IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2007-18-4.html

How to Choose the Bidding Strategy in Continuous Double Auctions: Imitation Versus Take-The-Best Heuristics

Author

Abstract

Human-subject market experiments have established in a wide variety of environments that the Continuous Double Auction (CDA) guarantees the maximum efficiency (100 percent) and the transaction prices converge quickly to the competitive equilibrium price. Since in human-subject experiments we can not control the agents' behaviour, one would like to know if these properties (quick price convergence and high market efficiency) hold for alternative agents' bidding strategies. We go a step farther: we substitute human agents by artificial agents to calibrate the agents' behaviour . In this paper we demonstrate that price convergence and allocative market efficiency in CDA markets depend on the proportion of the bidding strategies (Kaplan, Zero-Intelligence Plus, and GD) that agents have on both market sides. As a result, price convergence may not be achieved. The interesting question to ask is: can convergence be assured if the agents choose their bidding strategies? Since humans are frugal we explore two fast & frugal heuristics (imitation versus take-the-best) to choose one of three bidding strategies in order to answer this question. We find that the take-the-best choice performs much better than the imitation heuristic in the three market environments analyzed. Our experiment can be interpreted as a test to see whether an individual learning outperforms social learning or individual rationality (take-the-best) outperforms ecological rationality (imitation), for a given relevant institution (the CDA) in alternative environments.

Suggested Citation

  • Marta Posada & Adolfo López-Paredes, 2007. "How to Choose the Bidding Strategy in Continuous Double Auctions: Imitation Versus Take-The-Best Heuristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(1), pages 1-6.
  • Handle: RePEc:jas:jasssj:2007-18-4
    as

    Download full text from publisher

    File URL: https://www.jasss.org/11/1/6/6.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rosaria Conte & Mario Paolucci, 2001. "Intelligent Social Learning," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(1), pages 1-3.
    2. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
    3. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    4. Huw Dixon & Steven Wallis & Scott Moss, "undated". "Axelrod Meets Cournot: Oligopoly and the Evolutionary Metaphor Part 1," Discussion Papers 95/8, Department of Economics, University of York.
    5. Vernon L. Smith, 2003. "Constructivist and Ecological Rationality in Economics," American Economic Review, American Economic Association, vol. 93(3), pages 465-508, June.
    6. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
    7. Dixon, Huw David & Wallis, Steven & Moss, Scott, 2002. "Axelrod Meets Cournot: Oligopoly and the Evolutionary Metaphor," Computational Economics, Springer;Society for Computational Economics, vol. 20(3), pages 139-156, December.
    8. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70(2), pages 111-111.
    9. Antoni Bosch-DomËnech & Nicolaas J. Vriend, 2003. "Imitation of successful behaviour in cournot markets," Economic Journal, Royal Economic Society, vol. 113(487), pages 495-524, April.
    10. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    11. Smith, Vernon L, 1989. "Theory, Experiment and Economics," Journal of Economic Perspectives, American Economic Association, vol. 3(1), pages 151-169, Winter.
    12. repec:bla:eufman:v:4:y:1998:i:1:p:91-103 is not listed on IDEAS
    13. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    14. Marta Posada & Cesáreo Hernández & Adolfo López-Paredes, 2008. "Testing Marshallian And Walrasian Instability With An Agent-Based Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 249-260.
    15. Shu-Heng Chen & Chung-Ching Tai, 2003. "Trading Restrictions, Price Dynamics And Allocative Efficiency In Double Auction Markets: Analysis Based On Agent-Based Modeling And Simulations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 283-302.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. İlker Yıldırım & Pınar Yolum, 2009. "Hybrid models for achieving and maintaining cooperative symbiotic groups," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 8(2), pages 243-258, December.
    2. Rubén Fuentes-Fernández & Samer Hassan & Juan Pavón & José M. Galán & Adolfo López-Paredes, 2012. "Metamodels for role-driven agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 18(1), pages 91-112, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    2. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    3. Juliette Rouchier, 2013. "The Interest of Having Loyal Buyers in a Perishable Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 151-170, February.
    4. Anufriev, Mikhail & Arifovic, Jasmina & Donmez, Anil & Ledyard, John & Panchenko, Valentyn, 2025. "IEL-CDA model: A more accurate theory of behavior in continuous double auctions," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    5. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    6. 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.
    7. Dixon, Huw D. & Sbriglia, Patrizia & Somma, Ernesto, 2006. "Learning to collude: An experiment in convergence and equilibrium selection in oligopoly," Research in Economics, Elsevier, vol. 60(3), pages 155-167, September.
    8. Itzhak Rasooly, 2022. "Competitive equilibrium and the double auction," Papers 2209.07532, arXiv.org.
    9. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    10. Athreya, Kartik B., 2014. "Big Ideas in Macroeconomics: A Nontechnical View," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262019736, December.
    11. Sean Crockett, 2013. "Price Dynamics In General Equilibrium Experiments," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 421-438, July.
    12. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    13. Cason, Timothy N. & Friedman, Daniel, 1996. "Price formation in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(8), pages 1307-1337, August.
    14. Abigail Devereaux, 2025. "Costs of choice: reformulating price theory without heroic assumptions," Public Choice, Springer, vol. 202(3), pages 455-481, March.
    15. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    16. Tai, Chung-Ching & Chen, Shu-Heng & Yang, Lee-Xieng, 2018. "Cognitive ability and earnings performance: Evidence from double auction market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 409-440.
    17. Großer, Jens & Reuben, Ernesto, 2013. "Redistribution and market efficiency: An experimental study," Journal of Public Economics, Elsevier, vol. 101(C), pages 39-52.
    18. Narine Udumyan & Juliette Rouchier & Dominique Ami, 2014. "Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 199-231, February.
    19. Nicolaisen, James & Petrov, Valentin & Tesfatsion, Leigh S., 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Staff General Research Papers Archive 1952, Iowa State University, Department of Economics.
    20. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jas:jasssj:2007-18-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Francesco Renzini (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.