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Efficiency of continuous double auctions under individual evolutionary learning with full or limited information

Anufriev, Mikhail and Arifovic, Jasmina and Ledyard, John and Panchenko, Valentyn (2013) Efficiency of continuous double auctions under individual evolutionary learning with full or limited information. Journal of Evolutionary Economics, 23 (3). pp. 539-573. ISSN 0936-9937. doi:10.1007/s00191-011-0230-8.

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In this paper we explore how specific aspects of market transparency and agents’ behavior affect the efficiency of the market outcome. In particular, we are interested whether learning behavior with and without information about actions of other participants improves market efficiency. We consider a simple market for a homogeneous good populated by buyers and sellers. The valuations of the buyers and the costs of the sellers are given exogenously. Agents are involved in consecutive trading sessions, which are organized as a continuous double auction with order book. Using Individual Evolutionary Learning agents submit price bids and offers, trying to learn the most profitable strategy by looking at their realized and counterfactual or “foregone” payoffs. We find that learning outcomes heavily depend on information treatments. Under full information about actions of others, agents’ orders tend to be similar, while under limited information agents tend to submit their valuations/ costs. This behavioral outcome results in higher price volatility for the latter treatment. We also find that learning improves allocative efficiency when compared to outcomes Zero-Intelligent traders.

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URLURL TypeDescription DOIArticle
Arifovic, Jasmina0000-0002-7092-6541
Additional Information:© 2011 The Author(s). This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. We are grateful to two referees for their thorough reading of the paper and numerous useful suggestions. We thank the participants of the workshop “Evolution and market behavior in economics and finance” in Pisa, the SCE-2009 conference in Sydney, and the seminars at the University of Amsterdam, University of Auckland, Concordia University, Montreal, Simon Fraser University and the University of Technology, Sydney, for useful comments on earlier drafts of this paper. Mikhail Anufriev acknowledges the financial support by the EU 7th framework collaborative project “Monetary, Fiscal and Structural Policies with Heterogeneous Agents (POLHIA)”, grant no. 225408. Jasmina Arifovic acknowledges financial support from the Social Sciences and Humanities Research Council under the Standard Research Grant Program. Valentyn Panchenko acknowledges the support under Australian Research Council’s Discovery Projects funding scheme (project number DP0986718). Usual caveats apply.
Funding AgencyGrant Number
European Union (EU) 7th Framework Collaborative Project225408
Standard Research Grant Program Social Sciences and Humanities Research CouncilUNSPECIFIED
Australian Research Council Discovery Project funding schemeDP0986718
Subject Keywords:Allocative efficiency; Continuous double auction; Individual evolutionary learning
Issue or Number:3
Classification Code:JEL Classification: D83; C63; D44
Record Number:CaltechAUTHORS:20130815-092245964
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:39940
Deposited By: Tony Diaz
Deposited On:19 Aug 2013 18:30
Last Modified:09 Nov 2021 23:48

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