Show simple record

dc.contributor.authorDassanayake, Wajira
dc.contributor.authorJayawardena, Chandimal
dc.contributor.authorArdekani, Iman
dc.contributor.authorSharifzadeh, Hamid
dc.date.accessioned2019-03-08T00:11:50Z
dc.date.available2019-03-08T00:11:50Z
dc.date.issued2019-03-07
dc.identifier.issn2324-3635
dc.identifier.urihttps://hdl.handle.net/10652/4549
dc.description.abstractStock market prices are intrinsically dynamic, volatile, highly sensitive, nonparametric, nonlinear and chaotic in nature, as they are influenced by a myriad of interrelated factors. As such, stock market time series prediction is complex and challenging. Many researchers have been attempting to predict stock market price movements using various techniques and different methodological approaches. Recent literature confirms that hybrid models, integrating linear and non-linear functions or statistical and learning models, are better suited for training, prediction and generalisation performance of stock market prices. The purpose of this review is to investigate different techniques applied in stock market price prediction with special emphasis on hybrid models.en_NZ
dc.language.isoenen_NZ
dc.publisherUnitec ePressen_NZ
dc.rightsModels Applied in Stock Market Prediction: A Literature Survey by Wajira Dassanayake, Chandimal Jayawardena, Iman Ardekani and Hamid Sharifzadeh is licensed under a Creative Commons AttributionNonCommercial 4.0 International License.en_NZ
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 New Zealand*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/nz/*
dc.subjectstock marketsen_NZ
dc.subjectstock movementen_NZ
dc.subjectpredictionen_NZ
dc.subjectcorrelation analysisen_NZ
dc.subjectstock price analysisen_NZ
dc.subjectcomputer modelingen_NZ
dc.subjectliterature reviewsen_NZ
dc.titleModels applied in stock market prediction : a literature surveyen_NZ
dc.typeJournal Articleen_NZ
dc.rights.holderAuthorsen_NZ
dc.subject.marsden150299 Banking, Finance and Investment not elsewhere classifieden_NZ
dc.subject.marsden0802 Computation Theory and Mathematicsen_NZ
dc.identifier.bibliographicCitationDassanayake, W., Jayawardena, C., Ardekani. I., & Sharifzadeh, H. (2019). Models Applied in Stock Market Prediction: A Literature Survey. (Unitec ePress Occasional and Discussion Paper Series 2019/01). Unitec ePress. ISSN 2324-3635 Retrieved from http://www.unitec.ac.nz/epressen_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.spage1en_NZ
unitec.publication.lpage21en_NZ
unitec.publication.volume2019en_NZ
unitec.publication.issue1en_NZ
unitec.publication.titleUnitec ePress Occasional and Discussion Paper Seriesen_NZ
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
unitec.identifier.roms63139
unitec.identifier.roms63155
unitec.identifier.roms64433
unitec.identifier.roms64586
unitec.relation.epresshttps://www.unitec.ac.nz/epress/index.php/models-applied-in-stock-market-prediction-a-literature-survey/en_NZ
unitec.publication.placeMount Albert, Auckland, New Zealanden_NZ
unitec.institution.studyareaComputing


Files in this item

Thumbnail
Thumbnail

This item appears in

Show simple record

Attribution-NonCommercial-NoDerivs 3.0 New Zealand
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 New Zealand

© Unitec Institute of Technology, Private Bag 92025, Victoria Street West, Auckland 1142