Forecasting stock price movements using neural networks

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dc.contributor.advisorGuo, Renkuanen_ZA
dc.contributor.authorRank, Christianen_ZA
dc.date.accessioned2014-07-30T17:44:18Z
dc.date.available2014-07-30T17:44:18Z
dc.date.issued2006en_ZA
dc.descriptionIncludes bibliographical references (p. 99-101).
dc.description.abstractThe prediction of security prices has shown to be one of the most important but most difficult tasks in financial operations. Linear approaches failed to model the non-linear behaviour of markets and non-linear approaches turned out to posses too many constraints. Neural networks seem to be a suitable method to overcome these problems since they provide algorithms which process large sets of data from a non-linear context and yield thorough results. The first problem addressed by this research paper is the applicability of neural networks with respect to markets as a tool for pattern recognition. It will be shown that markets posses the necessary requirements for the use of neural networks, i.e. markets show patterns which are exploitable.en_ZA
dc.identifier.apacitationRank, C. (2006). <i>Forecasting stock price movements using neural networks</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/4392en_ZA
dc.identifier.chicagocitationRank, Christian. <i>"Forecasting stock price movements using neural networks."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2006. http://hdl.handle.net/11427/4392en_ZA
dc.identifier.citationRank, C. 2006. Forecasting stock price movements using neural networks. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Rank, Christian AB - The prediction of security prices has shown to be one of the most important but most difficult tasks in financial operations. Linear approaches failed to model the non-linear behaviour of markets and non-linear approaches turned out to posses too many constraints. Neural networks seem to be a suitable method to overcome these problems since they provide algorithms which process large sets of data from a non-linear context and yield thorough results. The first problem addressed by this research paper is the applicability of neural networks with respect to markets as a tool for pattern recognition. It will be shown that markets posses the necessary requirements for the use of neural networks, i.e. markets show patterns which are exploitable. DA - 2006 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2006 T1 - Forecasting stock price movements using neural networks TI - Forecasting stock price movements using neural networks UR - http://hdl.handle.net/11427/4392 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/4392
dc.identifier.vancouvercitationRank C. Forecasting stock price movements using neural networks. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2006 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/4392en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherStatistical Sciencesen_ZA
dc.titleForecasting stock price movements using neural networksen_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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