. It is shown that for certain time horizons into the past, the JLS based trading strategies significantly outperform random trading strategies. However this result is highly dependent on how far the model looks into the past, and if the model is calibrating to positive or negative bubbles. The lack of research with regards to the "stylized facts" of the JLS model, specifically relating to the time horizon and type of bubble, poses a significant hurdle in correctly identifying a LPPL structure in stock prices. These core features of the JLS model were developed from a number of positive bubbles that built up over many years. The results suggest that these features may not apply over all time horizons, and for both types of bubbles. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20483 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:38.153Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Division of Actuarial Science |
| publisherStr | Division of Actuarial Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/20483 The detection of phase transitions in the South African market Van Gysen, Michael Mahomed, Obeid Bosman, Petrus Mathematical Finance This dissertation details the performance of two specific trading strategies which are based on the Johansen-Ledoit-Sornette (JLS) model. Both positive and negative bubbles are modelled as a log-periodic power law (LPPL) ending in a finite time singularity. The stock prices of the constituents of the FTSE/JSE Top40 index are taken as inputs to the JLS model from 3 June 2003 to 31 August 2015. It is shown that for certain time horizons into the past, the JLS based trading strategies significantly outperform random trading strategies. However this result is highly dependent on how far the model looks into the past, and if the model is calibrating to positive or negative bubbles. The lack of research with regards to the "stylized facts" of the JLS model, specifically relating to the time horizon and type of bubble, poses a significant hurdle in correctly identifying a LPPL structure in stock prices. These core features of the JLS model were developed from a number of positive bubbles that built up over many years. The results suggest that these features may not apply over all time horizons, and for both types of bubbles. 2016-07-20T06:56:46Z 2016-07-20T06:56:46Z 2016 Master Thesis Masters MPhil http://hdl.handle.net/11427/20483 eng application/pdf Division of Actuarial Science Faculty of Commerce University of Cape Town |
| spellingShingle | Mathematical Finance Van Gysen, Michael The detection of phase transitions in the South African market |
| thesis_degree_str | Master's |
| title | The detection of phase transitions in the South African market |
| title_full | The detection of phase transitions in the South African market |
| title_fullStr | The detection of phase transitions in the South African market |
| title_full_unstemmed | The detection of phase transitions in the South African market |
| title_short | The detection of phase transitions in the South African market |
| title_sort | detection of phase transitions in the south african market |
| topic | Mathematical Finance |
| url | http://hdl.handle.net/11427/20483 |
| work_keys_str_mv | AT vangysenmichael thedetectionofphasetransitionsinthesouthafricanmarket AT vangysenmichael detectionofphasetransitionsinthesouthafricanmarket |