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Profitability, efficiency, and inequality in double auction markets with snipers

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  • Brewer, Paul
  • Ratan, Anmol

Abstract

This research builds upon two early efforts to explore robot trading strategies within the double auction market: (1) Gode and Sunder's Zero Intelligence robots, a simple, loss-avoiding, random, persistent, liquidity-providing strategy that produced, in double auction markets, high efficiency of allocation and market price convergence (within-period) towards the predictions of competitive theory; and (2) an entirely parasitic version of Todd Kaplan's Snipers, a simple, loss-avoiding, deterministic, liquidity-removing strategy. The original version of Kaplan's Snipers achieved the highest profit in an early tournament (the Santa Fe Double Auction Tournament) in part by accepting others’ orders when there was an excellent price, a low bid-ask spread, or time was running out. As we increase the proportion of snipers in a market, we find that sniping is not generally superior to the ZI strategy and that the snipers’ parasitic and end-of-period behaviors eventually cause extreme price variance and divergence from competitive equilibrium, lower market efficiencies, and rising Gini coefficients of inequality. Our results contrast with earlier claims by Gode and Sunder and others that double auction market efficiency and convergence to competitive equilibria are market properties relatively insensitive to agent strategies. Instead, we find a need to consider agent strategy in explaining how our market outcomes differ from those previously obtained either by Gode and Sunder or by Kaplan's successful tournament entry. Specifically, the interaction of parasitic sniper strategies creates a trading constraint: snipers will never trade with each other. These strategy-induced trading constraints force the standard market efficiency metric lower as the sniper population rises.

Suggested Citation

  • Brewer, Paul & Ratan, Anmol, 2019. "Profitability, efficiency, and inequality in double auction markets with snipers," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 486-499.
  • Handle: RePEc:eee:jeborg:v:164:y:2019:i:c:p:486-499
    DOI: 10.1016/j.jebo.2019.06.017
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    References listed on IDEAS

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    1. Paola Tubaro, 2009. "Is individual rationality essential to market price formation? The contribution of zero-intelligence agent trading models," Journal of Economic Methodology, Taylor & Francis Journals, vol. 16(1), pages 1-19.
    2. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 322-322.
    3. Alvin E. Roth & Axel Ockenfels, 2002. "Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet," American Economic Review, American Economic Association, vol. 92(4), pages 1093-1103, September.
    4. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
    5. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    6. Vernon L. Smith, 1965. "Experimental Auction Markets and the Walrasian Hypothesis," Journal of Political Economy, University of Chicago Press, vol. 73, pages 387-387.
    7. Steven Gjerstad & Jason M. Shachat, 2007. "Individual Rationality and Market Efficiency," Purdue University Economics Working Papers 1204, Purdue University, Department of Economics.
    8. Bossaerts, Peter & Plott, Charles R., 2008. "From Market Jaws to the Newton Method: The Geometry of How a Market Can Solve Systems of Equations," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 2, pages 22-24, Elsevier.
    9. Friedman, Daniel, 1991. "A simple testable model of double auction markets," Journal of Economic Behavior & Organization, Elsevier, vol. 15(1), pages 47-70, January.
    10. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    11. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    12. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, Oxford University Press, vol. 130(4), pages 1547-1621.
    13. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    14. 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.
    15. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    16. 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;Economic Science Association, vol. 5(3), pages 179-208, December.
    17. Catherine C. Eckel & Daniel Houser & Peter J. Boettke, 2017. "A Celebration of Vernon Smith's 90th Birthday and Lifetime Contributions to Economics, Southern Economic Association, 2016," Southern Economic Journal, John Wiley & Sons, vol. 83(3), pages 639-643, January.
    18. Kimbrough, Erik O. & Smyth, Andrew, 2018. "Testing the boundaries of the double auction: The effects of complete information and market power," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 372-396.
    19. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, September.
    20. Paul Brewer & Jaksa Cvitanic & Charles R. Plott, 2013. "Market microstructure design and flash crashes: A simulation approach," Journal of Applied Economics, Universidad del CEMA, vol. 16, pages 223-250, November.
    21. Brewer, Paul J., 2008. "Zero-Intelligence Robots and the Double Auction Market: A Graphical Tour," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 4, pages 31-45, Elsevier.
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