Please wait a minute...
Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (1): 99-111    DOI: 10.11925/infotech.2096-3467.2020.0063
Current Issue | Archive | Adv Search |
Relationship Between Financial News and Stock Market Fluctuations
Lv Huakui1,2(),Liu Zhenghao1,2,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
Download: PDF (5095 KB)   HTML ( 21 ) 
Export: BibTeX | EndNote (RIS)      
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     
Received: 19 January 2020      Published: 05 February 2021
ZTFLH:  F832  
Fund:The work is supported by the National Natural Science Foundation of China Grant No(91646206)
Corresponding Authors: Lv Huakui     E-mail: lvhuakui@whu.edu.cn
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Huakui Lv
Zhenghao Liu
Yuxing Qian
Xudong Hong

Cite this article:

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.

URL:

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

Research Framework
财经新闻类别 含义 举例
股市波动类 对个股涨跌情况或股市整体变动情况描述的新闻 3月15日,恒指开盘微跌0.03%,资讯科技板块走强,领涨恒生十一大行业板块。截至9:57,恒生资讯科技业指数涨幅扩大至0.78%,居行业涨幅榜首位,恒指由绿翻红,涨0.20%
股权及高管变动类 招商引资、并购重组等会导致公司股权情况发生变化以及公司董监高等人事重大变动的新闻 根据港交所最新权益披露资料显示,2018年12月14日,常茂生物(00954.HK)获董事长芮新生场内增持5.2万股,每股均价0.6838港元,涉资约3.56万港元
公司战略及其他类 公司在战略上的改变及国家政策变动等宏观新闻 全国政协委员、中国东方电气集团党组书记、董事长邹磊3月2日对中国证券报记者表示,东方电气正积极推进与民营企业开展混合所有制的合作,目前正与多家民营公司洽谈
Definition of Three Kinds of News
指标 公式 变量解释
收益率[29] Returnt=ln(Pricet)-ln(Pricet-1) Pricet为沪深300在t时刻的收盘价;Pricet-1为t时刻前一时刻的收盘价
成交量 TradingVolumet=ln (Round(TradingVt,-2)) TradingVt为t时刻的成交量;Round()函数表示对成交量取整
股市振幅 Amplitudet=Priceth-PricetlPricetl Priceth为t时刻沪深300的最高价;Pricetl为t时刻的最低价
新闻情感[29] Sentk=ln[1+Mkpos1+Mkneg]
Sentt=1j∑k=1jSentk		 Sentk为每条新闻情感值;Mkpos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;Mkneg为消极情感得分;Sentt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] SentSVt=1j∑k=1j(Sentt,k-Sentt)2 Sentt,k为t时刻新闻k表达的情感;Sentt为t时刻平均文本情感值
新闻数量[31] NewsVolumet=ln(1+NewsVt) NewsVt为当天的新闻数量
新闻长度[32,33] NewsLengtht=ln∑k=1jNewsLengthkj NewsLengthk为文本k所含字数
Index Definition
新闻类型 数据量 变量 平均值 最大值 最小值 标准差
股市波动类 198 615 Sent
SentSV
NewsVolume
NewsLength		 0.579
1.665
4.896
6.813		 1.865
3.538
6.553
7.833		 -0.586
0.239
0
5.694		 0.307
0.414
1.312
0.260
股权及高管变动类 256 493 Sent
SentSV
NewsVolume
NewsLength		 0.991
2.418
5.203
6.486		 2.374
5.196
6.917
7.869		 -0.082
0
0
5.313		 0.274
0.449
1.226
0.315
公司战略及其他类 318 294 Sent
SentSV
NewsVolume
NewsLength		 1.788
2.377
5.607
7.142		 2.567
4.316
6.815
7.777		 0.831
1.083
1.609
6.417		 0.234
0.311
0.912
0.158
Descriptive Statistics of Three Kinds of News
Influence of Stock Market Fluctuation News on Stock Market
Influence of Equity and Executive Change News on Stock Market
Influence of Strategy and Other News on Stock Market
Influence of Stock Market on Stock Market Fluctuation News
Influence of Stock Market on Equity and Executive Change News
[1] 中国证券登记结算有限责任公司. 投资者统计[DB/OL]. http://www.chinaclear.cn/zdjs/tjyb2/center_tjbg.shtml .
