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Interaction effects within factor investing in a South African context
The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, valu...
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| Format: | Thesis |
| Language: | English |
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Division of Actuarial Science
2017
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| _version_ | 1867613297857003520 |
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| access_status_str | Open Access |
| author | Varejes, Luc |
| author2 | Mohamed, Obeid |
| author_browse | Mohamed, Obeid Varejes, Luc |
| author_facet | Mohamed, Obeid Varejes, Luc |
| author_sort | Varejes, Luc |
| collection | Thesis |
| description | The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, value, low volatility and momentum and determines which factors have the largest impact on portfolio return. In addition to testing these single factor portfolios, the various interaction effects between the individual factors are investigated. This framework is divided into two parts. The first, is an empirical study on the JSE Top 100 over the 15 year period beginning September 2001 and ending September 2016. Quarterly and monthly rebalancing as well as transaction costs of 100 basis points (per trade) have been employed to mimic realistic investment management. Much of the framework used to incorporate these factors is adapted from Bender and Wang (2016) who tested these interactions on the S&P 500. The second, involves the construction of a controlled market model in an attempt to provide mathematical justification to the framework. The controlled model simulates stock price paths, in a Mil'shtein (1974) fashion, using Geometric Brownian Motion with a stochastic alpha component added to the drift. Factors are simulated randomly using correlated uniform distributions. The controlled model uses realistic market parameters and constructs the factor portfolio in the same manner as the empirical study. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/25531 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:54.099Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| 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:11427/25531 Interaction effects within factor investing in a South African context Varejes, Luc Mohamed, Obeid Mathematical Finance The notion of portfolio tilting towards fundamental factors has been the subject of many empirical studies over the last few decades. With this being said, there is limited literature on the interaction effects between these individual factors. This dissertation focuses specifically on quality, value, low volatility and momentum and determines which factors have the largest impact on portfolio return. In addition to testing these single factor portfolios, the various interaction effects between the individual factors are investigated. This framework is divided into two parts. The first, is an empirical study on the JSE Top 100 over the 15 year period beginning September 2001 and ending September 2016. Quarterly and monthly rebalancing as well as transaction costs of 100 basis points (per trade) have been employed to mimic realistic investment management. Much of the framework used to incorporate these factors is adapted from Bender and Wang (2016) who tested these interactions on the S&P 500. The second, involves the construction of a controlled market model in an attempt to provide mathematical justification to the framework. The controlled model simulates stock price paths, in a Mil'shtein (1974) fashion, using Geometric Brownian Motion with a stochastic alpha component added to the drift. Factors are simulated randomly using correlated uniform distributions. The controlled model uses realistic market parameters and constructs the factor portfolio in the same manner as the empirical study. 2017-10-04T14:27:42Z 2017-10-04T14:27:42Z 2017 Master Thesis Masters MPhil http://hdl.handle.net/11427/25531 eng application/pdf Division of Actuarial Science Faculty of Commerce University of Cape Town |
| spellingShingle | Mathematical Finance Varejes, Luc Interaction effects within factor investing in a South African context |
| thesis_degree_str | Master's |
| title | Interaction effects within factor investing in a South African context |
| title_full | Interaction effects within factor investing in a South African context |
| title_fullStr | Interaction effects within factor investing in a South African context |
| title_full_unstemmed | Interaction effects within factor investing in a South African context |
| title_short | Interaction effects within factor investing in a South African context |
| title_sort | interaction effects within factor investing in a south african context |
| topic | Mathematical Finance |
| url | http://hdl.handle.net/11427/25531 |
| work_keys_str_mv | AT varejesluc interactioneffectswithinfactorinvestinginasouthafricancontext |