IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/164.html
   My bibliography  Save this paper

Zero-Intelligence Trading without Resampling

Author

Listed:
  • Marco LiCalzi

    () (Department of Applied Mathematics, University of Venice)

  • Paolo Pellizzari

    () (Department of Applied Mathematics, University of Venice)

Abstract

This paper studies the consequences of removing the resampling assumption from the zero-intelligence trading model in Gode and Sunder (1993). We obtain three results. First, individual rationality is no longer sufficient to attain allocative effciency in a continuous double auction; hence, the rules of the market matter. Second, the allocative effciency of the continuous double auction is higher than for other sequential protocols both with or without resampling. Third, compared to zero intelligence, the effect of learning on allocative effciency is sharply positive without resampling and mildly negative with resampling.

Suggested Citation

  • Marco LiCalzi & Paolo Pellizzari, 2008. "Zero-Intelligence Trading without Resampling," Working Papers 164, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpaper:164
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2008wp164.pdf
    File Function: First version, 2008
    Download Restriction: no

    References listed on IDEAS

    as
    1. LiCalzi, Marco & Pellizzari, Paolo, 2007. "Simple market protocols for efficient risk sharing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3568-3590, November.
    2. Hurwicz, Leonid & Radner, Roy & Reiter, Stanley, 1975. "A Stochastic Decentralized Resource Allocation Process: Part I," Econometrica, Econometric Society, vol. 43(2), pages 187-221, March.
    3. Marco LiCalzi & Paolo Pellizzari, 2007. "Which market protocols facilitate fair trading?," Working Papers 151, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    4. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
    5. 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.
    6. Paul Brewer & Maria Huang & Brad Nelson & Charles Plott, 2002. "On the Behavioral Foundations of the Law of Supply and Demand: Human Convergence and Robot Randomness," Experimental Economics, Springer;Economic Science Association, vol. 5(3), pages 179-208, December.
    7. Steven Gjerstad & Jason M. Shachat, 2007. "Individual Rationality and Market Efficiency," Purdue University Economics Working Papers 1204, Purdue University, Department of Economics.
    8. Marco LiCalzi & Paolo Pellizzari, 2006. "The allocative effectiveness of market protocols under intelligent trading," Working Papers 134, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    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. Marco LiCalzi & Lucia Milone & Paolo Pellizzari, 2008. "Allocative efficiency and traders' protection under zero intelligence behavior," Working Papers 168, Department of Applied Mathematics, Università Ca' Foscari Venezia, revised Nov 2009.
    2. 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, pages 539-573.
    3. Florian Hauser & Marco LiCalzi, 2011. "Learning to trade in an unbalanced market," Working Papers 2, Department of Management, Università Ca' Foscari Venezia.
    4. 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.

    More about this item

    JEL classification:

    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • D51 - Microeconomics - - General Equilibrium and Disequilibrium - - - Exchange and Production Economies
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:vnm:wpaper:164. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marco LiCalzi). General contact details of provider: http://edirc.repec.org/data/dmvenit.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.