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  1. University of Computer Studies, Yangon
  2. Conferences

Big Data Analytics for Price Prediction

http://hdl.handle.net/20.500.12678/0000004074
http://hdl.handle.net/20.500.12678/0000004074
329e6ae3-afd5-450a-baf5-3ebe734b8bb8
34306115-7a08-4526-83be-5f84378745e8
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20161.pdf 20161.pdf (98 Kb)
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Article
Upload type
Publication
Title
Title Big Data Analytics for Price Prediction
Language en
Publication date 2016-02-25
Authors
Khine, Kyi Lai Lai
Nyunt, Thi Thi Soe
Description
Big Data Predictive Analytics isinfluenced in the financial market mainly instock exchange with its emergingtechnologies. Stock Market Prediction hasalways been one of the hottest topics inresearch, as well as a great challenge due toits complex and volatile nature. Stock orshare prices are considered to be verydynamic and quick changes because of theunderlying nature of financial domain.Therefore, there is a critical need inprediction approaches to be effective andefficient utilization of large amount ofmarket data (Big Data) to analyze futureprediction in stock price movement. In thispaper, a hybrid prediction model isproposed for predicting daily basis stockprice changes or movements. It is based onthe combination of historical stock pricedata and text mining techniques which takethe textual contents of Financial NewsWebsites that have highly impacts on pricemovement.
Keywords
Big Data, predictive analytics, prediction model, stock price movement
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/178
Journal articles
Fourteenth International Conference On Computer Applications (ICCA 2016)
Conference papers
Books/reports/chapters
Thesis/dissertations
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