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A simple agent-based financial market model: Direct interactions and comparisons of trading profits

  • Westerhoff, Frank

We develop an agent-based financial market model in which agents follow technical and fundamental trading rules to determine their speculative investment positions. A central feature of our model is that we consider direct interactions between speculators due to which they may decide to change their trading behavior. For instance, if a technical trader meets a fundamental trader and they realize that fundamental trading has been more profitable than technical trading in the recent past, the probability that the technical trader switches to fundamental trading rules is relatively high. Our simple setup is able to replicate some salient features of asset price dynamics.

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Paper provided by Bamberg University, Bamberg Economic Research Group in its series BERG Working Paper Series with number 61.

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Date of creation: 2009
Date of revision:
Handle: RePEc:zbw:bamber:61
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  1. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
  2. Menkhoff, Lukas & Taylor, Mark P., 2006. "The Obstinate Passion of Foreign Exchange Professionals : Technical Analysis," The Warwick Economics Research Paper Series (TWERPS) 769, University of Warwick, Department of Economics.
  3. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-96, July.
  4. Frankel, Jeffrey A & Froot, Kenneth A, 1986. "Understanding the U.S. Dollar in the Eighties: The Expectations of Chartists and Fundamentalists," The Economic Record, The Economic Society of Australia, vol. 0(0), pages 24-38, Supplemen.
  5. J. Doyne Farmer & Shareen Joshi, 2000. "The Price Dynamics of Common Trading Strategies," Working Papers 00-12-069, Santa Fe Institute.
  6. Manzan, S. & Westerhoff, F., 2002. "Heterogeneous Expectations, Exchange Rate Dynamics and Predictability," CeNDEF Working Papers 02-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  7. Manfred Gilli & Peter Winker & Vahidin Jeleskovic, 2006. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Computing in Economics and Finance 2006 147, Society for Computational Economics.
  8. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
  9. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  10. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  11. Menkhoff, Lukas, 1997. "Examining the Use of Technical Currency Analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(4), pages 307-18, October.
  12. Carl Chiarella & Roberto Dieci & Laura Gardini, 2001. "Speculative Behaviour and Complex Asset Price Dynamics," Research Paper Series 49, Quantitative Finance Research Centre, University of Technology, Sydney.
  13. Frank H. Westerhoff, 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(2+3), pages 195-227, June.
  14. Brock, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers 9530r, Wisconsin Madison - Social Systems.
  15. 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.
  16. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
  17. Frank Westerhoff, 2004. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Computing in Economics and Finance 2004 14, Society for Computational Economics.
  18. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February.
  19. Rosser, J. Jr. & Ahmed, Ehsan & Hartmann, Georg C., 2003. "Volatility via social flaring," Journal of Economic Behavior & Organization, Elsevier, vol. 50(1), pages 77-87, January.
  20. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
  21. J. Barkley Rosser, Jr. & Honggang Li, 2004. "Market Dynamics and Stock Price Volatility," Computing in Economics and Finance 2004 91, Society for Computational Economics.
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