Show simple item record

dc.contributor.authorWang, Yanqi
dc.date.accessioned2016-08-16T20:20:20Z
dc.date.available2016-08-16T20:20:20Z
dc.identifier.urihttp://hdl.handle.net/10464/9792
dc.description.abstractThis thesis joins the debate on utilizing the Genetic Algorithm (GA) to discover profitable trading strategies by providing an out-of-sample test of GA-based trading strategies on the CSI 300 index. Our results suggest that, with trading costs taken into consideration, GA-based trading rules consistently beat the buy-and-hold strategy in daily trading of CSI 300 index. Besides, we open up the black box of the evolution process of the GA by testing the statistical significance of the GA-based profitable trading strategies through the Fama-MacBeth regressions. In addition, this study connects the literature on the regime switching with studies on the GA-based trading strategies to construct one regime-switching Genetic Algorithm (RSGA) model and makes a comparison between the GA-based and the RSGA-based trading strategies. The empirical results show that trading strategies generated from the RSGA model consistently outperform those obtained from the GA model.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectGAen_US
dc.subjecttrading strategyen_US
dc.subjectblack boxen_US
dc.subjectregime-switching GAen_US
dc.subjectoutperformanceen_US
dc.titleThe Application of the Genetic Algorithm in Promoting Stock Trading Performancesen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Managementen_US
dc.degree.levelMastersen_US
dc.contributor.departmentFaculty of Business Programsen_US
dc.degree.disciplineFaculty of Businessen_US
refterms.dateFOA2021-07-16T10:03:23Z


Files in this item

Thumbnail
Name:
Brock_Wang_Yanqi_2016.pdf
Size:
1.436Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record