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Switching Rates and the Asymptotic Behavior of Herding Models

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Author Info

  • Albrecht Irle
  • Jonas Kauschke
  • Thomas Lux
  • Mishael Milakovic

Abstract

Markov chains have experienced a surge of economic interest in the form of behavioral agent-based models that aim at explaining the statistical regularities of financial returns. We review some of the relevant mathematical facts and show how they apply to agent-based herding models, with the particular goal of establishing their asymptotic behavior because several studies have pointed out that the ability of such models to reproduce the stylized facts hinges crucially on the size of the agent population (typically denoted by n), a phenomenon that is also known as n-dependence. Our main finding is that n-(in)dependence traces back to both the topology and the velocity of information transmission among heterogeneous financial agents

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1595.

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Length: 16 pages
Date of creation: Feb 2010
Date of revision:
Handle: RePEc:kie:kieliw:1595

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Keywords: Markov chains; agent-based finance; herding; N-dependence;

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References

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  1. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
  2. Alfarano, Simone & Lux, Thomas, 2005. "A noise trader model as a generator of apparent financial power laws and long memory," Economics Working Papers 2005,13, Christian-Albrechts-University of Kiel, Department of Economics.
  3. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2006. "Time-Variation of Higher Moments in a Financial Market with Heterogeneous Agents: An Analytical Approach," Working Papers wpn06-01, Warwick Business School, Finance Group.
  4. Reiner Franke & Simone Alfarano, 2007. "A Simple Asymmetric Herding Model to Distinguish Between Stock and Foreign Exchange Markets," Working Papers wp07-01, Warwick Business School, Finance Group.
  5. 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.
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Cited by:
  1. S. Alfarano & M. Milakovic & M. Raddant, 2013. "A note on institutional hierarchy and volatility in financial markets," The European Journal of Finance, Taylor & Francis Journals, vol. 19(6), pages 449-465, July.

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