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The impact of US presidents on market returns: Evidence from Trump's tweets

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  • Pham, Duong Phuong Thao
  • Huynh, Ngoc Quang Anh
  • Duong, Duy

Abstract

We analyze President Trump’s Twitter posts on the COVID-19 pandemic to quantitatively construct his sentiment proxy to examine its predictive power in industry-level equity returns. With the growing influence of social media, some “special” people have been able to use their celebrity status for wielding significant market influence, thereby causing a new modern crisis. This study parsed words from 2574 tweets from President Trump’s Twitter account to explore the predictive power of his sentiments on the US market during the pandemic. After controlling for rigorous factors, result shows that an industry-level negative tone in general content is unlikely to be predictive of stock returns. Furthermore, the consumer goods industry exhibited a negative return when Trump displayed a negative attitude toward the pandemic. Industries adversely affected by the pandemic because of travel restrictions, consumption shocks, and public health issues are statistically correlated with Trump’s negative tone on the pandemic.

Suggested Citation

  • Pham, Duong Phuong Thao & Huynh, Ngoc Quang Anh & Duong, Duy, 2022. "The impact of US presidents on market returns: Evidence from Trump's tweets," Research in International Business and Finance, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:riibaf:v:62:y:2022:i:c:s0275531922000691
    DOI: 10.1016/j.ribaf.2022.101681
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    1. Suphanit Piyapromdee & Peter Spittal, 2020. "The Income and Consumption Effects of COVID‐19 and the Role of Public Policy," Fiscal Studies, John Wiley & Sons, vol. 41(4), pages 805-827, December.
    2. Corbet, Shaen & Goodell, John W. & Günay, Samet, 2020. "Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19," Energy Economics, Elsevier, vol. 92(C).
    3. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    4. Goodell, John W. & Huynh, Toan Luu Duc, 2020. "Did Congress trade ahead? Considering the reaction of US industries to COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    5. Schell, Daniel & Wang, Mei & Huynh, Toan Luu Duc, 2020. "This time is indeed different: A study on global market reactions to public health crisis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    6. Veronica Guerrieri & Guido Lorenzoni & Ludwig Straub & Iván Werning, 2022. "Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?," American Economic Review, American Economic Association, vol. 112(5), pages 1437-1474, May.
    7. Wagner, Alexander F. & Zeckhauser, Richard J. & Ziegler, Alexandre, 2018. "Company stock price reactions to the 2016 election shock: Trump, taxes, and trade," Journal of Financial Economics, Elsevier, vol. 130(2), pages 428-451.
    8. Bodnaruk, Andriy & Loughran, Tim & McDonald, Bill, 2015. "Using 10-K Text to Gauge Financial Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(4), pages 623-646, August.
    9. Pham, Linh & Luu Duc Huynh, Toan, 2020. "How does investor attention influence the green bond market?," Finance Research Letters, Elsevier, vol. 35(C).
    10. Carl Ajjoub & Thomas Walker & Yunfei Zhao, 2020. "Social media posts and stock returns: The Trump factor," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 17(2), pages 185-213, June.
    11. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, August.
    12. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    13. Ghulam Abbas & Shouyang Wang, 2020. "Does macroeconomic uncertainty really matter in predicting stock market behavior? A comparative study on China and USA," China Finance Review International, Emerald Group Publishing Limited, vol. 10(4), pages 393-427, May.
    14. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    15. Sharif, Arshian & Aloui, Chaker & Yarovaya, Larisa, 2020. "COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach," International Review of Financial Analysis, Elsevier, vol. 70(C).
    16. Schwert, G William, 1981. "Using Financial Data to Measure Effects of Regulation," Journal of Law and Economics, University of Chicago Press, vol. 24(1), pages 121-158, April.
    17. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
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    1. Bales, Stephan & Burghartz, Kaspar & Burghof, Hans-Peter & Hitz, Lukas, 2023. "Does the source of uncertainty matter? The impact of financial, newspaper and Twitter-based measures on U.S. banks," Research in International Business and Finance, Elsevier, vol. 65(C).

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    More about this item

    Keywords

    Coronavirus; COVID-19; Market reactions; Trump Twitter; US industries;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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