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Genetic learning as an explanation of stylized facts of foreign exchange markets

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  • Lux, Thomas
  • Schornstein, Sascha

Abstract

This paper revisits the Kareken-Wallace model of exchange rate formation in a two-country overlapping generations world. Following the seminal paper by Arifovic (Journal of Political Economy, 104, 1996, 510 – 541) we investigate a dynamic version of the model in which agents? decision rules are updated using genetic algorithms. Our main interest is in whether the equilibrium dynamics resulting from this learning process helps to explain the main stylized facts of free-floating exchange rates (unit roots in levels together with fat tails in returns and volatility clustering). Our time series analysis of simulated data indicates that for particular parameterizations, the characteristics of the exchange rate dynamics are, in fact, very similar to those of empirical data. The similarity appears to be quite insensitive with respect to some of the ingredients of the GA algorithm (i.e. utility-based versus rank-based or tournament selection, binary or real coding). However, appearance or not of realistic time series characteristics depends crucially on the mutation probability (which should be low) and the number of agents (not more than about 1000). With a larger population, this collective learning dynamics looses its realistic appearance and instead exhibits regular periodic oscillations of the agents? choice variables. --

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Mathematical Economics.

Volume (Year): 41 (2005)
Issue (Month): 1-2 (February)
Pages: 169-196

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Handle: RePEc:eee:mateco:v:41:y:2005:i:1-2:p:169-196

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  3. Kirman Alan & Teyssière Gilles, 2002. "Microeconomic Models for Long Memory in the Volatility of Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, De Gruyter, vol. 5(4), pages 1-23, January.
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  12. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B, University of Bonn, Germany 437, University of Bonn, Germany, revised Jul 1998.
  13. Bilson, John F O, 1981. "The "Speculative Efficiency" Hypothesis," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 54(3), pages 435-51, July.
  14. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 104(3), pages 510-41, June.
  15. Gaunersdorfer, A. & Hommes, C.H., 2005. "A nonlinear structural model for volatility clustering," CeNDEF Working Papers, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance 05-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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