IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v58y2021ics106294082100125x.html
   My bibliography  Save this article

President’s Tweets, US-China economic conflict and stock market Volatility: Evidence from China and G5 countries

Author

Listed:
  • Nishimura, Yusaku
  • Sun, Bianxia

Abstract

This study provides empirical evidence that the tweets from US President Donald J. Trump influence the trading decisions of investors worldwide. We examine the effects of Trump’s tweets related to China on stock market volatility in China and the G5 countries. Our results show that Trump’s original tweets related to the US-China economic conflict expand volatility in stock markets worldwide, and the US-China trade friction intensifies this effect. Furthermore, Trump’s tweets with different sentiments have different impacts on the returns of global stock markets. Our findings confirm that international investors may make their investment decisions based on information conveyed in these tweets.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:ecofin:v:58:y:2021:i:c:s106294082100125x
    DOI: 10.1016/j.najef.2021.101506
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106294082100125X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2021.101506?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    3. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    4. Joel Peress, 2014. "The Media and the Diffusion of Information in Financial Markets: Evidence from Newspaper Strikes," Journal of Finance, American Finance Association, vol. 69(5), pages 2007-2043, October.
    5. Martin Martens, 2002. "Measuring and forecasting S&P 500 index‐futures volatility using high‐frequency data," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(6), pages 497-518, June.
    6. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    7. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: Intra-day versus inter-day models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 449-465, December.
    8. Joseph E. Engelberg & Christopher A. Parsons, 2011. "The Causal Impact of Media in Financial Markets," Journal of Finance, American Finance Association, vol. 66(1), pages 67-97, February.
    9. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    10. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    11. 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.
    12. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    13. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    14. Constantin Colonescu, 2018. "The Effects of Donald Trump's Tweets on US Financial and Foreign Exchange Markets," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 4(4), pages 375-388, October.
    15. 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.
    16. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    17. Xin Huang, 2018. "Macroeconomic news announcements, systemic risk, financial market volatility, and jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(5), pages 513-534, May.
    18. Qi Ge & Alexander Kurov & Marketa Halova Wolfe, 2019. "Do Investors Care About Presidential Company‐Specific Tweets?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(2), pages 213-242, July.
    19. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    3. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2017. "Do International Investors Cause Stock Market Comovements? Comparing Responses of Cross-Listed Stocks between Accessible and Inaccessible Markets," Discussion Papers in Economics and Business 17-01, Osaka University, Graduate School of Economics.
    4. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2018. "Do international investors cause stock market spillovers? Comparing responses of cross-listed stocks between accessible and inaccessible markets," Economic Modelling, Elsevier, vol. 69(C), pages 237-248.
    7. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media bots and stock markets," European Financial Management, European Financial Management Association, vol. 26(3), pages 753-777, June.
    8. Dimitrios P. Louzis & Spyros Xanthopoulos-Sisinis & Apostolos P. Refenes, 2012. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Applied Economics, Taylor & Francis Journals, vol. 44(27), pages 3533-3550, September.
    9. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    10. 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.
    11. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
    12. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    13. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    14. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    15. Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
    16. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    17. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Fabio & Spagnolo, Nicola, 2022. "Cross-border portfolio flows and news media coverage," Journal of International Money and Finance, Elsevier, vol. 126(C).
    18. Lee, Hwang Hee & Hyun, Jung-Soon, 2019. "The asymmetric effect of equity volatility on credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 125-136.
    19. Bollerslev, Tim & Kretschmer, Uta & Pigorsch, Christian & Tauchen, George, 2009. "A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects," Journal of Econometrics, Elsevier, vol. 150(2), pages 151-166, June.
    20. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.

    More about this item

    Keywords

    High-frequency data; Social media; Stock market volatility; Trump tweets; US-China economic conflict;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:58:y:2021:i:c:s106294082100125x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.