The design considerations and development of a simulator for the backtesting of investment strategies

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dc.contributor.advisorMarsden, Garyen_ZA
dc.contributor.authorGounden, Kevinen_ZA
dc.date.accessioned2014-12-30T06:52:36Z
dc.date.available2014-12-30T06:52:36Z
dc.date.issued2011en_ZA
dc.description.abstractThe skill of accurately predicting the optimal time to buy or sell shares on the stock market is one that has been actively sought by both experienced and novice investors since the advent of the stock exchange in the early 1930s. Since then, the finance industry has employed a plethora of techniques to improve the prediction power of the investor. This thesis is an investigation into one of those techniques and the advancement of this technique through the use of computational power. The technique of portfolio strategy backtesting as a vehicle to achieve improved predictive power is one that has existed within financial services for decades. Portfolio backtesting, as alluded to by its name, is the empirical testing of an investment strategy to determine how the strategy would have performed historically, with a view that past performance may be indicative of future performance.en_ZA
dc.identifier.apacitationGounden, K. (2011). <i>The design considerations and development of a simulator for the backtesting of investment strategies</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/10569en_ZA
dc.identifier.chicagocitationGounden, Kevin. <i>"The design considerations and development of a simulator for the backtesting of investment strategies."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2011. http://hdl.handle.net/11427/10569en_ZA
dc.identifier.citationGounden, K. 2011. The design considerations and development of a simulator for the backtesting of investment strategies. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Gounden, Kevin AB - The skill of accurately predicting the optimal time to buy or sell shares on the stock market is one that has been actively sought by both experienced and novice investors since the advent of the stock exchange in the early 1930s. Since then, the finance industry has employed a plethora of techniques to improve the prediction power of the investor. This thesis is an investigation into one of those techniques and the advancement of this technique through the use of computational power. The technique of portfolio strategy backtesting as a vehicle to achieve improved predictive power is one that has existed within financial services for decades. Portfolio backtesting, as alluded to by its name, is the empirical testing of an investment strategy to determine how the strategy would have performed historically, with a view that past performance may be indicative of future performance. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - The design considerations and development of a simulator for the backtesting of investment strategies TI - The design considerations and development of a simulator for the backtesting of investment strategies UR - http://hdl.handle.net/11427/10569 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/10569
dc.identifier.vancouvercitationGounden K. The design considerations and development of a simulator for the backtesting of investment strategies. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/10569en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherComputer Scienceen_ZA
dc.titleThe design considerations and development of a simulator for the backtesting of investment strategiesen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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