Modern Advanced Analytics Platforms and Predictive Models for Stock Price Forecasting: IBM Watson Analytics Case

dc.contributor.author Faizullov, Ilias
dc.contributor.author Yablonsky, Sergey
dc.date.accessioned 2016-12-29T00:29:01Z
dc.date.available 2016-12-29T00:29:01Z
dc.date.issued 2017-01-04
dc.description.abstract The primary purpose of this paper was to provide an in-depth analysis of the ability of modern analytical platforms (using IBM Watson Analytics as an example) to generate predictive models for stock prices forecasting in comparison with traditional analytical econometric platforms and models. Series of stock predictive models based on the suggestions of IBM Watson Analytics have demonstrated results, which are superior to all other models. In terms of forecasting accuracy, they beat all models except for the Random Walk. The simulation has demonstrated high returns for most of the suggested models.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2017.128
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41281
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Advanced Analytics Platforms
dc.subject IBM Watson Analytics
dc.subject Predictive Models for Stock Price Forecasting
dc.title Modern Advanced Analytics Platforms and Predictive Models for Stock Price Forecasting: IBM Watson Analytics Case
dc.type Conference Paper
dc.type.dcmi Text
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