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Convergence of outcomes and evolution of strategic behavior in double auctions

Author

Listed:
  • Shira Fano

    (Dept. of Applied Mathematics, University of Venice)

  • Marco Li Calzi

    (Dept. of Applied Mathematics and Advanced School of Economics, University of Venice)

  • Paolo Pellizzari

    (Dept. of Applied Mathematics and Advanced School of Economics, University of Venice)

Abstract

We study the emergence of strategic behavior in double auctions with an equal number n of buyers and sellers, under the distinct assumptions that orders are cleared simultaneously or asynchronously. The evolution of strategic behavior is modeled as a learning process driven by a genetic algorithm. We find that, as the size n of the market grows, allocative inefficiency tends to zero and performance converges to the competitive outcome, regardless of the order-clearing rule. The main result concerns the evolution of strategic behavior. Under simultaneous order-clearing, as n increases, only marginal traders learn to be price takers and make offers equal to their valuations/costs. Under asynchronous order-clearing, as n increases, all intramarginal traders learn to be price makers and make offers equal to the competitive equilibrium price. The nature of the order-clearing rule affects in a fundamental way what kind of strategic behavior we should expect to emerge.

Suggested Citation

  • Shira Fano & Marco Li Calzi & Paolo Pellizzari, 2010. "Convergence of outcomes and evolution of strategic behavior in double auctions," Working Papers 196, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:196
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    Cited by:

    1. 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).
    2. Shira Fano & Marco LiCalzi & Paolo Pellizzari, 2013. "Convergence of outcomes and evolution of strategic behavior in double auctions," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 513-538, July.
    3. Michiel Leur & Mikhail Anufriev, 2018. "Timing under individual evolutionary learning in a continuous double auction," Journal of Evolutionary Economics, Springer, vol. 28(3), pages 609-631, August.
    4. Florian Hauser & Marco LiCalzi, 2011. "Learning to Trade in an Unbalanced Market," Lecture Notes in Economics and Mathematical Systems, in: Sjoukje Osinga & Gert Jan Hofstede & Tim Verwaart (ed.), Emergent Results of Artificial Economics, pages 65-76, Springer.
    5. Olga A. Rud & Jean Paul Rabanal, 2018. "Evolution of markets: a simulation with centralized, decentralized and posted offer formats," Journal of Evolutionary Economics, Springer, vol. 28(3), pages 667-689, August.
    6. Paolo Pellizzari, 2011. "Optimal trading in a limit order book using linear strategies," Working Papers 2011_16, Department of Economics, University of Venice "Ca' Foscari", revised Sep 2011.
    7. 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.
    8. 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.
    9. Shira Fano & Paolo Pellizzari, 2011. "Time-Dependent Trading Strategies in a Continuous Double Auction," Lecture Notes in Economics and Mathematical Systems, in: Sjoukje Osinga & Gert Jan Hofstede & Tim Verwaart (ed.), Emergent Results of Artificial Economics, pages 165-176, Springer.
    10. Giulio Bottazzi & Pietro Dindo, 2013. "Evolution and market behavior in economics and finance: introduction to the special issue," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 507-512, July.
    11. 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).
    12. Ruijgrok, Matthijs, 2012. "A single-item continuous double auction game," MPRA Paper 42086, University Library of Munich, Germany.
    13. Jean Paul Rabanal & Olga A. Rabanal, 2015. "A Simulation on the Evolution of Markets: Call Market, Decentralized and Posted Offer," Working Papers 34, Peruvian Economic Association.

    More about this item

    Keywords

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    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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