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An Agent-based Modeling Approach to Study Price Impact
Author(s)
Date Issued
2012-03-29
Date Available
2012-08-17T15:58:39Z
Abstract
Price impact models are important for devising trade execution strategies. However, a proper characterization of price impacts is still lacking. This study models the price impact using an agent-based modeling approach. The purpose of this paper is to investigate whether agent intelligence is a necessary condition when seeking to construct realistic price impact with an artificial market simulation. We build a zero- intelligence based artificial limit order market model. Our model distinguishes limit orders according to their order aggressiveness and takes into account some observed facts including log-normal distributed order sizes and power-law distributed limit order placements. The model is calibrated using trades and orders data from the London Stock Exchange. The results indicate that agent intelligence is needed when simulating an artificial market where replicating price impact is a concern.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
IEEE Press
Copyright (Published Version)
2012 IEEE
Subject – LCSH
Prices--Computer simulation
Stock exchanges--Computer simulation
Multiagent systems
Language
English
Status of Item
Peer reviewed
Part of
Computational Intelligence for Financial Engineering & Economics (CIFEr), 2012 IEEE Conference on [proceedings]
Conference Details
2012 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, New York, USA, 29-30 March 2012
ISBN
978-1-4673-1802-0
This item is made available under a Creative Commons License
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