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Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

  • Alfarano, Simone
  • Lux, Thomas
  • Wagner, Friedrich

Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19–49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241–254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354–368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137–156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

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File URL: http://www.sciencedirect.com/science/article/pii/S0378437106004298
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Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 370 (2006)
Issue (Month): 1 ()
Pages: 38-42

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Handle: RePEc:eee:phsmap:v:370:y:2006:i:1:p:38-42
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  1. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
  2. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February.
  3. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
  4. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Society for Computational Economics, vol. 26(1), pages 19-49, August.
  5. De Long, J. Bradford & Shleifer, Andrei & Summers, Lawrence H. & Waldmann, Robert J., 1990. "Noise Trader Risk in Financial Markets," Scholarly Articles 3725552, Harvard University Department of Economics.
  6. Westerhoff Frank H. & Reitz Stefan, 2003. "Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-15, December.
  7. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
  8. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
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