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Rate of Return Parity with Robot Asset Traders

  • Jason Childs

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    Human populated experimental asset markets produce data with two major qualitative consistencies; finite price bubbles and rate of return parity. Robot traders following different behavioural rules are used to create data that is qualitatively similar to that produced by human subjects in a laboratory setting. A trend pricing component of behaviour is required for robots to generate finite price bubbles. A single arbitrageur in combination with trend pricing and simple profit maximization is required to generate rate of return parity. Copyright Springer Science+Business Media, LLC 2007

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    File URL: http://hdl.handle.net/10.1007/s10614-006-9060-4
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    Article provided by Society for Computational Economics in its journal Computational Economics.

    Volume (Year): 29 (2007)
    Issue (Month): 1 (February)
    Pages: 1-12

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    Handle: RePEc:kap:compec:v:29:y:2007:i:1:p:1-12
    Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=100248

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    1. Jason Childs & Stuart Mestelman, 2006. "Rate-of-return Parity in Experimental Asset Markets," Review of International Economics, Wiley Blackwell, vol. 14(3), pages 331-347, 08.
    2. Robert Moir, 1998. "A Monte Carlo Analysis of the Fisher Randomization Technique: Reviving Randomization for Experimental Economists," Experimental Economics, Springer, vol. 1(1), pages 87-100, June.
    3. Youssefmir, Michael & Huberman, Bernardo A & Hogg, Tad, 1998. "Bubbles and Market Crashes," Computational Economics, Society for Computational Economics, vol. 12(2), pages 97-114, October.
    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 119-37, February.
    5. Sunder, S., 1992. "Experimental Asset Markets: A Survey," GSIA Working Papers 1992-19, Carnegie Mellon University, Tepper School of Business.
    6. Gode, D.K. & Sunder, S., 1991. "Allocative Efficiency of Markets with Zero Intelligence (Z1) Traders: Market as a Partial Substitute for Individual Rationality," GSIA Working Papers 1992-16, Carnegie Mellon University, Tepper School of Business.
    7. Steiglitz, Ken & Shapiro, Daniel, 1998. "Simulating the Madness of Crowds: Price Bubbles in an Auction-Mediated Robot Market," Computational Economics, Society for Computational Economics, vol. 12(1), pages 35-59, August.
    8. Timothy N. Cason & Daniel Friedman, 1997. "Price Formation in Single Call Markets," Econometrica, Econometric Society, vol. 65(2), pages 311-346, March.
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