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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/125989

    Title: 政治人物,推特與金融市場: 來自川普推特的證據
    Politicians, Twitter, and Financial Markets: Evidence from Donald Trump’s tweets
    Authors: 孔美玲
    Consunji, Margaret A.
    Contributors: 楊子霆

    Yang, Tzu-Ting
    Lo, Kuang-Ta

    Consunji, Margaret A.
    Keywords: 川普
    Synthetic Control Method
    Stock Prices
    Exchange Rates
    Date: 2019
    Issue Date: 2019-09-05 17:42:38 (UTC+8)
    Abstract: The use of Twitter as a key political communication tool has become synonymous with U.S. President Donald Trump’s regime. However, Trump’s tweets can also tend to be unabashedly critical of companies, states, and other political figures. Whether or not these negative tweets have an impact on financial markets is debatable. This paper uses the synthetic control method (SCM) to examine the effects of Trump’s negative trade- and business-related tweets on financial markets, particularly stock prices and exchange rates. Three publicly traded U.S. companies (Boeing, Amazon, Harley-Davidson) and three currencies (Euro, Canadian dollar, Mexican peso) were chosen, while 1-2 tweets were collected for each treatment unit. To create the synthetic control for each treatment unit, extensive control unit data was also collected. Then, for each treatment unit, two synthetic control models were created, with one model containing all outcome lags and all covariates whilst the other contained all outcome lags and some covariates. We found that for each treatment unit, the two models were similar, indicating that the results were robust. Overall, we found that results varied depending on the “target” of Trump’s tweets, with the causal effect being most significant for Amazon and Mexico, likely due to the fact that traders or investors may react differently to Trump’s tweets and may base their decisions on certain company- or country-specific characteristics or features, such as type of industry, trade ties, and geographical proximity, among others.
    Reference: Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493–505. https://doi.org/10.1198/jasa.2009.ap08746
    Abadie, A., Diamond, A., & Hainmueller, J. (2011). SYNTH: Stata module to implement Snythetic Control Methods for Comparative Case Studies. Retrieved from https://web.stanford.edu/~jhain/synthpage.html
    Abadie, A., Diamond, A., & Hainmueller, J. (2015). Comparative Politics and the Synthetic Control Method. American Journal of Political Science, 59(2), 495–510. https://doi.org/10.1111/ajps.12116
    Alonso-Muñoz, L., Marcos-García, S., & Casero-Ripollés, A. (2016). Political leaders in (inter)action. Twitter as a strategic communication tool in electoral campaigns. Trípodos, 71–90. Retrieved from https://core.ac.uk/download/pdf/155003405.pdf
    apilayer. (2019). currencylayer API. Retrieved June 1, 2019, from currencylayer API | Free, Reliable Currency Converter API website: https://currencylayer.com/
    Barber, B. M., & Odean, T. (2013). The Behavior of Individual Investors. In Handbook of the Economics of Finance (Vol. 2, pp. 1533–1570). https://doi.org/10.1016/B978-0-44-459406-8.00022-6
    Batista, A. R. de A., Maia, U., & Romero, A. (2018). Stock market under the 2016 Brazilian presidential impeachment: a test in the semi-strong form of the efficient market hypothesis,. Revista Contabilidade & Finanças, 29(78), 405–417. https://doi.org/10.1590/1808-057x201805560
    Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1–8. https://doi.org/10.1016/j.jocs.2010.12.007
    Born, J. A., & Clark, W. (2017). Trump Tweets and the Efficient Market Hypothesis. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2973186
