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The causal relationship between social media sentiment and stock return: Experimental evidence from an online message forum

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  • Wang, Xinjie
  • Xiang, Zhiqiang
  • Xu, Weike
  • Yuan, Peixuan

Abstract

This paper examines the impact of sentiment in an online message forum on stock returns. Using a novel controlled experiment, we collect a large panel of messages with no fundamental information but strong sentiment and stock return data. We find a significant causal effect of social media sentiment on the same-day stock returns. The sentiment has no significant effects on stock returns on subsequent days. This effect is mainly driven by messages with positive sentiment, which has a strong positive impact on stock returns. Our results establish a causal relationship between social media sentiment and stock returns and highlight the risk of market manipulation via social media.

Suggested Citation

  • Wang, Xinjie & Xiang, Zhiqiang & Xu, Weike & Yuan, Peixuan, 2022. "The causal relationship between social media sentiment and stock return: Experimental evidence from an online message forum," Economics Letters, Elsevier, vol. 216(C).
  • Handle: RePEc:eee:ecolet:v:216:y:2022:i:c:s0165176522001793
    DOI: 10.1016/j.econlet.2022.110598
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    1. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
    2. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    3. Zhang, Tonghui & Yuan, Ying & Wu, Xi, 2020. "Is microblogging data reflected in stock market volatility? Evidence from Sina Weibo," Finance Research Letters, Elsevier, vol. 32(C).
    4. Steve Y. Yang & Sheung Yin Kevin Mo & Anqi Liu, 2015. "Twitter financial community sentiment and its predictive relationship to stock market movement," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1637-1656, October.
    5. Jia, Weishi & Redigolo, Giulia & Shu, Susan & Zhao, Jingran, 2020. "Can social media distort price discovery? Evidence from merger rumors," Journal of Accounting and Economics, Elsevier, vol. 70(1).
    6. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    7. Broadstock, David C. & Zhang, Dayong, 2019. "Social-media and intraday stock returns: The pricing power of sentiment," Finance Research Letters, Elsevier, vol. 30(C), pages 116-123.
    8. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    9. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    10. Gan, Baoqing & Alexeev, Vitali & Bird, Ron & Yeung, Danny, 2020. "Sensitivity to sentiment: News vs social media," International Review of Financial Analysis, Elsevier, vol. 67(C).
    11. Ackert, Lucy F. & Jiang, Lei & Lee, Hoan Soo & Liu, Jie, 2016. "Influential investors in online stock forums," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 39-46.
    12. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    13. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    14. Gao, Ya & Xiong, Xiong & Feng, Xu & Li, Youwei & Vigne, Samuel A., 2019. "A new attention proxy and order imbalance: Evidence from China," Finance Research Letters, Elsevier, vol. 29(C), pages 411-417.
    15. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    16. Pieter de Jong & Sherif Elfayoumy & Oliver Schnusenberg, 2017. "From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(1), pages 54-64, January.
    17. Selin Duz Tan & Oktay Tas, 2021. "Social Media Sentiment in International Stock Returns and Trading Activity," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(2), pages 221-234, April.
    18. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    19. Xiong, Xiong & Meng, Yongqiang & Joseph, Nathan Lael & Shen, Dehua, 2020. "Stock mispricing, hard-to-value stocks and the influence of internet stock message boards," International Review of Financial Analysis, Elsevier, vol. 72(C).
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    Cited by:

    1. Zeitun, Rami & Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2023. "The impact of Twitter-based sentiment on US sectoral returns," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    2. Halil D Kaya & Abhinav Maramraju & Anish Nallapu, 2023. "Social Media, Trading Volume, Volatility And Stock Prices," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 40-50, December.

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    More about this item

    Keywords

    Sentiment; Online message board; Stock return;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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