The effect of investor sentiment on stock volatility is a highly attractive research question in both the academic field and the real financial industry.With the proposal of China’s"dual carbon"target,green...The effect of investor sentiment on stock volatility is a highly attractive research question in both the academic field and the real financial industry.With the proposal of China’s"dual carbon"target,green stocks have gradually become an essential branch of Chinese stock markets.Focusing on 106 stocks from the new energy,environmental protection,and carbon–neutral sectors,we construct two investor sentiment proxies using Internet text and stock trading data,respectively.The Internet sentiment is based on posts from Eastmoney Guba,and the trading sentiment comes from a variety of trading indicators.In addition,we divide the realized volatility into continuous and jump parts,and then investigate the effects of investor sentiment on different types of volatilities.Our empirical findings show that both sentiment indices impose significant positive impacts on realized,continuous,and jump volatilities,where trading sentiment is the main factor.We further explore the mediating effect of information asymmetry,measured by the volume-synchronized probability of informed trading(VPIN),on the path of investor sentiment affecting stock volatility.It is evidenced that investor sentiments are positively correlated with the VPIN,and they can affect volatilities through the VPIN.We then divide the total sample around the coronavirus disease 2019(COVID-19)pandemic.The empirical results reveal that the market volatility after the COVID-19 pandemic is more susceptible to investor sentiments,especially to Internet sentiment.Our study is of great significance for maintaining the stability of green stock markets and reducing market volatility.展开更多
描述一个网络舆情监控系统IPSMS(Internet public sentiment monitoring system)。该系统试图将网络新闻及论坛、BBS上的帖子依关键词搜索,并依"事件"聚类,让管理者通过阅读事件可以了解正在发生或已经发生的事件,并提供自动...描述一个网络舆情监控系统IPSMS(Internet public sentiment monitoring system)。该系统试图将网络新闻及论坛、BBS上的帖子依关键词搜索,并依"事件"聚类,让管理者通过阅读事件可以了解正在发生或已经发生的事件,并提供自动持续追踪事件发展的功能,以协助管理者快速完整且全面地了解事件全貌。系统由网页抓取器、网页解析器及跟踪检测系统三部分组成。由于网络舆情的特点是数据量巨大,为了提高效率,系统采用了网页清理技术,并且在话题跟踪过程中使用了k-d tree方法。最后,对系统的未来工作进行了展望。展开更多
基金supported by the National Natural Science Foundation of China(72171005),to which we are deeply grateful。
文摘The effect of investor sentiment on stock volatility is a highly attractive research question in both the academic field and the real financial industry.With the proposal of China’s"dual carbon"target,green stocks have gradually become an essential branch of Chinese stock markets.Focusing on 106 stocks from the new energy,environmental protection,and carbon–neutral sectors,we construct two investor sentiment proxies using Internet text and stock trading data,respectively.The Internet sentiment is based on posts from Eastmoney Guba,and the trading sentiment comes from a variety of trading indicators.In addition,we divide the realized volatility into continuous and jump parts,and then investigate the effects of investor sentiment on different types of volatilities.Our empirical findings show that both sentiment indices impose significant positive impacts on realized,continuous,and jump volatilities,where trading sentiment is the main factor.We further explore the mediating effect of information asymmetry,measured by the volume-synchronized probability of informed trading(VPIN),on the path of investor sentiment affecting stock volatility.It is evidenced that investor sentiments are positively correlated with the VPIN,and they can affect volatilities through the VPIN.We then divide the total sample around the coronavirus disease 2019(COVID-19)pandemic.The empirical results reveal that the market volatility after the COVID-19 pandemic is more susceptible to investor sentiments,especially to Internet sentiment.Our study is of great significance for maintaining the stability of green stock markets and reducing market volatility.