    Botosaru, I., & Ferman, B. (2019). On the role of covariates in the synthetic control method. The Econometrics Journal. https://doi.org/10.1093/ectj/utz001
    Bouttell, J., Craig, P., Lewsey, J., Robinson, M., & Popham, F. (2018). Synthetic control methodology as a tool for evaluating population-level health interventions. Journal of Epidemiology and Community Health, 72(8), 673–678. https://doi.org/10.1136/jech-2017-210106
    Breuninger, K. (2018, December 31). Trump’s most memorable Twitter bombshells of 2018. CNBC. Retrieved from https://www.cnbc.com/2018/12/31/trumps-top-10-biggest-twitter-bombshells-made-history-in-2018.html
    Cancel, D. (2018, January 18). Mexican Peso Traders Are Learning to Ignore Trump’s Tweets. Bloomberg. Retrieved from https://www.bloomberg.com/news/articles/2018-01-18/mexican-peso-traders-are-learning-to-ignore-trump-s-tweets
    Carr, N. (2018, January 26). Why Trump Tweets (And Why We Listen) - POLITICO Magazine. Politico MAgazine. Retrieved from https://www.politico.com/magazine/story/2018/01/26/donald-trump-twitter-addiction-216530
    Central Intelligence Agency (CIA). (2019). The world factbook 2019. Retrieved July 8, 2019, from https://www.cia.gov/library/publications/the-world-factbook/index.html
    Chu, B. (2016, October 7). Five charts that show how the pound has been ravaged by Brexit. The Independent. Retrieved from http://www.independent.co.uk/news/business/news/sterlings-punishment-five-charts-that-show-how-the-pound-has-been-ravaged-by-brexit-a7350251.html
    Clinton, H. (2016, June 9). “Delete your account.” [Twitter Post]. Retrieved from https://twitter.com/HillaryClinton/status/740973710593654784
    Colonescu, C. (2018). The Effects of Donald Trump’s Tweets on US Financial and Foreign Exchange Markets. Athens Journal of Business & Economics, 4, 375–388. https://doi.org/10.30958/ajbe.4-4-2
    Coyne, B. (2016, November 7). How #Election2016 was Tweeted so far. Retrieved June 20, 2019, from https://blog.twitter.com/en_us/a/2016/how-election2016-was-tweeted-so-far.html
    Cunningham, S. (2018). Causal Inference: The Mixtape. 1.7, 328. Retrieved from http://scunning.com/cunningham_mixtape.pdf
    DiChristopher, T. (2019, May 10). Trump’s tweets swing stock market amid trade deal uncertainty. CNBC. Retrieved from https://www.cnbc.com/2019/05/10/trumps-tweets-swing-stock-market-amid-trade-deal-uncertainty.html
    Dube, A., & Zipperer, B. (2015). Pooling Multiple Case Studies Using Synthetic Controls: An Application to Minimum Wage Policies (Discussion Paper No. 8944; p. 60). Retrieved from Institute for the Study of Labor (IZA) website: http://ftp.iza.org/dp8944.pdf
    Evans, G. (2019, May 28). People are losing interest in Trump’s tweets, research finds but people still can’t stop following him. Indy100. Retrieved from https://www.indy100.com/article/trump-twitter-tweets-interactions-us-president-down-research-8933646
    Farley, A. (2018, August 15). Harley-Davidson Stock Nears Breakdown After Trump Tweet. Retrieved May 29, 2019, from Investopedia website: https://www.investopedia.com/news/harleydavidson-stock-nears-breakdown-after-trump-tweet/
    Fisher, M. (2013, April 23). Syrian hackers claim AP hack that tipped stock market by $136 billion. Is it terrorism? Washington Post. Retrieved from https://www.washingtonpost.com/news/worldviews/wp/2013/04/23/syrian-hackers-claim-ap-hack-that-tipped-stock-market-by-136-billion-is-it-terrorism/
    Galati, G., & Ho, C. (2001). Macroeconomic news and the euro/dollar exchange rate. Retrieved from https://www.bis.org/publ/work105.htm
    Galiani, S. & Quistorff, B. (2017). “The synth runner package: Utilities to automate synthetic control estimation using synth”. Stata Journal, StataCorp LP, vol.17(4), 834-849. Retrieved from https://ideas.repec.org/a/tsj/stataj/v17y2017i4p834-849.html
