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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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Abstract [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.
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Received: 06 August 2018
Published: 03 July 2019
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