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Trump tweets and the efficient Market Hypothesis

Author

Listed:
  • Born, Jeffery A.

    (Northeastern University)

  • Myers, David H.

    (Northeastern University)

  • Clark, William J.

    (Morgan Stanley)

Abstract

In a Semi-Strong Form (SSF) Efficient Market, asset prices should respond quickly and completely to the public release of new information. In the period from his election on 11/8/16 to his swearing in ceremony on 1/20/17, President-elect Trump posted numerous statements (‘tweets’) on his Twitter messaging service account that identified ten publicly traded firms. In the absence of new information, the Efficient Market Hypothesis (EMH) predicts that these announcements should have little or no price impact on the common stocks of these firms. Using standard event study methods, we find that positive (negative) content tweets elicited positive (negative) abnormal returns on the event date and virtually all of this effect is from the opening stock price to the close. Within five trading days, the CARs are no longer statistically significant. President-elect Trump’s tweets were associated with increases in trading volume and Google Search activity. Taken as a whole, the price and trading volume response, combined with Google Search activity is consistent with hypothesis that it was small/noise traders who were acting on President-elect Trump’s tweets and that their impacts were transitory.

Suggested Citation

  • Born, Jeffery A. & Myers, David H. & Clark, William J., 2017. "Trump tweets and the efficient Market Hypothesis," Algorithmic Finance, IOS Press, vol. 6(3-4), pages 103-109.
    • Handle: RePEc:ris:iosalg:0062
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    Citations

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    Cited by:

    1. Kinyua, Johnson D. & Mutigwe, Charles & Cushing, Daniel J. & Poggi, Michael, 2021. "An analysis of the impact of President Trump’s tweets on the DJIA and S&P 500 using machine learning and sentiment analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    2. Heleen Brans & Bert Scholtens, 2020. "Under his thumb the effect of president Donald Trump’s Twitter messages on the US stock market," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-11, March.
    3. Nishimura, Yusaku & Sun, Bianxia, 2021. "President’s Tweets, US-China economic conflict and stock market Volatility: Evidence from China and G5 countries," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    4. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
    5. Marinč, Matej & Massoud, Nadia & Ichev, Riste & Valentinčič, Aljoša, 2021. "Presidential candidates linguistic tone: The impact on the financial markets," Economics Letters, Elsevier, vol. 204(C).
    6. Abdi, Farshid & Kormanyos, Emily & Pelizzon, Loriana & Getmansky, Mila & Simon, Zorka, 2021. "Market impact of government communication: The case of presidential tweets," SAFE Working Paper Series 314, Leibniz Institute for Financial Research SAFE, revised 2021.
    7. Yusaku Nishimura & Xuyi Dong & Bianxia Sun, 2021. "Trump's tweets: Sentiment, stock market volatility, and jumps," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 497-512, September.
    8. Machus, Tobias & Mestel, Roland & Theissen, Erik, 2022. "Heroes, just for one day: The impact of Donald Trump’s tweets on stock prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    9. Vijay S. Sampath & Arthur J. O’Connor & Calvester Legister, 2022. "Moral leadership and investor attention: An empirical assessment of the potus’s tweets on firms’ market returns," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 881-910, April.
    10. Minea Elena Loredana, 2019. "A Critical Theoretical Analysis On The Implications Of Efficient Market Hypothesis (Emh)," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 298-303, December.

    More about this item

    Keywords

    Efficient Market Hypothesis; trump; tweets; noise traders;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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