Algorithmic Trade Execution and Intraday Market Dynamics
Department of Mathematics
CFM-Imperial Institute of Quantitative Finance
Imperial College, London
"Optimal execution" algorithms are typically derived assuming an exogenous price process which is unaffected by the trading behavior of market participants. On the other hand, intraday price behavior in electronic markets shows reveals evidence of the price impact of algorithmic order flow, an extreme example being the 'Flash Crashes' repeatedly observed in such markets. We propose a simple model for analyzing the feedback effects which arise in a market where participants attempt to minimize the impact of their trade execution. We show that widely used execution algorithms which aim at reducing market impact of trades can actually lead to unintended synchronization of participants' order flows, increase their market impact and generate large « self-exciting » intraday swings in volume and volatility.
We show that these bursts may occur even in absence of large orders, and leads to a systematic underperformance of 'optimal execution' strategies.
These results call for a critical assessment of "optimal execution" algorithms and points to a notion of order flow toxicity which is distinct from information asymmetry and adverse selection.