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The allocative effectiveness of market protocols under intelligent trading

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Author Info

  • Marco LiCalzi

    ()

  • Paolo Pellizzari

    (Department of Applied Mathematics, University of Venice)

Abstract

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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Related research

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

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References

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  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. Nicolas Audet & Toni Gravelle & Jing Yang, 2002. "Alternative Trading Systems: Does One Shoe Fit All?," Working Papers 02-33, Bank of Canada.
  3. 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, vol. 5(3), pages 179-208, December.
  4. Smith, Vernon L, 1982. "Microeconomic Systems as an Experimental Science," American Economic Review, American Economic Association, vol. 72(5), pages 923-55, December.
  5. Shyam Sunder & MODELS A, 2002. "Markets as Artifacts: Aggregate Efficiency from Zero-Intelligence Traders," Yale School of Management Working Papers ysm284, Yale School of Management, revised 01 Sep 2004.
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Cited by:
  1. Dan Ladley & Klaus Reiner Schenk-Hoppe, 2007. "Do Stylised Facts of Order Book Markets Need Strategic Behaviour?," Swiss Finance Institute Research Paper Series 07-20, Swiss Finance Institute.
  2. Marco LiCalzi & Paolo Pellizzari, 2008. "Zero-Intelligence Trading without Resampling," Working Papers 164, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  3. Alessandro N. Cappellini & Gianluigi Ferraris, 2009. "Waiting Times In Simulated Stock Markets," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 195-206.
  4. Marco LiCalzi & Paolo Pellizzari, 2005. "Simple market protocols for efficient risk sharing," Finance 0504019, EconWPA.
  5. 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.

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