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Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets

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  • Schmitt, Noemi
  • Westerhoff, Frank H.
Abstract
We propose an empirically motivated financial market model in which speculators rely on trend-following, contrarian and fundamental trading rules to determine their orders. Speculators' probabilistic rule-selection behavior - the only type of randomness in our model - depends on past and future performance indicators. For a large number of speculators, the model's intrinsic noise vanishes and its dynamics is driven by an analytically tractable nonlinear map. An in-depth investigation into this map provides the key to understanding how the model functions. Since our model is able to match a number of important stylized facts concerning financial markets, it may be regarded as validated.

Suggested Citation

  • Schmitt, Noemi & Westerhoff, Frank H., 2019. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," BERG Working Paper Series 151, Bamberg University, Bamberg Economic Research Group.
  • Handle: RePEc:zbw:bamber:151
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    References listed on IDEAS

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    2. Mignot, Sarah & Westerhoff, Frank H., 2023. "Explaining the stylized facts of foreign exchange markets with a simple agent-based version of Paul de Grauwe's chaotic exchange rate model," BERG Working Paper Series 189, Bamberg University, Bamberg Economic Research Group.
    3. Federico Bassi & Raquel Ramos & Dany Lang, 2023. "Bet against the trend and cash in profits: An agent-based model of endogenous fluctuations of exchange rates," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 429-472, April.
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    5. Perras, Patrizia & Wagner, Niklas, 2020. "Pricing equity-bond covariance risk: Between flight-to-quality and fear-of-missing-out," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    6. Savin, Ivan & Mundt, Philipp, 2022. "Drivers of productivity change in global value chains: Reallocation vs. innovation," Economics Letters, Elsevier, vol. 220(C).
    7. Michael Heinrich Baumann & Michaela Baumann & Lars Grüne & Bernhard Herz, 2023. "Market Structure and Instability Artifacts in Heterogeneous Agent Models: Lessons from Implicit Discretizations of Stiff Equations," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 855-890, October.
    8. Sahm, Marco, 2022. "Optimal accuracy of unbiased Tullock contests with two heterogeneous players," BERG Working Paper Series 175, Bamberg University, Bamberg Economic Research Group.
    9. Gardini, L. & Radi, D. & Schmitt, N. & Sushko, I. & Westerhoff, F., 2022. "Causes of fragile stock market stability," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 483-498.
    10. Mundt, Philipp & Cantner, Uwe & Inoue, Hiroyasu & Savin, Ivan & Vannuccini, Simone, 2021. "Market selection in global value chains," BERG Working Paper Series 170, Bamberg University, Bamberg Economic Research Group.
    11. Philipp Mundt & Simone Alfarano & Mishael Milaković, 2022. "Survival and the Ergodicity of Corporate Profitability," Management Science, INFORMS, vol. 68(5), pages 3726-3734, May.
    12. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    13. Jean-Philippe Bouchaud, 2024. "The Self-Organized Criticality Paradigm in Economics & Finance," Papers 2407.10284, arXiv.org, revised Sep 2024.
    14. Deborah Noguera & Gabriel Montes-Rojas, 2023. "Minskyan model with credit rationing in a network economy," SN Business & Economics, Springer, vol. 3(3), pages 1-26, March.
    15. Schmitt, Sefanie Y. & Bruckner, Dominik, 2022. "Unaware consumers and disclosure of deficiencies," BERG Working Paper Series 178, Bamberg University, Bamberg Economic Research Group.

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    More about this item

    Keywords

    financial markets; stylized facts; technical and fundamental analysis; probabilistic rule-selection behavior; nonlinear dynamics; stability and bifurcation analysis;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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