Adaptive Traders and the Design of Financial Markets



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    • University of Toulouse, Institut d'Administration des Entreprises and CRG. I would like to thank Klaus Adam, Vikas Agarwal, Bruno Biais, Stefano Lovo, Lalitha Naveen, Anand Venkateswaran, participants at the 2003 Joint Conference on Information Sciences in Cary, NC, and especially Catherine Casamatta and Naveen Daniel for helpful comments and discussions. I am also grateful to an anonymous referee, an anonymous associate editor, and the Editor, Robert Stambaugh, for their suggestions. Part of this research was done while I was an assistant professor of Finance at the Robinson College of Business, Georgia State University. The financial support of the College is gratefully acknowledged. Anna Agapova and Costanza Meneghetti provided excellent research assistance on part of this paper.


This paper studies a financial market populated by adaptive traders. Learning is modeled following Camerer and Ho (1999). A call market and a Walrasian tatonnement are compared in an environment in which both institutions have the same Nash and competitive equilibrium outcomes. When traders learn via a belief-based model, equilibrium is discovered in both types of markets. In contrast, when traders learn via a reinforcement-based model, convergence to equilibrium is achieved in the Walrasian tatonnement but not in the call market. This paper suggests that market mechanisms can be designed to foster traders' learning of equilibrium strategies.