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The allocative effectiveness of market protocols under intelligent trading


Author Info

  • Marco LiCalzi


  • Paolo Pellizzari

    (Department of Applied Mathematics, University of Venice)


We study the performance of four market protocols that lead to allocative efficiency: batch auction, continuous double auction, specialist dealership, and a hybrid of these last two. In a former study, we compared them with respect to several additional performance criteria under the assumption of zero intelligence. This paper analyzes three performance criteria under different ways to remove the assumption of zero intelligence. The following conclusions are robust. The number of wasteful transaction is minimized by the batch auction and the dealership. Moreover, the former minimizes price dispersion and the latter minimizes time to convergence.

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Bibliographic Info

Paper provided by Department of Applied Mathematics, Università Ca' Foscari Venezia in its series Working Papers with number 134.

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Length: 13 pages
Date of creation: May 2006
Date of revision:
Publication status: Published in C. Bruun (ed.), Advances in Artificial Economics, Springer, 2006, 17-29
Handle: RePEc:vnm:wpaper:134

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Keywords: evaluation of market protocols; market design; microstructure; agent-based methodologies;

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  1. Marco LiCalzi & Paolo Pellizzari, 2006. "Simple Market Protocols for Efficient Risk Sharing," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia 136, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  2. Shyam Sunder & MODELS A, 2002. "Markets as Artifacts: Aggregate Efficiency from Zero-Intelligence Traders," Yale School of Management Working Papers, Yale School of Management ysm284, Yale School of Management, revised 01 Sep 2004.
  3. Nicolas Audet & Toni Gravelle & Jing Yang, 2002. "Alternative Trading Systems: Does One Shoe Fit All?," Working Papers, Bank of Canada 02-33, Bank of Canada.
  4. 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, Springer, vol. 5(3), pages 179-208, December.
  5. Smith, Vernon L, 1982. "Microeconomic Systems as an Experimental Science," American Economic Review, American Economic Association, American Economic Association, vol. 72(5), pages 923-55, December.
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Cited by:
  1. Alessandro Cappellini & Gianluigi Ferraris, 2008. "Waiting Times in Simulated Stock Markets," Papers 0802.3291,
  2. Marco LiCalzi & Paolo Pellizzari, 2005. "Simple market protocols for efficient risk sharing," Finance, EconWPA 0504019, EconWPA.
  3. Ladley, Dan & Schenk-Hoppé, Klaus Reiner, 2009. "Do stylised facts of order book markets need strategic behaviour?," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 33(4), pages 817-831, April.
  4. Marco LiCalzi & Paolo Pellizzari, 2008. "Zero-Intelligence Trading without Resampling," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia 164, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  5. Marco LiCalzi & Lucia Milone & Paolo Pellizzari, 2008. "Allocative efficiency and traders' protection under zero intelligence behavior," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia 168, Department of Applied Mathematics, Università Ca' Foscari Venezia, revised Nov 2009.


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