摘要
股票市场中的“过度交易”现象会增加市场波动,进而加剧市场风险。本文抓取了2019年1月1日至2021年11月30日沪深300指数与中证500指数成分股的东方财富股吧发帖文本数据,基于文本数据挖掘方式构建了1小时的社交媒体投资者高频情绪指标,深入探究了投资者情绪对我国A股市场日内过度交易行为的影响及其作用机制。研究发现:投资者情绪能显著地正向影响投资者日内过度交易行为,同时投资者情绪对机构投资者日内过度交易的影响强于个人投资者。进一步地,牛市中受投资者情绪影响产生的日内过度交易行为明显大于熊市;并且相较于中小盘股,投资者情绪对大盘股中个人投资者日内过度交易行为的影响程度更大。本文研究结论对投资者优化投资策略、引导监管机构机制设计、防范我国股票市场过度交易风险等具有较强的参考意义。
"Overtrading"in the stock market increases market volatility,which exacerbates market risk.This paper crawls the text data posted by the Eastmoney Stock Forum for the constituents of the CSI 300 Index and CSI 500 Index from January 1,2019 to November 30,2021.By using text data mining,this paper constructs one-hour high-frequency sentiment indicator of social media investors,and explores the impact of investor sentiment on intraday overtrading behavior in China's A-share market and its mechanism.The results show that investor sentiment can significantly positively affect investors'intraday overtrading behavior,and has a stronger impact on institutional investors'intraday overtrading than individual investors.Further,intraday overtrading behavior affected by investor sentiment in bull markets is significantly greater than in bear markets.And investor sentiment has a greater impact on intraday overtrading behavior in large-cap stocks than in small-and mid-cap stocks.The research conclusions of this paper have strong reference significance for investors to optimize investment strategies,guide the design of regulatory mechanisms,and prevent overtrading risks in China's stock market.
出处
《浙江金融》
2023年第9期64-73,26,共11页
Zhejiang Finance
关键词
投资者高频情绪
过度交易
股票市场
日内效应
文本挖掘
High-frequency Investor Sentiment
Overtrading
Stock Market
Intraday Effects
Text Mining
