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Aggregation and dissemination of information in experimental asset markets in the presence of a manipulator

  • Helena Veiga

    ()

  • Marc Vorsatz

    ()

We study with the help of a laboratory experiment the conditions under which an uninformed manipulator - a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on - is able to induce higher asset prices. We find that the average contract price is significantly higher in the presence of the manipulator if, and only if, the asset takes the lowest possible value and insiders have perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains; i.e., independently on whether the informed traders have perfect or partial information, it earns always more than the average trader. Finally, not only uninformed subjects suffer from the presence of the robot trader, but also some of the imperfectly informed insiders have lower payoffs once the robot trader is added as a market participant.

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws084110.

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Date of creation: Sep 2008
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Handle: RePEc:cte:wsrepe:ws084110
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  1. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Discussion Papers 03-025, Stanford Institute for Economic Policy Research.
  2. Camerer, Colin & Weigelt, Keith, 1991. "Information Mirages in Experimental Asset Markets," The Journal of Business, University of Chicago Press, vol. 64(4), pages 463-93, October.
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  4. Colin Camerer, 1998. "Can asset markets be manipulated? A field experiment with racetrack betting," Natural Field Experiments 00222, The Field Experiments Website.
  5. Plott, Charles R. & Sunder, Shyam., . "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational Expectations Models," Working Papers 331, California Institute of Technology, Division of the Humanities and Social Sciences.
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  11. Archishman Chakraborty & Bilge Yilmaz, 2008. "Microstructure Bluffing with Nested Information," American Economic Review, American Economic Association, vol. 98(2), pages 280-84, May.
  12. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 2010. "A theory of Fads, Fashion, Custom and cultural change as informational Cascades," Levine's Working Paper Archive 1193, David K. Levine.
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  17. Itay Goldstein & Alexander Guembel, 2008. "Manipulation and the Allocational Role of Prices," Review of Economic Studies, Oxford University Press, vol. 75(1), pages 133-164.
  18. Veiga Helena & Vorsatz Marc, 2006. "Price Manipulation in an Experimental Asset Market," Research Memorandum 024, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  19. Sunder, S., 1989. "Market For Information: Experimental Evidence," GSIA Working Papers 88-89-53, Carnegie Mellon University, Tepper School of Business.
  20. Benabou, Roland & Laroque, Guy, 1992. "Using Privileged Information to Manipulate Markets: Insiders, Gurus, and Credibility," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 921-58, August.
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