政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/125989

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/125989

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政大機構典藏 > 社會科學學院 > 應用經濟與社會發展英語碩士學位學程 (IMES) > 學位論文 > Item 140.119/125989

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题名:	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
作者:	孔美玲 Consunji, Margaret A.
贡献者:	楊子霆羅光達 Yang, Tzu-Ting Lo, Kuang-Ta 孔美玲 Consunji, Margaret A.
关键词:	川普合成控制法推特股價匯率 Trump Synthetic Control Method Twitter Stock Prices Exchange Rates
日期:	2019
上传时间:	2019-09-05 17:42:38 (UTC+8)
摘要:	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.
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描述:	碩士國立政治大學應用經濟與社會發展英語碩士學位學程(IMES) 105266009
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0105266009
数据类型:	thesis
DOI:	10.6814/NCCU201900722
显示于类别:	[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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