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Social media, political uncertainty, and stock markets

Author

Listed:
  • Rui Fan

    (Swansea University)

  • Oleksandr Talavera

    (University of Birmingham)

  • Vu Tran

    (University of Reading)

Abstract

This study proposes a new measure of firm-level uncertainty exposure around important political events. More specifically, we construct a degree of (dis)agreement among social media users who jointly mention firms and politicians. We study a sample of over 23 million tweets mentioning both a firm from the S&P 500 composite and ‘Trump’ from October 2016 to May 2017. We then analyze the relationship between the (dis)agreement measure and individual stock features. The results suggest that increased disagreement among such tweets is associated with heightened stock price volatility and trading volume. This link is observed before the US Presidential Inauguration in January 2017 but not afterwards. The finding is confirmed by further robustness checks based on filtered tweets with policy keywords and policy-sensitive industries.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:rqfnac:v:55:y:2020:i:3:d:10.1007_s11156-020-00870-4
    DOI: 10.1007/s11156-020-00870-4
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    References listed on IDEAS

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    Cited by:

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    2. D. G. DeBoskey & Yutao Li & Gerald J. Lobo & Yan Luo, 2021. "Corporate political transparency and the cost of debt," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 111-145, July.
    3. Guastella, Gianni & Mazzarano, Matteo & Pareglio, Stefano & Xepapadeas, Anastasios, 2022. "Climate reputation risk and abnormal returns in the stock markets: A focus on large emitters," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. Nguyen, Phuc Lam Thy & Alsakka, Rasha & Mantovan, Noemi, 2023. "Political preferences and stock markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Matteo Mazzarano & Giovanni Guastella & Stefano Pareglio & Anastasios Xepapadeas, 2021. "Carbon Boards and Transition Risk: Explicit and Implicit exposure implications for Total Stock Returns and Dividend Payouts," DISCE - Quaderni del Dipartimento di Politica Economica dipe0023, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    6. Ma, Dan & Zhang, Chuan & Hui, Yarong & Xu, Bing, 2022. "Economic uncertainty spillover and social networks," Journal of Business Research, Elsevier, vol. 145(C), pages 454-467.
    7. Daniel Perico Ortiz, 2023. "Economic policy statements, social media, and stock market uncertainty: An analysis of Donald Trump’s tweets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(2), pages 333-367, June.

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    More about this item

    Keywords

    Twitter; US election; Stock market; Investor sentiment; Text classification; Computational linguistics;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • 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
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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