Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements
This paper documents that speed is crucially important for high frequency trading strategies based on U.S. macroeconomic news releases. Using order level data of the highly liquid S&P500 ETF traded on NASDAQ from January 6, 2009, to December 12, 2011, we find that a delay of 300 milliseconds (1 second) significantly reduces returns by 3.08% (7.33%) compared to instantaneous execution over all announcements in the sample. This reduction is stronger in case of high impact news and on days with high volatility. In addition, we assess the effect of algorithmic trading on market quality around macroeconomic news. Increases in algorithmic trading activity have a positive (mixed) effect on market quality measures when we use algorithmic trading proxies that capture the top of the orderbook (full orderbook).
|event-based training, highfrequency training, latency costs, macroeconomic news, market activity|
|Financial Markets and the Macroeconomy (jel E44), General Financial Markets: General (jel G10), Information and Market Efficiency; Event Studies (jel G14)|
|Tinbergen Institute Discussion Paper Series|
|Discussion paper / Tinbergen Institute|
|Tinbergen Institute Discussion Paper No. 12-121/III|
Scholtus, M.L, van Dijk, D.J.C, & Frijns, B.P.M. (2012). Speed, Algorithmic Trading, and Market Quality around Macroeconomic News Announcements (No. TI 12-121/III ). Discussion paper / Tinbergen Institute (pp. 1–68). Tinbergen Institute. Retrieved from http://hdl.handle.net/1765/38199