[1] (China Securities Depository and Clearing Corporation Limited. Investor Statistics[DB/OL]. http://www.chinaclear.cn/zdjs/tjyb2/center_tjbg.shtml
[2] 陈健, 曾世强 . 投资者情绪对股票价格波动的影响研究[J]. 价格理论与实践, 2018(7):99-102.
[2] ( Chen Jian, Zeng Shiqiang . Research on the Influence of Investor Sentiment on Stock Price Volatility, Price: Theory & Practice, 2018(7):99-102.)
[3] Deng S, Huang Z J, Sinha A P , et al. The Interaction Between Microblog Sentiment and Stock Return: An Empirical Examination[J]. MIS Quarterly, 2018,42(3):895-918.
[4] 杨继东 . 媒体影响了投资者行为吗?——基于文献的一个思考[J]. 金融研究, 2007(11):93-102.
[4] ( Yang Jidong . Does the Media Influence Investor Behavior? -A Reflection Based on Literature, Journal of Financial Research, 2007(11):93-102.)
[5] 倪浩 . 新闻信息对不同类型投资者行为的影响[D]. 天津:天津大学, 2017.
[5] ( Ni Hao . The Impact of News Information on the Behavior of Different Types of Investors[D]. Tianjin: Tianjin University, 2017.)
[6] Williams P, Aaker J L . Can Mixed Emotions Peacefully Coexist?[J]. Journal of Consumer Research, 2002,28(4):636-649.
doi: 10.1086/jcr.2002.28.issue-4
[7] 程萧潇 . 场景效应还是内容效应?——财经新闻、网络舆情对股市行情的实证检验[J]. 统计与信息论坛, 2019,34(7):69-75.
[7] ( Cheng Xiaoxiao . Contextual Effect or Content Effect? Empirical Test of Financial News and Online Public Opinion on Stock Market Quotation[J]. Statistics & Information Forum, 2019,34(7):69-75.)
[8] 尹海员 . 新闻媒体报道对投资者情绪影响效应研究——来自我国股票市场的经验证据[J]. 厦门大学学报(哲学社会科学版), 2016(2):92-101.
[8] ( Yin Haiyuan . A Study on Effect of Media Reports on Investor Sentiment: Evidence from China’s Stock Market[J]. Journal of Xiamen University (Arts & Social Sciences), 2016 ( 2):92-101.)
[9] 史峰 . 金融媒体新闻情绪及其对股市影响研究[D]. 北京:对外经济贸易大学, 2018.
[9] ( Shi Feng . Research on Financial News Sentiment and Its Impact on Stock Market[D]. Beijing: University of International Business and Economics, 2018.)
[10] Li Q, Wang J, Bao L. Media Tone, Bias, and Stock Price Crash Risk: Evidence from China[J]. Asia-Pacific Journal of Accounting & Economics, DOI: 10.1080/16081625. 2019.1654396.
[11] Chan W S . Stock Price Reaction to News and No-News: Drift and Reversal After Headlines[J]. Journal of Financial Economics, 2003,70(2):223-260.
[12] Kelly S, Ahmad K . Estimating the Impact of Domain-Specific News Sentiment on Financial Assets[J]. Knowledge-Based Systems, 2018,150:116-126.
[13] Mitchell M L, Mulherin J H . The Impact of Public Information on the Stock Market[J]. The Journal of Finance, 1994,49(3):923-950.
[14] Fang L, Peress J . Media Coverage and the Cross‐Section of Stock Returns[J]. The Journal of Finance, 2009,64(5):2023-2052.
[15] 饶育蕾, 彭叠峰, 成大超 . 媒体注意力会引起股票的异常收益吗?——来自中国股票市场的经验证据[J]. 系统工程理论与实践, 2010,30(2):287-297.
[15] ( Rao Yulei, Peng Diefeng, Cheng Dachao . Does Media Attention Cause Abnormal Return? —Evidence from China’s Stock Market[J]. Systems Engineering-Theory & Practice, 2010,30(2):287-297.)
[16] 杨阳 . 上市公司新闻情感倾向对股价的影响分析[D]. 北京:北京理工大学, 2015.
