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.

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Jan 4th, 12:00 AM Jan 7th, 12:00 AM

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.

http://aisel.aisnet.org/hicss-50/da/business_intelligence_case_studies/4