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“Do Trump-Tweets About a Specific Company Affect Stock Returns and Trading Volumes of the Corresponding Industry?”

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“Do Trump-Tweets About a Specific Company Affect Stock Returns and Trading Volumes of the Corresponding Industry?” “Do Trump-tweets about a specific company affect stock returns and trading volumes of the corresponding industry?” Master Thesis Department Finance Furkan Ekinci ANR: 546675 Supervisor: David Hollanders Second reader: Dr. Peter de Goeij Date of completion: 22-10-2017 -2017- “Do Trump-tweets about a specific company affect stock returns and trading volumes of the corresponding industry?” Furkan Ekinci Tilburg University Abstract This research examines whether tweets from US-President Trump about a specific company in the time period 8th November 2016 to 30th April 2017 affect its’ and competitors’ stock prices and trading volumes. This study states that these news-events can be related to companies in the same industry. Thus, the hypothesis that “Trump-tweets” cause abnormal stock prices and trading volumes for mentioned companies and its corresponding industry is tested. The findings demonstrate that when Trump tweets about a specific company, stock prices increase while trading volumes decrease. Keywords: President Trump, tweets, industry, stock prices, trading volumes -2017- Preface This research paper is the last step to achieve my MSc. Finance degree. The last three months I was busy conducting this study. Because of the actuality of the topic, it was really interesting to figure out if the tweeting activity of Trump really affects the stock market. I would like to thank a number of people. Firstly, I would like to thank my supervisor David, without whose feedback my thesis would not be as it is now. Furthermore, I am grateful to my brother, my girlfriend, family, friends and God for always being there for me whenever I needed them, and providing me with the strength I needed to make this study the best possible. Furkan Ekinci Tilburg, October 2017 -2017- TABLE OF CONTENTS INTRODUCTION................................................................................................................ 1 I. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT ....................... 3 Web Data and Financial Data .................................................................................................... 3 Twitter and Trading ..................................................................................................................... 7 Trump, and Twitter as an Information Intermediary .............................................................. 9 Why do Investors React on Tweets: Psychological and Behavioral Approach ................. 10 Intra-industry Information Transfer: Are News Events about one Specific Firm Applicable to Whole Industry? ................................................................................................. 12 II. RESEARCH METHOD ............................................................................................. 16 Sample and Industry Definitions .............................................................................................. 16 Event Study Methodology .......................................................................................................... 18 III. EMPIRICAL RESULTS ............................................................................................ 28 Descriptive Statistics .................................................................................................................. 28 Event Study for Returns ............................................................................................................. 29 Event Study for Volumes ............................................................................................................ 32 Cross Sectional Analysis ........................................................................................................... 35 IV. CONCLUSION ........................................................................................................... 38 REFERENCES .................................................................................................................. 39 Appendix A……………………………………………………………………………… 41 Appendix B……………………………………………………………………………….42 Appendix C……………………………………………………………………………….44 Appendix D……………………………………………………………………………….44 Appendix E………………………………………………………………………………. 46 Appendix F……………………………………………………………………………….47 -2017- INTRODUCTION Twitter is one of the largest microblogging service providers and has shown steady growth over the past few years. Currently, it has more than 317 million active users and it is among the most popular online media services.1 Individuals, including politicians and celebrities, and businesses can communicate and share information via this platform. Since a few years, Twitter has also become an increasingly popular platform used for financial markets. Already known as “Twitter-president” of the United States, Donald J. Trump attracts strong attention in this online platform. In his tweets (messages), he particularly highlights certain companies or industries either in a negative or positive manner, a fact which seems to have an impact on the stock market. According to the Financial Times, a fake tweet about the injury of Obama caused the S&P 500 to decrease within seconds.2 Apparently, Twitter content can have an effect on stock returns. There seems to be a tendency among professional investors to use Twitter sentiment to react on trades. The impact of Trump’s tweets are thought to be that strong that even now an advertising company, named T3, in the United States developed the “Trump and Dump Bot” which analyzes his tweets and trades based on the content of these tweets. There is only limited financial research that examines the relationship between “Trump- tweets” and stock markets. Ge, Kurov and Wolfe (2017) analyze the impact of tweets from President Trump’s official Twitter account that include the name of a publicly traded company. They find that tweets have an impact on stock returns and increase trading volume, volatility and investor attention. However, a deeper explanation whether “Trump-tweets” affect stock returns and trading volumes of the industry as a whole still lacks evidence. Hence, there is a necessity to further investigate this issue. This research focuses on the relationship between tweets from President Trump, and its impact on stock returns and trading volumes of the whole industry. More specifically, it will analyze publicly traded companies appearing in a “Trump-tweet” and corresponding competitors in the same industry. Investors are inclined to associate news about a specific company with competitors. Due to asymmetric information in the market, market participants use the release of new public information about one firm to make valuation inferences about corresponding rival firms in the same industry. First to introduce this issue to financial research is Foster (1981) who examines the impact that a firm’s earnings releases have on the stock 1 https://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/ 2 http://business.time.com/2013/04/24/how-does-one-fake-tweet-cause-a-stock-market-crash/ 1 prices of other firms in its industry. He finds that investors relate news event about a company to the companies’ in the same industry. To my knowledge, this study is first to examine this particular issue. Question to be answered will be whether Trump-tweets’ impact reach not only mentioned companies, but also competitors in the same industry. Results will provide valuable information for investors. Whether or not paying attention and caring about Trump tweets is important for investors to figure out since profit-making strategies can be established. For example, selling the mentioned companies stock, and buying competitors’ stocks could be a possible scenario. Based on prior literature, my expectation is that “Trump-tweets” about a specific publicly traded company will move its and competitors’ stock returns and trading volumes. The main data for this are tweets from Trump, stock prices and trading volumes. Data for “Trump-tweets” are obtained from a tweet archive database for tweets by Trump.3 Data for stock prices and trading volumes are obtained from the Bloomberg Terminal.4 This also counts for data for control variables. Two samples are established based on specific industry definition. The full sample (small sample) is composed of 54 (30) companies.5 The data for tweets, stock prices and trading volumes are collected for beginning of Trump’s presidency (8th November 2016) until 30th April 2017.6 Obtained results of this research indicate that stock prices and trading volumes of companies mentioned in a “Trump-tweet” and competitors are significantly affected. While abnormal trading volumes are significantly negative for both samples, only the small sample (larger companies) shows significantly positive abnormal stock returns. This study is divided into four main chapters: Chapter I gives an overview of the relevant literature and hypothesis. The research method is explained in Chapter II. Chapter III discusses the results of the study and Chapter IV provides the conclusion. 3 http://www.trumptwitterarchive.com/archive 4 Access to Bloomberg is provided by IBS Capital Management BV. 5 All companies are listed in the United States. 6 The ending date 30th April 2017 has been chosen since it was the most current time when this research was written. 2 I. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT Web Data and Financial Data The examination of news-based data and the effect on stock prices is longstanding. There are several different studies investigating the relation between
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