[16] ( Yang Yang . Analysis on the Impact of the Sentiment of Firm-Apecific News on Stock Price[D]. Beijing: Beijing Institute of Technology, 2015.)
[17] Boudoukh J, Feldman R, Kogan S , et al. Information, Trading, and Volatility: Evidence from Firm-Specific News[J]. The Review of Financial Studies, 2019,32(3):992-1033.
[18] Li Q, Wang T J, Li P , et al. The Effect of News and Public Mood on Stock Movements[J]. Information Sciences, 2014,278:826-840.
[19] 刘海飞, 许金涛 . 互联网异质性财经新闻对股市的影响——来自中国互联网数据与上市公司的证据[J]. 产业经济研究, 2017(1):76-88.
[19] ( Liu Haifei, Xu Jintao . The Impact of Internet Heterogeneous Financial and Economic News on Stock Market: Evidence from Chinese Internet Data and Listed Companies, Industrial Economics Research, 2017(1):76-88.)
[20] 钟惠波, 沈依琴, 曾奕萌 . 新闻话语方式对股价的影响——基于财经媒体类型的视角[J]. 北京理工大学学报(社会科学版), 2018,20(3):98-104.
[20] ( Zhong Huibo, Shen Yiqin, Zeng Yimeng . The Influence of News Discourse and Stock Price——Based on the Perspective of Financial Media Types[J]. Journal of Beijing Institute of Technology(Social Sciences Edition), 2018,20(3):98-104.)
[21] Sims C A . Macroeconomics and Reality[J]. Econometrica, Econometric Society, 1980,48(1):1-48.
[22] Dewan S, Ramaprasad J. Social Media, Traditional Media, Music Sales[J]. MIS Quarterly, 2014,38(1):101-122.
[23] Li D F, Wang Y T, Madden A , et al. Analyzing Stock Market Trends Using Social Media User Moods and Social Influence[J]. Journal of the Association for Information Science and Technology, 2019,70(9):1000-1013.
[24] Tetlock P C . Giving Content to Investor Sentiment: The Role of Media in the Stock Market[J]. The Journal of Finance, 2007,62(3):1139-1168.
[25] 朱南丽, 邹平, 张永平 , 等. 基于博客/微博信息量的投资者关注度测量研究——来自中国股票市场的经验数据[J]. 经济问题探索, 2015(2):159-166.
[25] ( Zhu Nanli, Zou Ping, Zhang Yongping , et al. Research on Investor’s Attention Measurement Based on Blog/Microblog Information Volume——Empirical Data from China’s Stock Market, Inquiry into Economic Issues, 2015(2):159-166.)
[26] 徐琳宏, 林鸿飞, 潘宇 , 等. 情感词汇本体的构造[J]. 情报学报, 2008,27(2):180-185.
[26] ( Xu Linhong, Lin Hongfei, Pan Yu , et al. Constructing the Affective Lexicon Ontology[J]. Journal of the China Society for Scientific and Technical Information, 2008,27(2):180-185.)
[27] Bian S B, Jia D K, Li F , et al. A New Chinese Financial Sentiment Dictionary for Textual Analysis in Accounting and Finance[J]. SSRN Electronic Journal, 2019. DOI: 10.2139/ssrn.3446388.
[28] 陈晓东 . 基于情感词典的中文微博情感倾向分析研究[D]. 武汉:华中科技大学, 2012.
[28] ( Chen Xiaodong . Research on Sentiment Dictionary Based Emotional Tendency Analysis of Chinese Microblog[D]. Wuhan: Huazhong University of Science and Technology, 2012.)
[29] Sun Y, Liu X, Chen G Y , et al. How Mood Affects the Stock Market: Empirical Evidence from Microblogs[J]. Information & Management, 2020,57(5):103181.
[30] 岑咏华, 谭志浩, 吴承尧 . 财经媒介信息对股票市场的影响研究:基于情感分析的实证[J]. 数据分析与知识发现, 2019,3(9):98-114.
[30] ( Cen Yonghua, Tan Zhihao, Wu Chengyao . Impacts of Financial Media Information on Stock Market: An Empirical Study of Sentiment Analysis[J]. Data Analysis and Knowledge Discovery, 2019,3(9):98-114.)
