摘要
【目的】对财经新闻进行分类,探讨不同类型财经新闻与股市之间的关系。【方法】运用Word2Vec+k-Means方法对新闻文本进行聚类,并运用VAR模型从时间维度分析不同类别新闻如何影响股市以及股市的变动如何反作用于新闻。【结果】不同类别下的新闻情绪效应与信息效应能够显著影响股市成交量、振幅与收益,但对股市影响侧重不同;股市收益率与成交量分别反作用于新闻情感分歧与新闻长度,但依旧受新闻类别的影响。【局限】从股市整体角度分析股市与新闻之间的关系,而未考虑个股间差异。【结论】新闻与股市之间存在相互影响机制,且存在时间滞后效应;新闻类别是二者相互影响的关键变量。
[Objective] This paper explores the impacts of financial news on the stock market fluctuations.[Methods] We used the method of"Word2 Vec+k-means"to cluster news texts, and utilized VAR model to analyze the relationship between different types of news and the stock market performance. [Results] The sentiments and information of news significantly affect the trading volumes, amplitudes and returns of the stock market. Meanwhile, the fluctuations of stock market also influenced the emotion and length of the news reports.[Limitations] We did not analyze the relationship between the individual stock and news reports. [Conclusions]There are interactions and time-lag effects between news and stock market, while the news category is a key player.
作者
吕华揆
刘政昊
钱宇星
洪旭东
Lv Huakui;Liu Zhenghao;Qian Yuxing;Hong Xudong(Center for Studies of Information Resources,Wuhan University,Wuhan 430072,China;Big Data Institute,Wuhan University,Wuhan 430072,China;Institute of Finance and Economics,Shanghai University of Finance and Economics,Shanghai 200433,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2021年第1期99-111,共13页
Data Analysis and Knowledge Discovery
基金
国家自然科学基金重大研究计划(项目编号:91646206)的研究成果之一。