    Ge, Q., Kurov, A., & Wolfe, M. H. (2019). Do Investors Care about Presidential Company‐Specific Tweets? Journal of Financial Research. https://doi.org/10.1111/jfir.12177
    Goldman, D. (2018, April 3). Trump’s latest tweet takes down Amazon stock and the Nasdaq. CNN Business. Retrieved from https://money.cnn.com/2018/04/03/news/companies/amazon-stock/index.html
    Hardouvelis, G. A. (1988). Economic news, exchange rates and interest rates. Journal of International Money and Finance, 7(1), 23–35. https://doi.org/10.1016/0261-5606(88)90003-4
    Imbert, F. (2018, September 4). Canadian dollar drops after Trump says there’s “no political necessity” to keep Canada in a new trade deal. Retrieved May 29, 2019, from CNBC website: https://www.cnbc.com/2018/09/04/canadian-dollar-drops-after-trump-says-there-is-no-political-necessity-to-keep-canada-in-new-trade-deal.html
    InternetLiveStats.com. (2019). Twitter Usage Statistics - Internet Live Stats. Retrieved May 21, 2019, from https://www.internetlivestats.com/twitter-statistics/#sources
    Jermann, M. (2017). Predicting Stock Movement through Executive Tweets. 1-9. Retrieved from https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1174/reports/2743946.pdf
    Johnson, C. (2013). Compared to What? The Effectiveness of Synthetic Control Methods for Causal Inference in Educational Assessment. Theses and Dissertations, 946. Retrieved from http://scholarworks.uark.edu/etd/946?utm_source=scholarworks.uark.edu%2Fetd%2F946&utm_medium=PDF&utm_campaign=PDFCoverPages
    Johnson, E. M., & Brice, M. (2017, December 30). Trump wants Postal Service to charge “much more” for Amazon shipments. Reuters. Retrieved from https://www.reuters.com/article/us-usa-trump-amazon-com-idUSKBN1EN15O
    Juma’h, A. H., & Alnsour, Y. (2018). Using social media analytics: The effect of President Trump’s tweets on companies’ performance. Journal of Accounting and Management Information Systems, 17(1), 100–121. https://doi.org/10.24818/jamis.2018.01005
    Kemp, S. (2019, January 30). Digital trends 2019: Every single stat you need to know about the internet. Retrieved June 13, 2019, from The Next Web website: https://thenextweb.com/contributors/2019/01/30/digital-trends-2019-every-single-stat-you-need-to-know-about-the-internet/
    Kim, E. (2016, November 9). Trump warned Amazon would have “problems” under his presidency — here’s what could happen. Business Insider. Retrieved from https://www.businessinsider.com/how-trump-presidency-will-affect-amazon-2016-11
    Kornblum, A. (2018, August 13). 11 Tweets that Turned the Stock Market Upside Down. Retrieved May 28, 2019, from Feed | Ogilvy website: https://www.ogilvy.com/feed/11-tweets-that-turned-the-stock-market-upside-down/
    Kreif, N., Grieve, R., Hangartner, D., Turner, A. J., Nikolova, S., & Sutton, M. (2016). Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units: Synthetic Control Method for Evaluating Health Policies. Health Economics, 25(12), 1514–1528. https://doi.org/10.1002/hec.3258
    Kurtzleben, D. (2017, October 2). Pew Study: News Coverage Of Trump More Negative Than For Other Presidents: NPR. National Public Radio (NPR). Retrieved from https://www.npr.org/2017/10/02/555092743/study-news-coverage-of-trump-more-negative-than-for-other-presidents
    Mack, E. (2016, February 28). Why is Donald Trump threatening Amazon and Jeff Bezos? Retrieved June 21, 2019, from CNET website: https://www.cnet.com/news/donald-trump-threatens-jeff-bezos-amazon/
    Mak, T. (2019, April 11). How President Trump’s Angry Tweets Can Ripple Across Social Media. In National Public Radio’s Morning Edition. National Public Radio (NPR). Retrieved from https://www.npr.org/2019/04/11/712116702/how-trumps-angry-tweets-can-ripple-across-social-media
