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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (5): 11-18    DOI: 10.11925/infotech.2096-3467.2018.0871
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Predicting Stock Trends Based on News Events
Mengji Zhang(),Wanyu Du,Nan Zheng
School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, China
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[Objective] This paper tries to predict stock trends with the help of deep learning models, financial data and related news events. [Methods] First, we built a classification model for news events. Then, we used the recurrent neural networks to construct a forecasting model for stock trends based on news, capital flows and corporate financial reports. [Results] The prediction accuracy was improved by the proposed model (76.22% and 77.36% for the mining and pharmaceutical manufacturing industries). [Limitations] We did not examine the different impacts of news headlines and full-texts on stock market. We only chose news events from the past one year, which needs to be expanded. [Conclusions] News events could improve the accuracy of predicting stock trends.

Key wordsStock Trend Forecast      Deep Learning      Text Mining     
Received: 06 August 2018      Published: 03 July 2019

Cite this article:

Mengji Zhang,Wanyu Du,Nan Zheng. Predicting Stock Trends Based on News Events. Data Analysis and Knowledge Discovery, 2019, 3(5): 11-18.

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