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Learning to trade in an unbalanced market


Author Info

  • Florian Hauser

    (Department of Banking and Finance, Universitat Innsbruck)

  • Marco LiCalzi

    (Department of Management, Università Ca' Foscari Venezia)


We study the evolution of trading strategies in double auctions as the size of the market gets larger. When the number of buyers and sellers is balanced, Fano et al. (2011) show that the choice of the order-clearing rule (simultaneous or asynchronous) steers the emergence of fundamentally different strategic behavior. We extend their work to unbalanced markets, confirming their main result as well as that allocative inefficiency tends to zero. On the other hand, we discover that convergence to the competitive outcome takes place only when the market is large and that the long side of the market is more effective at improving its disadvantaged terms of trade under asynchronous order-clearing.

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Bibliographic Info

Paper provided by Department of Management, Università Ca' Foscari Venezia in its series Working Papers with number 2.

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Length: 23 pages
Date of creation: Apr 2011
Date of revision:
Publication status: Published in S. Osinga, G.J. Hofstede, and T. Verwaart (eds.), Emergent Results of Artificial Economics, Springer, 2011, 65-76
Handle: RePEc:vnm:wpdman:2

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Related research

Keywords: Trading protocols; Market design; Allocative efficiency; Genetic Programming;

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  1. Gode, Dhananjay K & Sunder, Shyam, 1997. "What Makes Markets Allocationally Efficient?," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 112(2), pages 603-30, May.
  2. Shira Fano & Marco Li Calzi & Paolo Pellizzari, 2010. "Convergence of outcomes and evolution of strategic behavior in double auctions," Working Papers, Department of Applied Mathematics, Università Ca' Foscari Venezia 196, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  3. 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.
  4. 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, Springer, vol. 23(3), pages 539-573, July.
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