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Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

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Author Info
Simone Alfarano ()
Thomas Lux
Friedrich Wagner

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Abstract

The behavioral origins of the stylized facts of financial returns have been addressed in a growing body of agent-based models of financial markets. While the traditional efficient market viewpoint explains all statistical properties of returns by similar features of the news arrival process, the more recent behavioral finance models explain them as imprints of universal patterns of interaction in these markets. In this paper we contribute to this literature by introducing a very simple agent-based model in which the ubiquitous stylized facts (fat tails, volatility clustering) are emergent properties of the interaction among traders. The simplicity of the model allows us to estimate the underlying parameters, since it is possible to derive a closed form solution for the distribution of returns. We show that the tail shape characterizing the fatness of the unconditional distribution of returns can be directly derived from some structural variables that govern the traders’ interactions, namely the herding propensity and the autonomous switching tendency. Copyright Springer Science + Business Media, Inc. 2005

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File URL: http://hdl.handle.net/10.1007/s10614-005-6415-1
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Publisher Info
Article provided by Springer in its journal Computational Economics.

Volume (Year): 26 (2005)
Issue (Month): 1 (August)
Pages: 19-49
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Handle: RePEc:kap:compec:v:26:y:2005:i:1:p:19-49

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Related research
Keywords: fat tails; herd behavior; speculative dynamics; volatility clustering;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  2. repec:bep:sndecm:7:2003:4:1125-1125 is not listed on IDEAS
    Other versions:
  3. Friedrich Wagner & Thomas Lux & Simone Alfarano, 2005. "Time-Variation of Higher Moments in a Financial Market with Heterogeneous Agents: An Analytical Approach," Working Papers wp05-02, Warwick Business School, Financial Econometrics Research Centre. [Downloadable!]
    Other versions:
  4. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B 437, University of Bonn, Germany, revised Jul 1998.
  5. Phillip Kearns & Adrian Pagan, 1997. "Estimating The Density Tail Index For Financial Time Series," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 171-175, May. [Downloadable!] (restricted)
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    Other versions:
  8. Lux, Thomas, 1996. "The Stable Paretian Hypothesis and the Frequency of Large Returns: An Examination of Major German Stocks," Applied Financial Economics, Taylor and Francis Journals, vol. 6(6), pages 463-75, December. [Downloadable!] (restricted)
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    Other versions:
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    Other versions:
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  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. [Downloadable!]
  2. Klein, Achim & Urbig, Diemo & Kirn, Stefan, 2008. "Who drives the Market? Estimating a heterogeneous Agent-based Financial Market Model using a Neural Network Approach," MPRA Paper 14433, University Library of Munich, Germany. [Downloadable!]
  3. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008,08, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
  4. Frank Westerhoff & Martin Hohnisch, 2007. "A note on interactions-driven business cycles," Journal of Economic Interaction and Coordination, Springer, vol. 2(1), pages 85-91, June. [Downloadable!] (restricted)
  5. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Kiel Working Papers 1426, Kiel Institute for the World Economy. [Downloadable!]
  6. V. Alfi & M. Cristelli & L. Pietronero & A. Zaccaria, 2008. "Minimal Agent Based Model for Financial Markets I: Origin and Self-Organization of Stylized Facts," Quantitative Finance Papers 0808.3562, arXiv.org. [Downloadable!]
  7. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An objective function for simulation based inference on exchange rate data," Journal of Economic Interaction and Coordination, Springer, vol. 2(2), pages 125-145, December. [Downloadable!] (restricted)
    Other versions:
  8. Franke, Reiner, 2008. "Artificial Long Memory Effects in Two Agend-Based Asset Pricing Models," Economics Working Papers 2008,15, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
  9. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Quantitative Finance Papers physics/0701140, arXiv.org. [Downloadable!]
  10. Boswijk, H.P. & Hommes C.H. & Manzan, S., 2005. "Behavioral Heterogeneity in Stock Prices," CeNDEF Working Papers 05-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
    Other versions:
  11. Ron Bird & Lorenzo Casavecchia & Paul Woolley, 2008. "Insights into the Market Impact of Different Investment Styles," Working Paper Series 1, The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney. [Downloadable!]
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