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Simple market protocols for efficient risk sharing

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  • Marco LiCalzi

    (University of Venice, Italy)

  • Paolo Pellizzari

    (University of Venice, Italy)

Abstract

This paper studies the performance of four market protocols with regard to allocative efficiency and other performance criteria such as volume or volatility. We examine batch auctions, continuous double auctions, specialist dealerships, and a hybrid of these last two. All protocols are practically implementable because the space of messages for traders is simple. We test the protocols by running (computerized) experiments in an environment that controls for traders’ behavior and rules out any informational effect. We find that all protocols generically converge to the efficient allocation in finite time. An extended comparison over other performance criteria produces no clear winner, but the presence of a specialist is clearly associated with the best all-round performance.

Suggested Citation

  • Marco LiCalzi & Paolo Pellizzari, 2005. "Simple market protocols for efficient risk sharing," Finance 0504019, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0504019
    Note: Type of Document - pdf; pages: 29. 29-page PDF document submitted via ftp
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    References listed on IDEAS

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    8. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    9. Marco LiCalzi & Paolo Pellizzari, 2006. "The Allocative Effectiveness of Market Protocols Under Intelligent Trading," Lecture Notes in Economics and Mathematical Systems, in: Charlotte Bruun (ed.), Advances in Artificial Economics, chapter 2, pages 17-29, Springer.
    10. 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.
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    Cited by:

    1. Iryna Veryzhenko & Arthur Jonath & Etienne Harb, 2020. "Non-Value-Added Tax to Improve Market Fairness," Working Papers hal-02881064, HAL.
    2. Iryna Veryzhenko & Arthur Jonath & Etienne Harb, 2022. "Non-Value-Added Tax to improve market fairness and quality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-30, December.
    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. 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.
    5. Ladley, Dan & Schenk-Hoppé, Klaus Reiner, 2009. "Do stylised facts of order book markets need strategic behaviour?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 817-831, April.
    6. 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.
    7. Paolo Pellizzari & Arianna Forno, 2007. "A comparison of different trading protocols in an agent-based market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(1), pages 27-43, June.
    8. Paolo Pellizzari, 2008. "The Toll of Subrational Trading in an Agent Based Economy," Research Paper Series 217, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Marco LiCalzi & Paolo Pellizzari, 2006. "The Allocative Effectiveness of Market Protocols Under Intelligent Trading," Lecture Notes in Economics and Mathematical Systems, in: Charlotte Bruun (ed.), Advances in Artificial Economics, chapter 2, pages 17-29, Springer.
    10. Anufriev, Mikhail & Panchenko, Valentyn, 2009. "Asset prices, traders' behavior and market design," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1073-1090, May.
    11. Nathalie Oriol & Iryna Veryzhenko, 2019. "Market structure or traders' behavior? A multi agent model to assess flash crash phenomena and their regulation," Quantitative Finance, Taylor & Francis Journals, vol. 19(7), pages 1075-1092, July.

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    More about this item

    Keywords

    market microstructure; allocative efficiency; comparison of market institutions; agent-based simulations.;
    All these keywords.

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other

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