We analyze the effects of Algorithmic News Trading (ANT) in the foreign exchange market around the time that the Bank of Japan makes public announcements of its policy decisions. To observe the activity level of ANT, we propose a novel measure based on a web access record to a central bank's webpage. We find that our proposed measure appropriately captures the activity level of ANT. Employing an event study analysis and a VAR analysis, we find that ANT increases market volatility immediately after the monetary policy announcements, and that ANT activity indirectly decreases market liquidity through increasing volatility. In addition, we suggest that ANT trades based on changes in texts on the monetary policy announcements.
Keywords: Algorithmic trading; Monetary policy; Foreign exchange market; News trading; Market microstructure
Views expressed in the paper are those of the authors and do not necessarily reflect those of the Bank of Japan or Institute for Monetary and Economic Studies.