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

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  • Westerhoff, Frank

Abstract

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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Bibliographic Info

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
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Handle: RePEc:zbw:bamber:61

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Web page: http://www.uni-bamberg.de/vwl/forschung/berg/
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Related research

Keywords: Agent-based financial market models; direct interactions; evolutionary fitness measures; technical and fundamental analysis; stylized facts of financial markets;

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References

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  1. Carl Chiarella & Roberto Dieci & Laura Gardini, 2001. "Speculative Behaviour and Complex Asset Price Dynamics," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 49, Quantitative Finance Research Centre, University of Technology, Sydney.
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Cited by:
  1. Eckel, Carsten, 2009. "International trade and retailing," BERG Working Paper Series 63, Bamberg University, Bamberg Economic Research Group.
  2. Alfarano, Simone & Milakovic, Mishael, 2010. "Identification of Interaction Effects in Survey Expectations: A Cautionary Note," MPRA Paper 26002, University Library of Munich, Germany.
  3. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 36(8), pages 1193-1211.
  4. Christian Pierdzioch & Georg Stadtmann, 2010. "Herdenverhalten von Wechselkursprognostikern?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 230(4), pages 436-453, August.
  5. Gervai, Pál & Trautmann, László & Wieszt, Attila, 2010. "The mission and culture of the corporation," BERG Working Paper Series 74, Bamberg University, Bamberg Economic Research Group.
  6. Franke, Reiner & Westerhoff, Frank, 2011. "Why a simple herding model may generate the stylized facts of daily returns: Explanation and estimation," BERG Working Paper Series 83, Bamberg University, Bamberg Economic Research Group.
  7. Bexheti, Abdulmenaf, 2010. "Anti-crisis measures in the republic of Macedonia and their effects: Are they sufficient?," BERG Working Paper Series 70, Bamberg University, Bamberg Economic Research Group.
  8. Seregi, János & Lelovics, Zsuzsanna & Balogh, László, 2012. "The social welfare function of forests in the light of the theory of public goods," BERG Working Paper Series 87, Bamberg University, Bamberg Economic Research Group.
  9. Imami, Drini & Lami, Endrit & Kächelein, Holger, 2011. "Political cycles in income from privatization: The case of Albania," BERG Working Paper Series 77, Bamberg University, Bamberg Economic Research Group.

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