Order Dynamics in a High-Frequency Trading Environment
University of Hohenheim
affiliation not provided to SSRN
July 14, 2011
We analyse order book message data in order to detect algorithmic trade activity. Previous papers usually analyse order book data with a time stamp precision of one hundredth of a second. In times of co-location, those levels of precision are not sufficient to see effects of ultra-high frequency algorithms. Our Nasdaq-supplied dataset is equipped with a time stamp precision of a billionth of a second. Thus, we 'zoom in' and analyse the sub-millisecond effects of algorithmic trading on the order book. We find evidence of algorithmic trading with the limit order lifetime, limit order revision time, and inter order placement time. In addition to that, we apply the proxies separately on exchange-traded funds and stocks to see if structured products are treated differently than common stocks.
Keywords: Algorithmic Trading, High-Frequency Trading, Order Dynamics, Microseconds
JEL Classification: G10, G29working papers series
Date posted: June 22, 2012 ; Last revised: February 24, 2013
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