The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach
Joint Authors
Wang, Gaoshan
Yu, Guangjin
Shen, Xiaohong
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
With more and more investors exerting their voices through network forums or social media platforms, the relationships between online investor sentiment and stock movements have drawn more and more attention.
In this paper, we crawl stock comments from China’s most popular online stock forum, East Money (www.eastmoney.com), and then develop a sentiment classifier using the LSTM method.
Using the online investor sentiment of the stock forum, we explore the effect of online investor sentiment on the stock movements of CSI300.
The results show that online investor sentiment has a significant positive impact on both stock return and trading volume and remains significant after controlling book-to-market ratio, BETA, and market value.
Moreover, investor sentiment has a significant positive impact on order imbalance of big trade, which represents the main flow of money in the market.
As a result, investor sentiment has a positive impact on the major fund flows in the market.
In other words, an increase in investor sentiment can boost the major money flows in the market to some extent.
From a practical point of view, investor sentiment can assist investors to make investment decisions and help the government to regulate the stock market.
American Psychological Association (APA)
Wang, Gaoshan& Yu, Guangjin& Shen, Xiaohong. 2020. The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142070
Modern Language Association (MLA)
Wang, Gaoshan…[et al.]. The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142070
American Medical Association (AMA)
Wang, Gaoshan& Yu, Guangjin& Shen, Xiaohong. The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142070
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142070