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作 者:周颖刚[1,2] 唐诚蔚 林哲晖 ZHOU Yinggang;TANG Chengwei;LIN Zhehui(School of Economics,Xiamen University,Xiamen 361005,China;Wang Yanan Institute for Studies in Economics,Xiamen University,Xiamen 361005,China;Paula and Gregory Chow Institute for Studies in Economics,Xiamen University,Xiamen 361005,China;Corporate Finance Department,Xiamen International Bank Head Office,Xiamen 361005,China)
机构地区:[1]厦门大学经济学院,厦门361005 [2]厦门大学王亚南经济研究院,厦门361005 [3]厦门大学邹至庄经济研究院,厦门361005 [4]厦门国际银行总行公司金融部,厦门361005
出 处:《计量经济学报》2024年第3期567-587,共21页China Journal of Econometrics
基 金:国家自然科学基金(71988101);国家社会科学基金重大项目(19ZDA060)。
摘 要:本文利用汤森路透市场心理指数(Thomson Reuters MarketPsych Indices)中个股层面的情绪数据和美国股票市场2010至2019年期间的交易数据,比较分析了新闻情绪和社交媒体情绪在日度和月度两个不同时间维度下对股票定价能力的差异.实证结果表明,社交媒体情绪在日度层面的表现要优于新闻情绪,而新闻情绪在月度层面对股票收益率的解释能力要强于社交媒体情绪.具体来说,在日度层面,本文构建了新闻情绪因子和社交媒体情绪因子,发现在Fama-French五因子模型下,社交媒体情绪因子有显著的超额收益,而新闻情绪因子不存在超额收益,并且社交媒体情绪因子能够解释大部分日度层面的市场异象,而新闻情绪因子无法解释日度层面的异象.格兰杰因果检验的结果表明社交媒体情绪因子的反应速度比新闻情绪因子快3至4个交易日,说明了社交媒体情绪因子领先于新闻情绪因子.在月度层面,本文发现新闻情绪因子对异象的解释能力有所改善,而社交媒体情绪因子对异象的解释能力大幅下降.此外,对于波动率异象和特质波动率异象来说,月度新闻情绪因子有较为显著的解释能力,而月度社交媒体情绪因子的解释能力不显著.This paper compares and analyzes the differences in stock pricing between news sentiment and social media sentiment in two different time dimensions,daily and monthly,using individual sentiment data from the Thomson Reuters MarketPsych Indices and trading data from the US stock market from 2010 to 2019.The empirical results indicate that social media sentiment performs better at the daily level than news sentiment,and news sentiment has a stronger explanatory power on stock returns at the monthly level than social media sentiment.Specifically,at the daily level,this paper constructs news sentiment factor and social media sentiment factor,and finds that social media sentiment factor still exhibits significant excess returns under the Fama-French five-factor model,while news sentiment factor no longer exhibits excess returns.In addition,social media sentiment factor can explain most market anomalies at the daily level,while news sentiment factor cannot.In order to investigate the reasons,this paper conducts a Granger causality test,indicating that the response speed of social media sentiment factor is 3 to 4 trading days faster than that of news sentiment factor.At the monthly level,this paper finds that news sentiment improves its ability to explain anomalies,while the explanatory power of social media decreases significantly.In addition,for volatility anomalies and idiosyncratic volatility anomalies,the monthly news sentiment factor has a significant explanatory power,while the explanatory power of the monthly social media sentiment factor is not significant.
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