E3S Web Conf.
Volume 214, 20202020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|Number of page(s)||5|
|Section||Machine Learning and Energy Industry Structure Forecast Analysis|
|Published online||07 December 2020|
- Huang Hong, Zhang Enhuan, and Sun Hongmei, “Will margin financing increase the impact of investor sentiment on stock index volatility?” China Soft Science, Vol. 3, pp. 151-161, 2016. [Google Scholar]
- Sun Kunpeng, and Xiao Xing, “The influence mechanism of internet social media on investor emotional contagion and stock price collapse risk, ” Technology and Economics, Vol. 37 (06), pp. 93-102, 2018. [Google Scholar]
- Shi Yong, Tang Jing, and Guo Kun, “The impact of social media investor attention and investor sentiment on China ‘s stock market, ”. Journal of Central University of Finance and Economics, Vol. 07, pp. 45, 2017. [Google Scholar]
- Dai Debao, and Lan Yusen, “Review on Investor Sentiment and Stock Price Research Based on Internet Text, ” Wuhan Finance, Vol. 01, pp. 41-45, January 2019. [Google Scholar]
- Zhao Ruwei, Xiong Xiong, and Shen Dehua, “Investor sentiment and stock price crash risk: empirical evidence from the Chinese market, ” Management Review, Vol. 31(03), pp. 50-60, 2019. [Google Scholar]
- Zhang Jihai, “The impact of investor sentiment on stock prices from the perspective of behavioral economics, ” Social Science Frontline, Vol. 12, pp. 235-239, 2019. [Google Scholar]
- Song Shunlin, and Wang Yanchao, “How does investor sentiment affect stock pricing? —— An empirical study based on IPO companies, ” Journal of Management Sciences, vol., 19 (05), pp. 41-55, 2016. [Google Scholar]
- Yang Tao, and Guo Mengmeng, “Investor Attention and Stock Market——Taking PM2. 5 Concept Stock as an Example, ” Financial Research, Vol. 05, pp. 190-206, 2019. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.