Quantpedia’s team reviews the academic paper “What Moves Markets?” by Mark Kerssenfischer and Maik Schmeling. Read an excerpt below.
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. 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.
Authors: Mark Kerssenfischer and Maik Schmeling
Title: What Moves Markets?
Abstract: What share of asset price movements is driven by news? We attempt to answer this question by building a large, time-stamped event database covering scheduled macroeconomic data releases, central bank announcements, bond auctions, as well as unscheduled news such as election results, sovereign rating downgrades, and natural catastrophes. We combine this news database with high-frequency stock price and bond yield changes, both for the United States and the euro area, going back to 2002. We find that news events account for about 50% of all market movements, suggesting that a much larger amount of return variation than previously thought can be traced back to observable news. Finally, we use our news database to quantify the share of asset price variation due to different types of news, to study the predictability of monetary policy surprises, and to dissect changes in the stock-bond correlation.
As always we present some interesting figures:
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