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Markets, Herding and Response to External Information

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  • Adrián Carro
  • Raúl Toral
  • Maxi San Miguel

Abstract

We focus on the influence of external sources of information upon financial markets. In particular, we develop a stochastic agent-based market model characterized by a certain herding behavior as well as allowing traders to be influenced by an external dynamic signal of information. This signal can be interpreted as a time-varying advertising, public perception or rumor, in favor or against one of two possible trading behaviors, thus breaking the symmetry of the system and acting as a continuously varying exogenous shock. As an illustration, we use a well-known German Indicator of Economic Sentiment as information input and compare our results with Germany’s leading stock market index, the DAX, in order to calibrate some of the model parameters. We study the conditions for the ensemble of agents to more accurately follow the information input signal. The response of the system to the external information is maximal for an intermediate range of values of a market parameter, suggesting the existence of three different market regimes: amplification, precise assimilation and undervaluation of incoming information.

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  • Adrián Carro & Raúl Toral & Maxi San Miguel, 2015. "Markets, Herding and Response to External Information," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-28, July.
    • Handle: RePEc:plo:pone00:0133287
    DOI: 10.1371/journal.pone.0133287
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    2. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harré, 2021. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model," SN Business & Economics, Springer, vol. 1(6), pages 1-21, June.
    3. Vygintas Gontis & Aleksejus Kononovicius, 2017. "Spurious memory in non-equilibrium stochastic models of imitative behavior," Papers 1707.09801, arXiv.org.
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    5. Kroujiline, Dimitri & Gusev, Maxim & Ushanov, Dmitry & Sharov, Sergey V. & Govorkov, Boris, 2015. "Forecasting stock market returns over multiple time horizons," MPRA Paper 66175, University Library of Munich, Germany.
    6. Eminente, Clara & Artime, Oriol & De Domenico, Manlio, 2022. "Interplay between exogenous triggers and endogenous behavioral changes in contagion processes on social networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    7. Sunyoung Lee & Keun Lee, 2021. "3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 359-380, April.
    8. Steven D. Silver & Marko Raseta, 2021. "An ARFIMA multi-level model of dual-component expectations in repeated cross-sectional survey data," Empirical Economics, Springer, vol. 60(2), pages 683-699, February.
    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.
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