DocumentCode
1697221
Title
An agent based model of the E-Mini S&P 500 applied to flash crash analysis
Author
Paddrik, Mark ; Hayes, Roy, Jr. ; Todd, Andrew ; Yang, Steve ; Beling, Peter ; Scherer, William
Author_Institution
Univ. of Virginia, Charlottesville, VA, USA
fYear
2012
Firstpage
1
Lastpage
8
Abstract
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.
Keywords
commodity trading; digital simulation; multi-agent systems; securities trading; E-Mini S&P 500 futures market; agent based model; agent based simulation model; flash crash analysis; limit order book; market microstructure; market phenomenon; order placement; order speed; price return; trading class; volatility; zero-intelligence agent-based model; Computer crashes; Contracts; Correlation; Educational institutions; Security; USA Councils; Uninterruptible power systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Financial Engineering & Economics (CIFEr), 2012 IEEE Conference on
Conference_Location
New York, NY
ISSN
PENDING
Print_ISBN
978-1-4673-1802-0
Electronic_ISBN
PENDING
Type
conf
DOI
10.1109/CIFEr.2012.6327800
Filename
6327800
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