    McClelland, R., & Gault, S. (2017). The Synthetic Control Method as a Tool to Understand State Policy [Research Report]. Retrieved from Urban Institute website: https://www.urban.org/sites/default/files/publication/89246/the_synthetic_control_method_as_a_tool_0.pdf
    Mittal, A., & Goel, A. (2011). Stock Prediction Using Twitter Sentiment Analysis. Retrieved from http://cs229.stanford.edu/proj2011/GoelMittal-StockMarketPredictionUsingTwitterSentimentAnalysis.pdf
    Mohammed, F. (2017, January 22). How Political Events Change Currency Value. Retrieved May 24, 2019, from JSTOR Daily website: https://daily.jstor.org/how-political-events-change-currency-value/
    Musk, E. [elonmusk]. (2013, March 25). Really exciting @TeslaMotors announcement coming on Thursday. Am going to put my money where my mouth is in v major way. [Tweet]. Retrieved from https://twitter.com/elonmusk/status/316260319360061440?lang=en
    Musk, E. [elonmusk]. (2018, August 7). Am considering taking Tesla private at $420. Funding secured. [Tweet]. Retrieved from https://twitter.com/elonmusk/status/1026872652290379776?lang=en
    NASDAQ. (2019a). AMZN Stock Quote - Amazon.com, Inc. Common Stock Price - Nasdaq. Retrieved June 15, 2019, from https://www.nasdaq.com/symbol/amzn
    NASDAQ. (2019b). HOG Stock Quote - Amazon.com, Inc. Common Stock Price - Nasdaq. Retrieved June 15, 2019, from https://www.nasdaq.com/symbol/hog
    Newport, F. (2018, May 16). Deconstructing Trump’s Use of Twitter. Retrieved May 21, 2019, from Gallup.com website: https://news.gallup.com/poll/234509/deconstructing-trump-twitter.aspx
    Nisar, T. M., & Yeung, M. (2018). Twitter as a tool for forecasting stock market movements: A short-window event study. The Journal of Finance and Data Science, 4(2), 101–119. https://doi.org/10.1016/j.jfds.2017.11.002
    Opatrny, M. (2017). Quantifying the Effects of the CNB’s Exchange Rate Commitment: A Synthetic Control Method Approach. Czech Journal of Economics and Finance (Finance a Uver), 67(6), 539–577. Retrieved from http://journal.fsv.cuni.cz/storage/1396_539_-_577_opatrny_final_issue_6_2017.pdf
    Ossinger, J., & Patterson, M. (2019, May 6). With Two Tweets, Trump Shatters Historic Calm in Global Markets. Bloomberg. Retrieved from https://www.bloomberg.com/news/articles/2019-05-06/with-two-tweets-trump-shatters-historic-calm-in-global-markets
    Ozturk, S. S., & Ciftci, K. (2014). A Sentiment Analysis of Twitter Content as a Predictor of Exchange Rate Movements. Review of Economic Analysis, 6(2), 132–140. Retrieved from https://pdfs.semanticscholar.org/8610/17e7d9c800817409cf81a7a32a24fc78c9fb.pdf
    Pagolu, V. S., Reddy, K. N., Panda, G., & Majhi, B. (2016). Sentiment analysis of Twitter data for predicting stock market movements. 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), 1345–1350. https://doi.org/10.1109/SCOPES.2016.7955659
    Ranco, G., Aleksovski, D., Caldarelli, G., Grčar, M., & Mozetič, I. (2015). The Effects of Twitter Sentiment on Stock Price Returns. PLOS ONE, 10(9), e0138441. https://doi.org/10.1371/journal.pone.0138441
    Rappeport, A. (2019, March 21). How Companies Learned to Stop Fearing Trump’s Twitter Wrath. The New York Times. Retrieved from https://www.nytimes.com/2019/03/20/us/politics/trump-twitter-businesses.html
    Rayarel, K. (2018). The Impact of Donald Trump’s Tweets on Financial Markets (Undergraduate Dissertation). University of Nottingham, Nottingham, United Kingdom. Retrieved from https://www.nottingham.ac.uk/economics/documents/research-first/krishan-rayarel.pdf
    Reuters. (2016, November 14). U.S. Dollar Soars on Bets That Donald Trump Could Spur Inflation. Fortune. Retrieved from http://fortune.com/2016/11/14/donald-trump-victory-dollar-inflation/
