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Evolutionary dynamics in financial markets with many trader types

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  • W.A. Brock, C.H. Hommes and F.O.O. Wagener

Abstract

This paper develops the notion of a Large Type Limit (LTL) describing the average behavior of adaptive evolutionary systems with many trader types. It is shown that generic and persistent features of adaptive evolutionary systems with many trader types are well described by the large type limit. Stability and bifurcation routes to instability and strange attractors are studied. An increase in the "intensity of adaption" or in the diversity of beliefs may lead to deviations from the RE fundamental benchmark and excess volatility. Simple examples of LTL are able to generate important stylized facts, such as volatility clustering and long memory, observed in real financial data.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 119.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:119

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Keywords: evolutionary adaptive systems; heterogeneous agents; bounded rationality; nonlinear dynamics;

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References

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Citations

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Cited by:
  1. Chiarella, Carl & He, Xue-Zhong & Zheng, Min, 2011. "An analysis of the effect of noise in a heterogeneous agent financial market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 148-162, January.
  2. Rabah Amir & Igor V. Evstigneev & Thorsten Hens & Klaus Reiner Schenk-Hoppé, . "Market Selection and Survival of Investment Strategies," IEW - Working Papers 091, Institute for Empirical Research in Economics - University of Zurich.
  3. S. Borovkova & H. Dehling & J. Renkema & H. Tulleken, 2003. "A Potential-Field Approach to Financial Time Series Modelling," Computational Economics, Society for Computational Economics, vol. 22(2), pages 139-161, October.
  4. Lux, Thomas & Schornstein, Sascha, 2003. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Economics Working Papers |aEconomics working paper, Christian-Albrechts-University of Kiel, Department of Economics.
  5. Brock, W.A. & Hommes, C.H., 2001. "Heterogeneous beliefs and and routes to complez dynamics in asset pricing models with price contingent contracts," CeNDEF Working Papers 01-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  6. Henrik Amilon, 2003. "Estimation of an Adaptive Stock Market Model with Heterogeneous Agents," Research Paper Series 107, Quantitative Finance Research Centre, University of Technology, Sydney.
  7. Orlando Gomes, 2004. "A Continuous-Time Asset Pricing Model with Boundedly Rational Heterogeneous Agents," Finance 0409055, EconWPA.
  8. Orlando Gomes, 2004. "Heterogeneous Researchers in a Two-Sector Representative Consumer Economy," GE, Growth, Math methods 0409009, EconWPA.
  9. Parke, William R. & Waters, George A., 2007. "An evolutionary game theory explanation of ARCH effects," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2234-2262, July.
  10. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
  11. Amilon, Henrik, 2005. "Estimation of an Adaptive Stock Market Model with Heterogeneous Agents," Working Paper Series 177, Sveriges Riksbank (Central Bank of Sweden).
  12. William R. Parke & George A. Waters, 2011. "On the Evolutionary Stability of Rational Expectations," Working Paper Series 20111002, Illinois State University, Department of Economics.
  13. Branch, William A. & McGough, Bruce, 2008. "Replicator dynamics in a Cobweb model with rationally heterogeneous expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 224-244, February.
  14. Brock,W.A. & Hommes,C.H., 2002. "Heterogeneous beliefs and routes to complex dynamics in asset pricing models with price contingent contracts," Working papers 3, Wisconsin Madison - Social Systems.
  15. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
  16. Carl Chiarella & Xue-Zhong He & Min Zheng, 2007. "The Stochastic Dynamics of Speculative Prices," Research Paper Series 208, Quantitative Finance Research Centre, University of Technology, Sydney.
  17. Yang, J-H.S. & Satchell, S.E., 2003. "Endogenous Correlation," Cambridge Working Papers in Economics 0321, Faculty of Economics, University of Cambridge.
  18. Constantinos VORLOW & Antonios ANTONIOU & Catherine KYRTSOU, 2004. "Surrogate Data Analysis and Stochastic Chaotic Modelling: Application to Stock Exchange Returns Series," Computing in Economics and Finance 2004 27, Society for Computational Economics.

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