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Interaction of Human and Artificial Agents on Double Auction Markets - Simulations and Laboratory Experiments

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  • Carsten Schmidt

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  • Jens Grossklags

Abstract

This paper provides an overview on the simulations and experiments we have done in order to better understand human-agent interaction in a market environment. We find that the introduction of software agents does not necessarily induce a more efficient market. More surprisingly, information on the existence of software agents in the market environment results in more efficient behavior of human traders.

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File URL: ftp://papers.econ.mpg.de/esi/discussionpapers/2003-22.pdf
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Bibliographic Info

Paper provided by Max Planck Institute of Economics, Strategic Interaction Group in its series Papers on Strategic Interaction with number 2003-22.

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Length: 4 pages
Date of creation: Feb 2004
Date of revision:
Handle: RePEc:esi:discus:2003-22

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References

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  1. 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.
  2. Rust, John & Miller, John H. & Palmer, Richard, 1994. "Characterizing effective trading strategies : Insights from a computerized double auction tournament," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 61-96, January.
  3. Gjerstad, Steven & Dickhaut, John, 1998. "Price Formation in Double Auctions," Games and Economic Behavior, Elsevier, vol. 22(1), pages 1-29, January.
  4. Gro├čklags, Jens & Schmidt, Carsten & Siegel, Jonathan, 2000. "Dumb software agents on an experimental asset market," SFB 373 Discussion Papers 2000,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  5. Reinhard Selten & Michael Mitzkewitz & Gerald R. Uhlich, 1997. "Duopoly Strategies Programmed by Experienced Players," Econometrica, Econometric Society, vol. 65(3), pages 517-556, May.
  6. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 111.
  7. Leland, Hayne & Rubinstein, Mark, 1988. "Comments on the Market Crash: Six Months After," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 45-50, Summer.
  8. Axel Ockenfels & Alvin E. Roth, 2001. "The Timing of Bids in Internet Auctions: Market Design, Bidder Behavior, and Artificial Agents," Papers on Strategic Interaction 2002-33, Max Planck Institute of Economics, Strategic Interaction Group.
  9. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-61, December.
  10. 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 119-37, February.
  11. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 83-110, May.
  12. Abreu, Dilip & Rubinstein, Ariel, 1988. "The Structure of Nash Equilibrium in Repeated Games with Finite Automata," Econometrica, Econometric Society, vol. 56(6), pages 1259-81, November.
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Cited by:
  1. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Society for Computational Economics, vol. 28(4), pages 313-331, November.
  2. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Society for Computational Economics, vol. 28(1), pages 51-69, August.

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