Location
Hilton Waikoloa Village, Hawaii
Event Website
http://www.hicss.hawaii.edu
Start Date
1-4-2017
End Date
1-7-2017
Description
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.
Modern Advanced Analytics Platforms and Predictive Models for Stock Price Forecasting: IBM Watson Analytics Case
Hilton Waikoloa Village, Hawaii
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.
https://aisel.aisnet.org/hicss-50/da/business_intelligence_case_studies/4