Combining News and Technical Indicators in Daily Stock Price Trends Prediction

Authors:
Yuzheng Zhai;Arthur Hsu;Saman K Halgamuge
Affiliations:
Dynamic System and Control Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, 3010, Australia;Dynamic System and Control Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, 3010, Australia;Dynamic System and Control Group, Department of Mechanical and Manufacturing Engineering, University of Melbourne, Victoria, 3010, Australia
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

Stock market prediction has always been one of the hottest topics in research, as well as a great challenge due to its complex and volatile nature. However, most of the existing methods neglect the impact from mass media that will greatly affect the behavior of investors. In this paper we present a system that combines the information from both related news releases and technical indicators to enhance the predictability of the daily stock price trends. The performance shows that this system can achieve higher accuracy and return than a single source system.