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Communication impacting financial markets

Author

Listed:
  • Jørgen Vitting Andersen

    (Centre d'Economie de la Sorbonne)

  • Ioannis Vrontos

    (Athens University of Economics and Business - Department of Statistics)

  • Petros Dellaportas

    (Athens University of Economics and Business - Department of Statistics)

  • Serge Galam

    (CEVIPOF - Center for Political Research)

Abstract

Background: Since the attribution of the Nobel prize in 2002 to Kahneman for prospect theory, behavioral finance has become an increasingly important subfield of finance. However the main parts of behavioral finance, prospect theory included, understand financial markets through individual investment behavior. Behavioral finance thereby ignores any interaction between participants. Methodology: We introduce a socio-financial model that studies the impact of communication on the pricing in financial markets. Considering the simplest possible case where each market participant has either a positive (bullish) or negative (bearish) sentiment with respect to the market, we model the evolution of the sentiment in the population due to communication in subgroups of different sizes. Nonlinear feedback effects between the market performance and changes in sentiments are taking into account by assuming that the market performance is dependent on changes in sentiments (e.g. a large sudden positive change in bullishness would lead to more buying). The market performance in turn has an impact on the sentiment through the transition probabilities to change an opinion in a group of a given size. The idea is that if for example the market has observed a recent downturn, it will be easier for even a bearish minority to convince a bullish majority to change opinion compared to the case where the meeting takes place in a bullish upturn of the market. Conclusions: Within the framework of our proposed model financial markets stylized facts such as volatility clustering and extreme events may be perceived as arising due to abrupt sentiment changes via ongoing communication of the market participants. The model introduces a new volatility measure which is apt of capturing volatility clustering and from maximum likelihood analysis we are able to apply the model to real data and give additional long term insight into where a market is heading

Suggested Citation

  • Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Documents de travail du Centre d'Economie de la Sorbonne 14029, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:14029
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Naji Massad & J{o}rgen Vitting Andersen, 2019. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Papers 1902.10800, arXiv.org.
    3. Naji Massad & Jørgen Vitting Andersen, 2017. "Three different ways synchronization can cause contagion in financial markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01673333, HAL.
    4. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "A Socio-Finance Model: Inference and empirical application," Working Papers hal-01215605, HAL.
    5. Yongqiang Meng & Dehua Shen & Xiong Xiong & Jørgen Vitting Andersen, 2020. "A Socio-Finance Model: The Case of Bitcoin," Post-Print halshs-03048777, HAL.
    6. Naji Massad & Jørgen Vitting Andersen, 2017. "Three different ways synchronization can cause contagion in financial markets," Post-Print halshs-01673333, HAL.
    7. Serge Galam, 2016. "The invisible hand and the rational agent are behind bubbles and crashes," Papers 1601.02990, arXiv.org.
    8. Naji Massad & Jørgen Vitting Andersen, 2017. "Three different ways synchronization can cause contagion in financial markets," Documents de travail du Centre d'Economie de la Sorbonne 17059, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Naji Massad & Jørgen Vitting Andersen, 2018. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Post-Print hal-01951164, HAL.
    10. Naji Massad & Jørgen Vitting Andersen, 2018. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01951164, HAL.
    11. Eberhard, Erich K. & Hicks, Jessica & Simon, Adam C. & Arbic, Brian K., 2022. "Livelihood considerations in land-use decision-making: Cocoa and mining in Ghana," World Development Perspectives, Elsevier, vol. 26(C).
    12. Zheng, Xi & Lu, Xi & Chan, Felix T.S. & Deng, Yong & Wang, Zhen, 2015. "Bargaining models in opinion dynamics," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 162-168.

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    More about this item

    Keywords

    Communication; formation of prices; stylized facts;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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