Nobody would argue that nowadays, we live in an information-rich society — the amount of available information (data) is constantly rising, and news is becoming more accessible and frequent. It is indisputable that this evolvement has also affected financial markets. Machine learning algorithms can chew up big chunks of data. We can analyze the sentiment (which is frequently related to the news). Big data does not seem to be a problem anymore, and high-frequent trading algorithms can react almost instantly. But how important is the news? Kerssenfischer and Schmeling (2021) provide several answers by studying the impact of scheduled and unscheduled news (frequently omitted in other news-related studies) in connection with high-frequency changes in bond yields and stock prices in the EU and US as well. The research points out that the effect is tremendous and significant. According to the researchers, roughly half of all stock and bond movements in the US and EU happen around identifiable unscheduled (such as Covid spread or Lehman Brothers bankruptcy) or scheduled (FOMC meetings, macro announcements, etc.) news. Apart from identifying the most important news, the research also shows that monetary policy surprises might not be as surprising as they seem since they are predictable. Furthermore, most central bank announcements cause a lower comovement in stocks and bonds. Overall, the research provides an excellent piece of information for both practitioners and academics and helps us better understand the impact and magnitude of news. — The Encyclopedia of Quantitative and Algorithmic Trading Strategies