The optimally diversified equity portfolio in South Africa: an artificial intelligence approach
| dc.contributor.author | Block, Aaron Eliyahu | |
| dc.date.accessioned | 2018-03-01T10:07:16Z | |
| dc.date.available | 2018-03-01T10:07:16Z | |
| dc.date.issued | 2017 | |
| dc.description | A thesis presented to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of Witwatersrand in fulfilment of the requirements for the degree of Master of Commerce (M.Com) in Business Finance, January 2017 | en_ZA |
| dc.description.abstract | Diversification has remained a central tenet in investment theory over multiple decades due to its demonstrated value as a risk mitigation technique. Increasing the number assets in a portfolio, where the magnitude of correlation is relatively slim, increases the amount of diversification while also encountering increased costs in the form of transaction costs, taxes and the like. Thus, it is imperative to solve for the optimal point of diversification to ensure an investor does not encounter unnecessary costs. This study aims to solve for the point of optimal diversification in an equity portfolio, focusing on the South African environment. This is achieved by employing a framework using both the traditional simulation method as well as more advanced mathematical techniques, namely: genetic programming and particle swarm optimisation. Marked improvements are realised in this study with regards to the methodology and results through the application of advanced mathematical approaches in addition to removing the restriction of equal weightings being applied to each share in the portfolio. The results revealed that an optimal portfolio can be constructed using up to only 15 shares. Secondly, the genetic programming approach demonstrated increased strength compared to the traditional simulation and particle swarm optimisation approaches, obtaining a greater level of diversification with fewer shares. Finally, although the aim of the study is focused on modelling the relationship between the number of shares in a portfolio and the achievable diversification benefits, it is also established that the portfolios indicated as being optimally diversified achieved market beating returns. | en_ZA |
| dc.description.librarian | XL2018 | en_ZA |
| dc.format.extent | Online resource (xiv, 198 leaves) | |
| dc.identifier.citation | Block, Aaron Eliyahu (2016) The optimally diversified equity portfolio in South Africa: an artificial intelligence approach, University of the Witwatersrand, Johannesburg, <https://hdl.handle.net/10539/24122> | |
| dc.identifier.uri | https://hdl.handle.net/10539/24122 | |
| dc.language.iso | en | en_ZA |
| dc.subject.lcsh | Portfolio management--South Africa | |
| dc.subject.lcsh | Investment analysis--South Africa | |
| dc.subject.lcsh | Finance--Mathematical models--Computer programs | |
| dc.subject.lcsh | Computer simulation | |
| dc.subject.lcsh | Simulation methods | |
| dc.title | The optimally diversified equity portfolio in South Africa: an artificial intelligence approach | en_ZA |
| dc.type | Thesis | en_ZA |