Frequent tweets of the former president of the United States, Donald Trump, provide a unique opportunity to study how financial markets respond to his statements. To do this, we utilize a precise timestamp of each tweet together with high-frequency financial data. We start by analyzing the impact of tweets in general, irrespective of their content. We find that tweets by President Trump are followed by increased uncertainty, increased trading and a decline in the US stock market. We utilize two methods in order to study whether the market reaction depends on the content of the tweets. First, classification of Trump's tweets depending on whether they contain a specific word reveals that market response is particularly negative for tweets containing the words “products” and “tariff”. Second, we use Latent Dirichlet Allocation to affiliate tweets with distinct topics. We find that while most topics do not impact financial markets, the US stock market responds to tweets related to the topic of a “trade war” by price decline, increased trading volume and increased uncertainty. The “trade war” tweets affect other financial markets too, as the Chinese stock market responds to these tweets negatively, while the price of gold responds positively. We illustrate the practical importance of our approach by an automated trading system, which achieves positive abnormal returns.