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The Strategic Impact of Pace in Double Auction Bargaining

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  • Steven Gjerstad

    (University of Arizona)

Abstract

This paper evaluates performance of human subjects and instances of a bidding model that interact in continuous ­time double auction experiments. Asks submitted by instances of the seller model (``automated sellers'') maximize the seller's expected surplus relative to a heuristic belief function, and arrive stochastically according to an exponential distribution. Automated buyers are similar. Across experiment sessions we vary the exponential distribution parameters of automated sellers and buyers in order to assess the impact of the relative pace of asks and bids on the performance of both human subjects and the automated sellers and buyers. In these experiments, prices converge and allocations converge to efficiency, yet the split of surplus typically differs significantly from the equilibrium split. In order to evaluate the impact of pace, a statistical model is developed in which the relative performance of sellers to buyers is examined as a function of the profile of types present in each experiment session. This econometric model demonstrates that (1) human buyers outperform human sellers, (2) automated sellers and buyers with a longer expected time between asks or bids outperform faster automated sellers and buyers, and (3) the performance of the faster automated buyers is comparable to that of human buyers.

Suggested Citation

  • Steven Gjerstad, 2003. "The Strategic Impact of Pace in Double Auction Bargaining," Microeconomics 0304001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpmi:0304001
    Note: Type of Document - PDF (from LaTeX ); prepared with MikTeX on IBM PC; to print on HP/PostScript/; pages: 36 ; figures: included
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    References listed on IDEAS

    as
    1. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
    2. Cason, Timothy N. & Friedman, Daniel, 1996. "Price formation in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(8), pages 1307-1337, August.
    3. Robert B. Wilson, 1987. "On Equilibria of Bid-Ask Markets," Palgrave Macmillan Books, in: George R. Feiwel (ed.), Arrow and the Ascent of Modern Economic Theory, chapter 11, pages 375-414, Palgrave Macmillan.
    4. 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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    Citations

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    Cited by:

    1. Zhen Zhang & Dave Cliff, 2020. "Market Impact in Trader-Agents: Adding Multi-Level Order-Flow Imbalance-Sensitivity to Automated Trading Systems," Papers 2012.12555, arXiv.org.
    2. Daniel Snashall & Dave Cliff, 2019. "Adaptive-Aggressive Traders Don't Dominate," Papers 1910.09947, arXiv.org.
    3. Henry Hanifan & Ben Watson & John Cartlidge & Dave Cliff, 2021. "Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Traders," Papers 2103.00600, arXiv.org.
    4. Henry Hanifan & John Cartlidge, 2019. "Fools Rush In: Competitive Effects of Reaction Time in Automated Trading," Papers 1912.02775, arXiv.org, revised Nov 2020.
    5. Bradley Miles & Dave Cliff, 2019. "A Cloud-Native Globally Distributed Financial Exchange Simulator for Studying Real-World Trading-Latency Issues at Planetary Scale," Papers 1909.12926, arXiv.org.
    6. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    7. Dave Cliff, 2024. "Parameterised response zero intelligence traders," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 19(3), pages 439-492, July.

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    More about this item

    Keywords

    Double auction; experimental economics; bounded rationality;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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