异质性财经新闻与股市关系研究*

doi:10.11925/infotech.2096-3467.2020.0063

数据分析与知识发现

2021, Vol. 5

Issue (1): 99-111 https://doi.org/10.11925/infotech.2096-3467.2020.0063

研究论文｜

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异质性财经新闻与股市关系研究*

吕华揆^1,²(

),刘政昊^1,²,钱宇星¹,洪旭东³

¹武汉大学信息资源研究中心武汉 430072
²武汉大学大数据研究院武汉 430072
³上海财经大学财经研究所上海 200433

Relationship Between Financial News and Stock Market Fluctuations

Lv Huakui^1,²(

),Liu Zhenghao^1,²,Qian Yuxing¹,Hong Xudong³

¹Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China
²Big Data Institute, Wuhan University, Wuhan 430072, China
³Institute of Finance and Economics, Shanghai University of Finance and Economics,Shanghai 200433, China

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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。

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	吕华揆
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关键词 ：异质性新闻, VAR模型, 股票市场, 情感分析

Abstract：

[Objective] This paper explores the impacts of financial news on the stock market fluctuations.[Methods] We used the method of “Word2Vec+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.

Key words： Heterogeneous News VAR Model Stock Market Sentiment Analysis

收稿日期: 2020-01-19 出版日期: 2021-02-05

ZTFLH:

F832

基金资助:*本文系国家自然科学基金重大研究计划的研究成果之一项目编号(91646206)

通讯作者: 吕华揆 E-mail: lvhuakui@whu.edu.cn

引用本文:

吕华揆,刘政昊,钱宇星,洪旭东. 异质性财经新闻与股市关系研究*[J]. 数据分析与知识发现, 2021, 5(1): 99-111.
Lv Huakui,Liu Zhenghao,Qian Yuxing,Hong Xudong. Relationship Between Financial News and Stock Market Fluctuations. Data Analysis and Knowledge Discovery, 2021, 5(1): 99-111.

链接本文:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2020.0063 或 https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2021/V5/I1/99

Fig.1 研究框架

Table 1 三类新闻的定义

指标	公式	变量解释
收益率^[29]	$Retur n t = ln (Pric e t) - ln (Pric e t - 1)$	$Pric e t 为$ 沪深300在t时刻的收盘价 $; Pric e t - 1$ 为t时刻前一时刻的收盘价
成交量	$TradingVolum e t = ln (Round (Trading V t, - 2))$	$Trading V t$ 为t时刻的成交量;Round()函数表示对成交量取整
股市振幅	$Amplitud e t = Pric e t h - Pric e t l Pric e t l$	$Pric e t h$ 为t时刻沪深300的最高价 $; Pric e t l$ 为t时刻的最低价
新闻情感^[29]	$Sen t k = ln [1 + M k pos 1 + M k neg]$ $Sen t t = 1 j ∑ k = 1 j Sen t k$	$Sen t k$ 为每条新闻情感值 $; M k pos$ 为文本k中所含积极情感得分,即文本中所有积极情感句分值之和; $M k neg$ 为消极情感得分; $Sen t t$ 为t时刻的新闻情感值;j为t时刻的新闻数量
情感分歧^[30]	$SentS V t = 1 j ∑ k = 1 j (Sen t t, k - Sen t t) 2$	$Sen t t, k$ 为t时刻新闻k表达的情感; $Sen t t$ 为t时刻平均文本情感值
新闻数量^[31]	$NewsVolum e t = ln (1 + News V t)$	$News V t 为$ 当天的新闻数量
新闻长度^[32,33]	$NewsLengt h t = ln ∑ k = 1 j NewsLengt h k j$	$NewsLengt h k$ 为文本k所含字数

Table 2 指标定义

Table 3 三类新闻描述性统计

Fig.2 股市波动类新闻对股市的影响

Fig.3 股权及高管变动类新闻对股市的影响

Fig.4 战略及其他类新闻对股市的影响

Fig.5 股市对股市波动类新闻的影响

Fig.6 股市对股权及高管变动类新闻的影响

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