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Limitations of stabilizing effects of fundamentalists: Facing positive feedback traders

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  • Baumann, Michael Heinrich
  • Baumann, Michaela
  • Erler, Alexander

Abstract

The authors analyze financial interactions between fundamentalists and chartists within a heterogeneous agent model, focusing on the role of fundamentalists stabilizing prices. In contrast to related studies, which are based on simulations and calculations, they analytically prove that the presence of fundamentalists is not sufficient to avoid asset price bubbles. The behavior of trend followers with bounded leverage can result in exploding prices irrespective of fundamentalists' investment decisions. They derive upper boundaries for positive feedback traders' initial investment necessary to avoid exploding prices. In order to stabilize stock/asset markets, intervention measures might be helpful.

Suggested Citation

  • Baumann, Michael Heinrich & Baumann, Michaela & Erler, Alexander, 2019. "Limitations of stabilizing effects of fundamentalists: Facing positive feedback traders," Economics Discussion Papers 2019-3, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwedp:20193
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    References listed on IDEAS

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    1. Hermsen, Oliver & Witte, Björn-Christopher & Westerhoff, Frank, 2010. "Disclosure requirements, the release of new information and market efficiency: new insights from agent-based models," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-26.
    2. Andrea Gaunersdorfer & Cars Hommes, 2007. "A Nonlinear Structural Model for Volatility Clustering," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288, Springer.
    3. Westerhoff, Frank H. & Dieci, Roberto, 2006. "The effectiveness of Keynes-Tobin transaction taxes when heterogeneous agents can trade in different markets: A behavioral finance approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(2), pages 293-322, February.
    4. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    5. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    6. Gilles Teyssière & Alan P. Kirman (ed.), 2007. "Long Memory in Economics," Springer Books, Springer, number 978-3-540-34625-8, January.
    7. Thomas Lux & Michele Marchesi, 2000. "Volatility Clustering In Financial Markets: A Microsimulation Of Interacting Agents," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 675-702.
    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. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    10. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
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    Cited by:

    1. Michael Heinrich Baumann, 2022. "Beating the market? A mathematical puzzle for market efficiency," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 279-325, June.

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    More about this item

    Keywords

    heterogeneous agents; feedback trading; fundamentalists; chartists; trend followers; financial bubbles; financial crisis;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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