[31] Li T, van Dalen J, van Rees P J . More than Just Noise? Examining the Information Content of Stock Microblogs on Financial Markets[J]. Journal of Information Technology, 2018,33(1):50-69.
doi: 10.1057/s41265-016-0034-2
[32] Li F. Annual Report Readability, Current Earnings, Earnings Persistence[J]. Journal of Accounting and Economics, 2008,45(2-3):221-247.
doi: 10.1016/j.jacceco.2008.02.003
[33] Lawrence A . Individual Investors and Financial Disclosure[J]. Journal of Accounting and Economics, 2013,56(1):130-147.
doi: 10.1016/j.jacceco.2013.05.001
[34] 武慧锋 . 新闻报道对股票价格影响的实证研究[J]. 财政科学, 2017,21(9):135-140.
[34] ( Wu Huifeng . Empirical Study on How News Impact Stock Prices[J]. Fiscal Science, 2017,21(9):135-140.)
[1] Xu Yuemei, Wang Zihou, Wu Zixin. Predicting Stock Trends with CNN-BiLSTM Based Multi-Feature Integration Model[J]. 数据分析与知识发现, 2021, 5(7): 126-138.
[2] Zhong Jiawa,Liu Wei,Wang Sili,Yang Heng. Review of Methods and Applications of Text Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(6): 1-13.
[3] Liu Tong,Liu Chen,Ni Weijian. A Semi-Supervised Sentiment Analysis Method for Chinese Based on Multi-Level Data Augmentation[J]. 数据分析与知识发现, 2021, 5(5): 51-58.
[4] Wang Yuzhu,Xie Jun,Chen Bo,Xu Xinying. Multi-modal Sentiment Analysis Based on Cross-modal Context-aware Attention[J]. 数据分析与知识发现, 2021, 5(4): 49-59.
[5] Li Feifei,Wu Fan,Wang Zhongqing. Sentiment Analysis with Reviewer Types and Generative Adversarial Network[J]. 数据分析与知识发现, 2021, 5(4): 72-79.
[6] Chang Chengyang,Wang Xiaodong,Zhang Shenglei. Polarity Analysis of Dynamic Political Sentiments from Tweets with Deep Learning Method[J]. 数据分析与知识发现, 2021, 5(3): 121-131.
[7] Zhang Mengyao, Zhu Guangli, Zhang Shunxiang, Zhang Biao. Grouping Microblog Users of Trending Topics Based on Sentiment Analysis[J]. 数据分析与知识发现, 2021, 5(2): 43-49.
[8] Han Pu, Zhang Wei, Zhang Zhanpeng, Wang Yuxin, Fang Haoyu. Sentiment Analysis of Weibo Posts on Public Health Emergency with Feature Fusion and Multi-Channel[J]. 数据分析与知识发现, 2021, 5(11): 68-79.
[9] Xu Hongxia,Yu Qianqian,Qian Li. Studying Content Interaction Data with Topic Model and Sentiment Analysis[J]. 数据分析与知识发现, 2020, 4(7): 110-117.
[10] Jiang Lin,Zhang Qilin. Research on Academic Evaluation Based on Fine-Grain Citation Sentimental Quantification[J]. 数据分析与知识发现, 2020, 4(6): 129-138.
[11] Shi Lei,Wang Yi,Cheng Ying,Wei Ruibin. Review of Attention Mechanism in Natural Language Processing[J]. 数据分析与知识发现, 2020, 4(5): 1-14.
[12] Li Tiejun,Yan Duanwu,Yang Xiongfei. Recommending Microblogs Based on Emotion-Weighted Association Rules[J]. 数据分析与知识发现, 2020, 4(4): 27-33.
[13] Shen Zhuo,Li Yan. Mining User Reviews with PreLM-FT Fine-Grain Sentiment Analysis[J]. 数据分析与知识发现, 2020, 4(4): 63-71.
[14] Xue Fuliang,Liu Lifang. Fine-Grained Sentiment Analysis with CRF and ATAE-LSTM[J]. 数据分析与知识发现, 2020, 4(2/3): 207-213.
[15] Zhang Yipeng,Ma Jingdong. Analyzing Sentiments and Dissemination of Misinformation on Public Health Emergency[J]. 数据分析与知识发现, 2020, 4(12): 45-54.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626，82624938   E-mail:jishu@mail.las.ac.cn