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Evolutionary Dynamics in Financial Markets With Many Trader Types

Author

Listed:
  • Brock, W.A.
  • Hommes, C.H.

    (Universiteit van Amsterdam)

  • Wagener, F.O.O.

    (Universiteit van Amsterdam)

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.

Suggested Citation

  • Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2001. "Evolutionary Dynamics in Financial Markets With Many Trader Types," CeNDEF Working Papers 01-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    • Handle: RePEc:ams:ndfwpp:01-01
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    Cited by:

    1. 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.
    2. Orlando Gomes, . "Volatility, Heterogeneous Agents and Chaos," The Electronic Journal of Evolutionary Modeling and Economic Dynamics, IFReDE - Université Montesquieu Bordeaux IV.
    3. Orlando Gomes, 2004. "A Continuous-Time Asset Pricing Model with Boundedly Rational Heterogeneous Agents," Finance 0409055, University Library of Munich, Germany.
    4. Orlando Gomes, 2007. "Routes to chaos in macroeconomic theory," Journal of Economic Studies, Emerald Group Publishing, vol. 33(6), pages 437-468, January.
    5. 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.
    6. 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.
    7. Yang, J-H.S. & Satchell, S.E., 2003. "Endogenous Correlation," Cambridge Working Papers in Economics 0321, Faculty of Economics, University of Cambridge.
    8. 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.
    9. Parke, William R. & Waters, George A., 2014. "On The Evolutionary Stability Of Rational Expectations," Macroeconomic Dynamics, Cambridge University Press, vol. 18(7), pages 1581-1606, October.
    10. 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.
    11. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
    12. Orlando Gomes, 2006. "Routes to chaos in macroeconomic theory," Journal of Economic Studies, Emerald Group Publishing, vol. 33(6), pages 437-468, November.
    13. Gomes, Orlando, 2006. "Heterogeneous Researchers in a Two-Sector Representative Consumer Economy," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 60(2), November.
    14. Branch, William A. & Evans, George W., 2006. "Intrinsic heterogeneity in expectation formation," Journal of Economic Theory, Elsevier, vol. 127(1), pages 264-295, March.
    15. 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.
    16. 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.
    17. 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.
    18. S. Borovkova & H. Dehling & J. Renkema & H. Tulleken, 2003. "A Potential-Field Approach to Financial Time Series Modelling," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 139-161, October.
    19. 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.
    20. Andrea Consiglio & Valerio Lacagnina & Annalisa Russino, 2005. "A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 71-87.
    21. Amir, Rabah & Evstigneev, Igor V. & Hens, Thorsten & Schenk-Hoppe, Klaus Reiner, 2005. "Market selection and survival of investment strategies," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 105-122, February.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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