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Modelling and Measuring the Irrational behaviour of Agents in Financial Markets: Discovering the Psychological Soliton

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  • Gurjeet Dhesi
  • Marcel Ausloos

Abstract

Following a Geometrical Brownian Motion extension into an Irrational Fractional Brownian Motion model, we re-examine agent behaviour reacting to time dependent news on the log-returns thereby modifying a financial market evolution. We specifically discuss the role of financial news or economic information positive or negative feedback of such irrational (or contrarian) agents upon the price evolution. We observe a kink-like effect reminiscent of soliton behaviour, suggesting how analysts' forecasts errors induce stock prices to adjust accordingly, thereby proposing a measure of the irrational force in a market.

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  • Gurjeet Dhesi & Marcel Ausloos, 2016. "Modelling and Measuring the Irrational behaviour of Agents in Financial Markets: Discovering the Psychological Soliton," Papers 1601.01553, arXiv.org.
    • Handle: RePEc:arx:papers:1601.01553
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    References listed on IDEAS

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    1. Ausloos, M. & Bronlet, Ph., 2003. "Strategy for investments from Zipf law(s)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 30-37.
    2. Vandewalle, N. & Ausloos, M., 1997. "Coherent and random sequences in financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 454-459.
    3. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    4. M. Ausloos & Ph. Bronlet, 2006. "Risk portofolio management under Zipf analysis based strategies," Springer Books, in: Hideki Takayasu (ed.), Practical Fruits of Econophysics, pages 257-261, Springer.
    5. Bulkley, George & Harris, Richard D F, 1997. "Irrational Analysts' Expectations as a Cause of Excess Volatility in Stock Prices," Economic Journal, Royal Economic Society, vol. 107(441), pages 359-371, March.
    6. Victor Dragotă & Elena Ţilică, 2014. "Market efficiency of the Post Communist East European stock markets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 307-337, June.
    7. 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.
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    Cited by:

    1. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    2. Ausloos, Marcel, 2021. "Hagiotoponyms in France: Saint popularity, like a herding phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    3. Jing Shi & Marcel Ausloos & Tingting Zhu, 2022. "If global or local investor sentiments are prone to developing an impact on stock returns, is there an industry effect?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1309-1320, January.
    4. Claudiu Vințe & Marcel Ausloos, 2023. "Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy," JRFM, MDPI, vol. 16(2), pages 1-24, February.
    5. Galam, Serge, 2016. "The invisible hand and the rational agent are behind bubbles and crashes," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 209-217.
    6. Argentiero, Amedeo & Bovi, Maurizio & Cerqueti, Roy, 2016. "Bayesian estimation and entropy for economic dynamic stochastic models: An exploration of overconsumption," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 143-157.
    7. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    8. Bonga-Bonga, Lumengo, 2024. "Exploring the sensitivity of BRICS stock markets to oil Price shocks: a quantile-on-quantile perspective," MPRA Paper 120190, University Library of Munich, Germany.
    9. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    10. Jiaquan Chen & Marcel Ausloos, 2023. "A Study about Who Is Interested in Stock Splitting and Why: Considering Companies, Shareholders, or Managers," JRFM, MDPI, vol. 16(2), pages 1-25, January.
    11. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.
    12. Andrew Spurr & Marcel Ausloos, 2021. "Challenging practical features of Bitcoin by the main altcoins," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1541-1559, October.
    13. Gurjeet Dhesi & Bilal Shakeel & Marcel Ausloos, 2021. "Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach," Annals of Operations Research, Springer, vol. 299(1), pages 1397-1410, April.
    14. Eduard Gabriel Ceptureanu & Sebastian Ion Ceptureanu & Doina I. Popescu & Liviu Bogdan Vlad, 2017. "Two Stage Analysis of Successful Change Implementation of Knowledge Management Strategies in Energy Companies from Romania," Energies, MDPI, vol. 10(12), pages 1-17, November.
    15. Cerqueti, Roy & Giacalone, Massimiliano & Panarello, Demetrio, 2019. "A Generalized Error Distribution Copula-based method for portfolios risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 687-695.
    16. Inga Ivanova, 2024. "Communication of information in systems of heterogeneous agents and systems’ dynamics," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5377-5393, December.

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