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The convergence and divergence of investors' opinions around earnings news: Evidence from a social network

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  • Giannini, Robert
  • Irvine, Paul
  • Shu, Tao

Abstract

We collect a unique dataset of Twitter posts to examine the change in investor disagreement around earnings announcements. We find that investors' opinions can either converge (reduced disagreement) or diverge (increased disagreement) around earnings announcements. The convergence and divergence of opinion has significant effects on trading volume and return. Consistent with theoretical predictions, both the convergence and divergence of opinion are associated with a greater volume reaction to earnings news. While the convergence of opinion is associated with lower earnings announcement returns, the divergence of opinion is associated with higher earnings announcement returns.

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  • Giannini, Robert & Irvine, Paul & Shu, Tao, 2019. "The convergence and divergence of investors' opinions around earnings news: Evidence from a social network," Journal of Financial Markets, Elsevier, vol. 42(C), pages 94-120.
    • Handle: RePEc:eee:finmar:v:42:y:2019:i:c:p:94-120
    DOI: 10.1016/j.finmar.2018.12.003
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    3. Ding, Rong & Zhou, Hang & Li, Yifan, 2020. "Social media, financial reporting opacity, and return comovement: Evidence from Seeking Alpha," Journal of Financial Markets, Elsevier, vol. 50(C).
    4. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media, political uncertainty, and stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(3), pages 1137-1153, October.
    5. Yang, Xiaolan & Zhu, Yu & Cheng, Teng Yuan, 2020. "How the individual investors took on big data: The effect of panic from the internet stock message boards on stock price crash," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    6. Laurent Bouton & Aniol Llorente-Saguer & Antonin Macé & Adam Meirowitz & Shaoting Pi & Dimitrios Xefteris, 2022. "Public Information as a Source of Disagreement Among Shareholders," NBER Working Papers 30757, National Bureau of Economic Research, Inc.
    7. Mahmoudi, Nader & Docherty, Paul & Melia, Adrian, 2022. "Firm-level investor sentiment and corporate announcement returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    8. 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).
    9. 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).
    10. Cookson, J. Anthony & Niessner, Marina & Schiller, Christoph M., 2022. "Can Social Media Inform Corporate Decisions? Evidence from Merger Withdrawals," SocArXiv 56yrj, Center for Open Science.
    11. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
    12. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.

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    More about this item

    Keywords

    Investor disagreement; Social media; Divergence of opinion; Convergence of opinion; Trading volume; Stock returns; Earnings announcement;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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