Research on the prediction of investor sentiment on stock market volatility

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	Research on the prediction of investor sentiment on stock market volatility
	Feng, WenFang; Jia, ShiLiang
	2022
会议名称	2022 7th International Conference on Electronic Technology and Information Science, ICETIS 2022
会议录名称	ICETIS 2022 - 7th International Conference on Electronic Technology and Information Science
页码	573-576
会议日期	January 21, 2022 - January 23, 2022
会议地点	Harbin, China
出版者	VDE VERLAG GMBH
摘要	The application of deep learning model in the financial field has attracted the attention of many researchers in recent years. This paper uses Bi-directional Long Short-Term Memory Neural Network model to study the relationship between investor sentiment and Volatility Prediction of Shanghai Stock Exchange index. The results show that during the sample observation period, there is a significant negative correlation between investor sentiment and stock market volatility, and investor sentiment can effectively predict the stock market volatility trend. These findings show that investor sentiment is closely related to the performance of the stock market, and investor sentiment has a significant impact on the stock market. © VDE VERLAG GMBH Berlin Offenbach.
关键词	Commerce Deep learning Forecasting Investments Bi-directional Investor's sentiments Learning models Negative correlation Neural network model Observation Period Performance Shanghai stock exchanges Stock market volatility
收录类别	EI
语种	英语
EI入藏号	20223612685676
EI主题词	Financial markets
EI分类号	461.4 Ergonomics and Human Factors Engineering
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/160664
专题	经济管理学院
作者单位	Lanzhou University of Technology, School of economics and management, LanZhou, China
第一作者单位	经济管理学院
推荐引用方式 GB/T 7714	Feng, WenFang,Jia, ShiLiang. Research on the prediction of investor sentiment on stock market volatility[C]:VDE VERLAG GMBH,2022:573-576.