dc.contributor.author | Dassanayake, Wajira | |
dc.date.accessioned | 2018-07-30T23:18:54Z | |
dc.date.available | 2018-07-30T23:18:54Z | |
dc.date.issued | 2017-10-05 | |
dc.identifier.uri | https://hdl.handle.net/10652/4333 | |
dc.description.abstract | My research intends to derive an intelligent multistep scalable hybrid model Integrating technical, fundamental and textual analyses. This dynamic multistep model would link the existing segregated models in the literature.
The literature survey reveals that the existing models formulate marginally segregated subsets in the area of stock market price prediction.
This research will be the first scientific exploration to combine the effects of historical factors, macroeconomic determinants and spontaneous events in a single multistep model to forecast the stock market prices. | en_NZ |
dc.language.iso | en | en_NZ |
dc.rights | All rights reserved | en_NZ |
dc.subject | stock markets | en_NZ |
dc.subject | stock movement prediction | en_NZ |
dc.subject | correlation analysis | en_NZ |
dc.subject | stock price analysis | en_NZ |
dc.title | A scalable multi-step hybrid model for stock index prediction | en_NZ |
dc.type | Conference Contribution - Oral Presentation | en_NZ |
dc.date.updated | 2018-04-27T14:30:02Z | |
dc.rights.holder | Author | en_NZ |
dc.subject.marsden | 1502 Other Banking, Finance and Investment | en_NZ |
dc.subject.marsden | 080109 Pattern Recognition and Data Mining | en_NZ |
dc.identifier.bibliographicCitation | Dassanayake, W. (2017, October). A scalable multi-step hybrid model for stock index prediction. Paper presented at the Unitec Research Symposium, 2017, Unitec Institute of Technology, New Zealand. | en_NZ |
unitec.publication.title | Unitec Research Symposium, 2017 | en_NZ |
unitec.conference.org | Unitec Institute of Technology | en_NZ |
unitec.conference.location | Unitec Institute of Technology, Auckland, New Zealand | en_NZ |
unitec.conference.sdate | 2017-10-05 | |
unitec.conference.edate | 2017-10-05 | |
unitec.peerreviewed | yes | en_NZ |
unitec.identifier.roms | 61318 | en_NZ |
unitec.institution.studyarea | Accounting and Finance | en_NZ |