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A comparison of different trading protocols in an agent-based market

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  • Paolo Pellizzari
  • Arianna Forno

Abstract

We compare price dynamics of different market protocols (batch auction, continuous double auction and dealership) in an agent-based artificial exchange. In order to distinguish the effects of market architectures alone, we use a controlled environment where allocative and informational issues are neglected and agents do not optimize or learn. Hence, we rule out the possibility that the behaviour of traders drives the price dynamics. Aiming to compare price stability and execution quality in broad sense, we analyze standard deviation, excess kurtosis, tail exponent of returns, volume, perceived gain by traders and bid-ask spread. Overall, a dealership market appears to be the best candidate in this respect, generating low volume and volatility, virtually no excess kurtosis and high perceived gain.
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  • 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.
    • Handle: RePEc:spr:jeicoo:v:2:y:2007:i:1:p:27-43
    DOI: 10.1007/s11403-006-0016-5
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    Cited by:

    1. Pellizzari, Paolo & Westerhoff, Frank, 2009. "Some effects of transaction taxes under different microstructures," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 850-863, December.
    2. Francesco Lamperti, 2016. "Empirical Validation of Simulated Models through the GSL-div: an Illustrative Application," LEM Papers Series 2016/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Cappellini, Alessandro & Ferraris, Gianluigi, 2007. "Waiting Times in Simulated Stock Markets," MPRA Paper 7324, University Library of Munich, Germany.
    4. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    6. Kostadinov, Fabian & Holm, Stefan & Steubing, Bernhard & Thees, Oliver & Lemm, Renato, 2014. "Simulation of a Swiss wood fuel and roundwood market: An explorative study in agent-based modeling," Forest Policy and Economics, Elsevier, vol. 38(C), pages 105-118.
    7. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    8. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    9. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.

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