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Individual Rationality and Market Efficiency

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  • Steven Gjerstad
  • Jason M. Shachat

Abstract

The demonstration by Smith [1962] that prices and allocations quickly converge to the competitive equilibrium in the continuous double auction (CDA) was one of the first and remains one of the most important results in experimental economics. His initial experiment, subsequent market experiments, and models of price adjustment and exchange have added considerably to our knowledge of how markets reach equilibrium, and how they respond to disruptions. Perhaps the best known model of exchange in CDA market experiments is the random behavior in the zero-intelligence (ZI) model by Gode and Sunder [1993]. They conclude that even without trader rationality the CDA generates efficient allocations and convergence of transaction prices to the proximity of the theoretical equilibrium price, provided only that agents meet their budget constraints. We demonstrate that by any reasonable measure prices don t converge in their simulations. Their budget constraint requires that a buyer s currency never exceeds her value for the commodity, which is an unnatural restriction. Their conclusion that market efficiency results from the structure of the CDA independent of traders profit seeking behavior rests on their claim that the constraints that they impose are a part of the market institution, but this is not so. We show that they in effect impose individual rationality, which is an aspect of agents' behavior. Researchers on learning in markets have been misled by their interpretation of the ZI simulations, with deleterious effects on the debate on market adjustment processes.

Suggested Citation

  • Steven Gjerstad & Jason M. Shachat, 2007. "Individual Rationality and Market Efficiency," Purdue University Economics Working Papers 1204, Purdue University, Department of Economics.
  • Handle: RePEc:pur:prukra:1204
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    File URL: https://business.purdue.edu/research/Working-papers-series/2007/1204.pdf
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    8. Gjerstad, Steven, 2007. "The competitive market paradox," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1753-1780, May.
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    16. Markose, Sheri & Arifovic, Jasmina & Sunder, Shyam, 2007. "Advances in experimental and agent-based modelling: Asset markets, economic networks, computational mechanism design and evolutionary game dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1801-1807, June.
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    Citations

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    Cited by:

    1. Marco LiCalzi & Paolo Pellizzari, 2008. "Zero-Intelligence Trading Without Resampling," Lecture Notes in Economics and Mathematical Systems, in: Klaus Schredelseker & Florian Hauser (ed.), Complexity and Artificial Markets, chapter 1, pages 3-14, Springer.
    2. Grazzini, J., 2011. "Experimental Based, Agent Based Stock Market," CeNDEF Working Papers 11-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    3. Marco LiCalzi & Lucia Milone & Paolo Pellizzari, 2011. "Allocative Efficiency and Traders’ Protection Under Zero Intelligence Behavior," Dynamic Modeling and Econometrics in Economics and Finance, in: Herbert Dawid & Willi Semmler (ed.), Computational Methods in Economic Dynamics, pages 5-28, Springer.
    4. Giuseppe Attanasi & Samuele Centorrino & Ivan Moscati, 2011. "Double Auction Equilibrium and Efficiency in a Classroom Experimental Search Market," LERNA Working Papers 11.03.337, LERNA, University of Toulouse.
    5. Junhuan Zhang & Peter McBurney & Katarzyna Musial, 2018. "Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 301-352, January.
    6. Brewer, Paul & Ratan, Anmol, 2019. "Profitability, efficiency, and inequality in double auction markets with snipers," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 486-499.
    7. Ross M. Miller, 2012. "The Effect Of Boundary Conditions On Efficiency And Pricing In Double‐Auction Markets With Zero‐Intelligence Agents," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(3), pages 179-188, July.
    8. Daniel Snashall & Dave Cliff, 2019. "Adaptive-Aggressive Traders Don't Dominate," Papers 1910.09947, arXiv.org.
    9. Steven Gjerstad, 2013. "Price dynamics in an exchange economy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 461-500, March.
    10. Mikhail Anufriev & Jasmina Arifovic & John Ledyard & Valentyn Panchenko, 2013. "Efficiency of continuous double auctions under individual evolutionary learning with full or limited information," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 539-573, July.
    11. Zhang, Junhuan, 2018. "Influence of individual rationality on continuous double auction markets with networked traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 353-392.
    12. Jakob Grazzini, 2013. "Information dissemination in an experimentally based agent-based stock market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 179-209, April.
    13. Jakob Grazzini, 2012. "Analysis of the Emergent Properties: Stationarity and Ergodicity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-7.
    14. Anufriev, Mikhail & Arifovic, Jasmina & Ledyard, John & Panchenko, Valentyn, 2022. "The role of information in a continuous double auction: An experiment and learning model," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).

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    More about this item

    Keywords

    Bounded rationality; double auction; exchange economy; experimental economics; market experiment; zero intelligence model;
    All these keywords.

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D51 - Microeconomics - - General Equilibrium and Disequilibrium - - - Exchange and Production Economies

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