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Do markets pay attention to political disinformation?

Author

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  • Hartwell, Christopher A.
  • Hubschmid-Vierheilig, Elena

Abstract

They do, but not in ways one might think. Using an example from the 2016 Presidential election in the United States, we show that days with heavy doses of disinformation related to the candidates do not affect broad index stock returns. However, disinformation that was strongly pro-Hillary Clinton was associated with a substantial lowering of conditional volatility of stocks, even when controlling for other macroeconomic news and news sentiment.

Suggested Citation

  • Hartwell, Christopher A. & Hubschmid-Vierheilig, Elena, 2024. "Do markets pay attention to political disinformation?," Finance Research Letters, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:finlet:v:70:y:2024:i:c:s1544612324013953
    DOI: 10.1016/j.frl.2024.106366
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    References listed on IDEAS

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    1. Pantzalis, Christos & Stangeland, David A. & Turtle, Harry J., 2000. "Political elections and the resolution of uncertainty: The international evidence," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1575-1604, October.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Refk Selmi & Jamal Bouoiyour, 2020. "The financial costs of political uncertainty: Evidence from the 2016 US presidential elections," Scottish Journal of Political Economy, Scottish Economic Society, vol. 67(2), pages 166-185, May.
    4. Hartwell, Christopher A., 2022. "Populism and financial markets," Finance Research Letters, Elsevier, vol. 46(PB).
    5. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    6. Arcuri, Maria Cristina & Gandolfi, Gino & Russo, Ivan, 2023. "Does fake news impact stock returns? Evidence from US and EU stock markets," Journal of Economics and Business, Elsevier, vol. 125.
    7. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    8. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    9. Herold, Michael & Kanz, Andreas & Muck, Matthias, 2021. "Do opinion polls move stock prices? Evidence from the US presidential election in 2016," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 665-690.
    10. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    11. Bryan Fong, 2021. "Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    12. Stephens, John & Mehdian, Seyed & Gherghina, Ștefan Cristian & Stoica, Ovidiu, 2023. "The reaction of the financial market to the January 6 United States Capitol attack: An intraday study," Finance Research Letters, Elsevier, vol. 56(C).
    13. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    14. Kolari, James W. & Pynnonen, Seppo, 2011. "Nonparametric rank tests for event studies," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 953-971.
    15. Vafaeimehr, Ahmadreza & Schulmerich, Marcus & Paterlini, Sandra, 2023. "Top investment banks, confirmation Bias, and the market pricing of forecast revisions," International Review of Financial Analysis, Elsevier, vol. 88(C).
    16. Alexandre Bovet & Hernán A. Makse, 2019. "Influence of fake news in Twitter during the 2016 US presidential election," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
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    More about this item

    Keywords

    Disinformation; Elections; Trump; Clinton; Volatility; Confirmation bias;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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