An agent based model of the E-Mini S&P 500 applied to flash crash analysis

We propose a zero-intelligence agent-based model of the E-Mini S&P 500 futures market, which allows for a close examination of the market microstructure. Several classes of agents are characterized by their order speed and order placement within the limit order book. These agents' orders populate the simulated market in a way consistent with real world participation rates. By modeling separate trading classes the simulation is able to capture interactions between classes, which are essential to recreating market phenomenon. The simulated market is validated against empirically observed characteristics of price returns and volatility. We therefore conclude that our agent based simulation model can accurately capture the key characteristics of the nearest months E-Mini S&P 500 futures market. Additionally, to illustrate the applicability of the simulation, experiments were run, which confirm the leading hypothesis for the cause of the May 6th 2010 Flash Crash.

[1]  J. Farmer,et al.  The power of patience: a behavioural regularity in limit-order placement , 2002, cond-mat/0206280.

[2]  Michael J. North,et al.  Toward teaching agent-based simulation , 2010, Proceedings of the 2010 Winter Simulation Conference.

[3]  Damien Challet,et al.  Analyzing and modeling 1+1d markets , 2001 .

[4]  S. Maslov Simple model of a limit order-driven market , 1999, cond-mat/9910502.

[5]  T. Swan,et al.  ECONOMIC GROWTH and CAPITAL ACCUMULATION , 1956 .

[6]  B. Mandlebrot The Variation of Certain Speculative Prices , 1963 .

[7]  M. Mézard,et al.  Statistical properties of stock order books: empirical results and models , 2002, cond-mat/0203511.

[8]  A. Kyle,et al.  The Flash Crash: The Impact of High Frequency Trading on an Electronic Market , 2011 .

[9]  Clara Vega,et al.  Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market , 2009 .

[10]  Szabolcs Mike,et al.  An Empirical Behavioral Model of Liquidity and Volatility , 2007, 0709.0159.

[11]  Gilles Teyssière,et al.  Microeconomic Models for Long Memory in the Volatility of Financial Time Series , 2001 .

[12]  Alex Kulesza,et al.  Empirical Limitations on High-Frequency Trading Profitability , 2010, The Journal of Trading.

[13]  Alex Kulesza,et al.  Empirical Limitations on High Frequency Trading Profitability , 2010, 1007.2593.

[14]  Angelo Ranaldo,et al.  Order aggressiveness in limit order book markets , 2004 .

[15]  Kimmo Kaski,et al.  Characteristic times in stock market indices , 1999 .