Agent Based Model of the E-Mini S&P 500 Future: Application for Policy Making

Proceedings of the 2012 Winter Simulation Conference

12 Pages Posted: 19 Jul 2012 Last revised: 20 Jun 2013

See all articles by Roy Hayes

Roy Hayes

University of Virginia

Mark E. Paddrik

Government of the United States of America - Office of Financial Research

Andrew Todd

University of Virginia

Steve Y. Yang

Stevens Institute of Technology

Peter Beling

University of Virginia, Dept. of System & Information Engineering

William Scherer

IEEE Intelligent Transportation Systems Society

Date Written: 2012

Abstract

An agent-based model (ABM) has a structure, which includes a set of agents, a topology and an environment. A simplified conception of a financial market includes a set of market participants, a trading mechanism, and a set of securities. In a typical ABM of a financial market, the market participants are agents, the market mechanism is the topology and the exogenous flow of information into the market is the environment. A zero-intelligence ABM model of the E-Mini Futures Market is presented. Several classes of agents are characterized by their speed and placement of orders within the limit order book. The proposed minimum quote life rule is implemented in the simulation. The minimum quote life rule prevents new orders from being cancelled or modified before a given time limit. Through experimentation, trade-off curves are generated. Thereby, illustrating the usefulness of this ABM and its ability to inform ongoing financial policy debates.

Keywords: Agent Based Model, Agent, E-MINI S&P 500, Minimum Quote Life, Policy, Rule Making

Suggested Citation

Hayes, Roy Lee and Paddrik, Mark Endel and Todd, Andrew and Yang, Steve Y. and Beling, Peter and Scherer, William, Agent Based Model of the E-Mini S&P 500 Future: Application for Policy Making (2012). Proceedings of the 2012 Winter Simulation Conference. Available at SSRN: https://ssrn.com/abstract=2112139 or http://dx.doi.org/10.2139/ssrn.2112139

Roy Lee Hayes (Contact Author)

University of Virginia ( email )

United States

Mark Endel Paddrik

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Andrew Todd

University of Virginia ( email )

1400 University Ave
Charlottesville, VA 22903
United States

Steve Y. Yang

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

Peter Beling

University of Virginia, Dept. of System & Information Engineering ( email )

1400 University Ave
Charlottesville, VA 22903
United States

William Scherer

IEEE Intelligent Transportation Systems Society

United States

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