    Sanders, C. (2019). yahoofinancials (Version 1.5) [Python]. Retrieved from https://github.com/JECSand/yahoofinancials (Original work published 2017)
    Sherouse, Oliver (2014). Wbdata. Arlington, VA. Available from http://github.com/OliverSherouse/wbdata
    Thielman, S. (2016, December 12). Trump’s tweet about Lockheed-Martin cuts $4bn in value as share prices fall | Business | The Guardian. The Guardian. Retrieved from https://www.theguardian.com/business/2016/dec/12/lockheed-martin-share-prices-donald-trump-tweet
    Tirunillai, S., & Tellis, G. J. (2017). Does Offline TV Advertising Affect Online Chatter? Quasi-Experimental Analysis Using Synthetic Control. Marketing Science, 36(6), 862–878. https://doi.org/10.1287/mksc.2017.1040
    Trump, D. [realdonaldtrump]. (2014, August 5). “SECURE THE BORDER! BUILD A WALL!”. [Twitter Post]. Retrieved from https://twitter.com/realdonaldtrump/status/496756082489171968?lang=en
    Trump, D. [realDonaldTrump]. (n.d.). Donald J. Trump (@realDonaldTrump) / Twitter. Retrieved July 2, 2019, from https://twitter.com/realDonaldTrump
    Trump, D. [realDonaldTrump]. (2016, June 9). “Obama just endorsed Crooked Hillary. He wants four more years of Obama—but nobody else does!”. [Twitter Post]. Retrieved from https://twitter.com/realDonaldTrump/status/740972317191352320
    Trump, D. [realDonaldTrump]. (2018a, June 22). “Based on the Tariffs and Trade Barriers long placed on the U.S. & its great companies and workers by the European Union, if these Tariffs and Barriers are not soon broken down and removed, we will be placing a 20% Tariff on all of their cars coming into the U.S. Build them here!”. [Twitter Post]. Retrieved from https://twitter.com/realdonaldtrump/status/1010320166486454272
    Trump, D. [realDonaldTrump]. (2018b, September 1). “I love Canada, but they’ve taken advantage of our Country for many years!”. [Twitter Post]. Retrieved from https://twitter.com/realdonaldtrump/status/1035850173224824832?lang=en
    Trump, D. [realDonaldTrump. (2019, June 1). “...travesty that is taking place in allowing millions of people to easily meander through their country and INVADE the U.S., not to mention the Drugs & Human Trafficking pouring in through Mexico. Are the Drug Lords, Cartels & Coyotes really running Mexico? We will soon find out! ....U.S. in order to avoid paying the 25% Tariff. Like Mexican companies will move back to the United States once the Tariff reaches the higher levels. They took many of our companies & jobs, the foolish Pols let it happen, and now they will come back unless Mexico stops the.....”. [Twitter Post]. Retrieved from https://twitter.com/realdonaldtrump/status/1134921830773469184?lang=en
    Uhl, M. W. (2017). Emotions Matter: Sentiment and Momentum in Foreign Exchange. Journal of Behavioral Finance, 18(3), 249–257. https://doi.org/10.1080/15427560.2017.1332061
    Vasquez, J. (2018, February 22). In One Tweet, Kylie Jenner Wiped Out $1.3 Billion of Snap’s Market Value. Bloomberg. Retrieved from https://www.bloomberg.com/news/articles/2018-02-22/snap-royalty-kylie-jenner-erased-a-billion-dollars-in-one-tweet
    Vitali, A. (2017, June 7). Trump’s tweets should be taken as official statements, the White House says. NBC News. Retrieved from https://www.nbcnews.com/politics/white-house/trump-s-tweets-official-statements-spicer-says-n768931
    Wagner, K. (2019, February 7). Twitter finally shared how big its daily user base is — and it’s a lot smaller than Snapchat’s. Retrieved May 21, 2019, from Vox website: https://www.vox.com/2019/2/7/18215204/twitter-daily-active-users-dau-snapchat-q4-earnings
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105266009
    Data Type: thesis
    DOI: 10.6814/NCCU201900722
    Appears in Collections:[應用經濟與社會發展英語碩士學位學程 (IMES) ] 學位論文

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