Stock market reactions to social media: Evidence from WeChat recommendations

被引:4
|
作者
Zhang, Yuzhao [1 ]
Liu, Haifei [2 ]
机构
[1] Nanjing Univ Finance & Econ, Sch Finance, Nanjing 210000, Jiangsu, Peoples R China
[2] Nanjing Univ, Sch Management & Engn, Nanjing 210093, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
WeChat recommendations; Price pressure hypothesis; Market reactions; Information diffusion; Social media; ANALYST RECOMMENDATIONS; PERFORMANCE EVALUATION; INFORMATION; SENTIMENT; ATTENTION; POSTINGS; NOISE; TALK; NEWS;
D O I
10.1016/j.physa.2020.125357
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This paper examines the market behavior of stocks that are favorably mentioned on official WeChat account (OWA). To the best of our knowledge, we are the first to investigate market reactions to recommendations on WeChat. The empirical results show that there is a significantly positive abnormal return and excess trading volume on the publication day. Moreover, the cumulative average abnormal return for OWA completely reverses in a short time, which supports the price pressure hypothesis. Additional analyses reveal that market reactions in the smaller firms are significantly greater than those in the largest firms on the publication day. Finally, we preclude possibilities that market reactions on the event day are induced by the secondary dissemination of analyst recommendations, firm-specific news releases, media coverage, and previous positive significant abnormal returns. (C) 2020 Published by Elsevier B.V.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Pan(dem)ic reactions in Turkish stock market: evidence from share repurchases
    Burak Pirgaip
    Eurasian Economic Review, 2021, 11 : 381 - 402
  • [42] SENTIMENT REVEALED IN SOCIAL MEDIA AND ITS EFFECT ON THE STOCK MARKET
    Chen, Hailiang
    De, Prabuddha
    Hu, Yu
    Hwang, Byoung-Hyoun
    2011 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP), 2011, : 25 - 28
  • [43] Predicting the French stock market using social media analysis
    Martin, Vincent
    2013 8TH INTERNATIONAL WORKSHOP ON SEMANTIC AND SOCIAL MEDIA ADAPTATION AND PERSONALIZATION (SMAP 2013), 2013, : 3 - 7
  • [44] Speculator and Influencer Evaluation in Stock Market by Using Social Media
    Dogan, Mustafa
    Metin, Omer
    Tek, Elif
    Yumusak, Semih
    Oztoprak, Kasim
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 4559 - 4566
  • [45] Social media investors' sentiment as stock market performance predictor
    Cheikh, Sana Ben
    Amiri, Hanen
    Loukil, Nadia
    INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS, 2024, 51 (06) : 713 - 724
  • [46] The impact of social media data on Chinese stock market performance
    Cheng, Wanyun
    Lin, Jie
    Zhu, Ling
    Journal of Computational Information Systems, 2013, 9 (19): : 7865 - 7872
  • [47] Predicting Stock Market Movements with Social Media and Machine Learning
    Koukaras, Paraskevas
    Tsichli, Vasiliki
    Tjortjis, Christos
    PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND TECHNOLOGIES (WEBIST), 2021, : 436 - 443
  • [48] Tracking Multiple Social Media for Stock Market Event Prediction
    Jin, Fang
    Wang, Wei
    Chakraborty, Prithwish
    Self, Nathan
    Chen, Feng
    Ramakrishnan, Naren
    ADVANCES IN DATA MINING: APPLICATIONS AND THEORETICAL ASPECTS, ICDM 2017, 2017, 10357 : 16 - 30
  • [49] Social Media and Stock Market Prediction: A Big Data Approach
    Awan, Mazhar Javed
    Rahim, Mohd Shafry Mohd
    Nobanee, Haitham
    Munawar, Ashna
    Yasin, Awais
    Zain, Azlan Mohd
    CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 67 (02): : 2569 - 2583
  • [50] Wisdom of the crowd and stock price crash risk: evidence from social media
    Md Miran Hossain
    Babak Mammadov
    Hamid Vakilzadeh
    Review of Quantitative Finance and Accounting, 2022, 58 : 709 - 742