How is the stock exchange index affected by the disclosures of politicians?

Abstract

The main purpose of this study is to understand the main influence of the politicians’ disclosure on the stock exchange index. In this context, a machine learning model is built in order to understand the hidden patterns behind the daily changes (rises and falls) of Dow Johns index. In the fourth chapter of this book, Donald Trump’s personal tweets are obtained to make evaluations. Similarly, in the analysis process of this chapter, these tweets and four-day time series Dow Johns industrial average values are taken into consideration. The findings show that when Mr. Trump uses the word witch at least once, it is certain that the index will rise. On the other side, when he uses both the word military and witch on the same day, the index gets a steep high. These results give an idea that when politicians use negative words, it increases the volatility in the stock market. Similar to this situation, if their disclosures are related to military issues, the stock exchange will also be influenced. Therefore, it is strongly recommended that politicians should choose their words carefully in order not to increase the volatility in the stock market.