Investor Attention and Twitter
Are Donald Trump's company-related tweets capturing investors' attention?
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Bachelor Thesis from the year 2021 in the subject Business economics - Business Management, Corporate Governance, grade: 1,7, University of Hohenheim (Financial Management), course: Risikomanagement, language: English, abstract: This thesis focuses on the impact of Trump's company-related tweets on the attention of retail investors. In this context, the main research question is whether Trump's tweets clearly have a triggering effect on retail investors attention and whether this financial attention can be measured with the help of direct proxies. This thesis is organized as follows. The first...
Bachelor Thesis from the year 2021 in the subject Business economics - Business Management, Corporate Governance, grade: 1,7, University of Hohenheim (Financial Management), course: Risikomanagement, language: English, abstract: This thesis focuses on the impact of Trump's company-related tweets on the attention of retail investors. In this context, the main research question is whether Trump's tweets clearly have a triggering effect on retail investors attention and whether this financial attention can be measured with the help of direct proxies. This thesis is organized as follows. The first chapter deals with the underlying theory and findings from previous research. Here, the first part presents a precise and clear definition of the concept of financial attention. Thereby, it is relevant to distinguish that it only refers to financial attention and not to attention per se. In the second part of the first chapter, direct and indirect proxies are presented and critically examined. As the research question relates to measurements for direct proxies, various direct attention measures are presented and evaluated. In addition, previous work examines how direct proxies can be applied as a measure of IPO events. The second chapter deals with data collection and methodology. In this process, company-related tweets from Donald Trump's Twitter account are collected and classified into a positive or negative tone. After that the SVI for the affected companies is searched on Google Trends. Subsequently, using a regression analysis in excel, the empirical relationship is examined. After describing and highlighting the results, the conclusion critically discusses the findings and offers suggestions for future work.
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