ISBN: 978-981-14-4787-7 DOI: 10.18178/wcse.2020.06.001
Research on the Correlation between Hot News and Stock Index Volatility Based on Deep Learning
Abstract— With the development of technology, the representation of text semantics by computer is also improving day by day, and the application scope is more and more extensive. The correlation between news and market volatility has become one of the hot topics in recent years. Stock market fluctuation is affected by many factors, and news is an important channel of influence factors. In this paper, a neural network structure named 'BLA' is designed to study the correlation between daily hot news and DJIA fluctuations, to judge the rise and fall of the index of the day. Experiments show that the accuracy of the 'BLA' network in analyzing the fluctuations of hot news and stock market index is higher than that of the traditional network.
Index Terms— news, stock market index, neural network, attention
Yuting Zhang, Zhaogong Zhang
Heilongjiang University, CHINA
Cite: Yuting Zhang, Zhaogong Zhang, "Research on the Correlation between Hot News and Stock Index Volatility Based on Deep Learning" Proceedings of 2020 the 10th International Workshop on Computer Science and Engineering (WCSE 2020), pp. 1-5, Shanghai, China, 19-21 June, 2020.