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Does Bitcoin React to Trump’s Tweets?

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  • Huynh, Toan Luu Duc

Abstract

This textual analysis with spillover effects examines whether the sentiment expressed in the US President Donald Trump’s tweets correlates to price and volume activity in the Bitcoin market. After examining 13,918 tweets from January 2017 to January 2020, we find that negative sentiment is a predictive factor for Bitcoin returns, trading volumes, realized volatility, and jumps. In addition, only negative sentiment has a Granger-causal relation with volatility. We also find that Trump’s Twitter sentiment can influence the Bitcoin market in the form of time-varying dependence. This paper also extended the COVID-19 period and found that Trump’s sentiment can be a predictive tool to the Bitcoin market during the pandemic. Our results hold robust for alternative cryptocurrencies and offer insights about this market.

Suggested Citation

  • Huynh, Toan Luu Duc, 2021. "Does Bitcoin React to Trump’s Tweets?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
  • Handle: RePEc:eee:beexfi:v:31:y:2021:i:c:s2214635021000903
    DOI: 10.1016/j.jbef.2021.100546
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    as
    1. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    4. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 1-30.
    5. Huang, Darien & Kilic, Mete, 2019. "Gold, platinum, and expected stock returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 50-75.
    6. Refk Selmi & Aviral Kumar Tiwari & Shawkat Hammoudeh, 2018. "Efficiency or speculation? A dynamic analysis of the Bitcoin market," Economics Bulletin, AccessEcon, vol. 38(4), pages 2037-2046.
    7. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    8. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    9. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Volatility spillovers across stock index futures in Asian markets: Evidence from range volatility estimators," Finance Research Letters, Elsevier, vol. 17(C), pages 158-166.
    10. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    11. Jozef Baruník and Ev~en Kocenda, 2019. "Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    12. Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    13. Haroon, Omair & Rizvi, Syed Aun R., 2020. "COVID-19: Media coverage and financial markets behavior—A sectoral inquiry," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    14. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    15. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    16. Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
    17. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    18. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    19. Shuming Liu, 2015. "Investor Sentiment and Stock Market Liquidity," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 16(1), pages 51-67, January.
    20. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    21. 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.
    22. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    23. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    24. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    25. 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.
    26. 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.
    27. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    28. 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.
    29. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    30. Shahzad, Syed Jawad Hussain & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2019. "Is Bitcoin a better safe-haven investment than gold and commodities?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 322-330.
    31. Koutmos, Dimitrios, 2018. "Liquidity uncertainty and Bitcoin’s market microstructure," Economics Letters, Elsevier, vol. 172(C), pages 97-101.
    32. Wang, Gang-Jin & Xie, Chi & Wen, Danyan & Zhao, Longfeng, 2019. "When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin," Finance Research Letters, Elsevier, vol. 31(C).
    33. 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.
    34. 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.
    35. 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.
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    Cited by:

    1. N. L. Balasudarsun & Bikramaditya Ghosh & Sathish Mahendran, 2022. "Impact of Negative Tweets on Diverse Assets during Stressful Events: An Investigation through Time-Varying Connectedness," JRFM, MDPI, vol. 15(6), pages 1-12, June.

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    More about this item

    Keywords

    Trump twitter; Negative; Positive; Textual analysis; Predictability;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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