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Do sentiments influence market dynamics? A reconstruction of the Brazilian stock market and its mood

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  • Araújo, Tanya
  • Eleutério, Samuel
  • Louçã, Francisco

Abstract

Sentiments play an important role in justifying economic actions and are typically presented as being a modern incarnation of expectations that influence financial markets, whether they be of a Keynesian or other type. For the case of the São Paulo Stock Market Index (IBovespa), this paper investigates whether sentiments, as publically expressed in specialised media, represent a covariate variable which influences stock market returns, and also how market dynamics evolve through time, especially in times of major shocks or recessions. In this study we use a network approach to relate the evolution of asset returns to a sentiments index. Daily data from IBovespa and a Thomson Reuters MarketPsych index are used as fair indicators of the evolution of the Brazilian economy from 2007 to 2015. We prove that changes in market prices affect news more than the reverse.

Suggested Citation

  • Araújo, Tanya & Eleutério, Samuel & Louçã, Francisco, 2018. "Do sentiments influence market dynamics? A reconstruction of the Brazilian stock market and its mood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1139-1149.
    • Handle: RePEc:eee:phsmap:v:505:y:2018:i:c:p:1139-1149
    DOI: 10.1016/j.physa.2018.04.045
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    References listed on IDEAS

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    1. Alexander M. Petersen & Fengzhong Wang & Shlomo Havlin & H. Eugene Stanley, 2010. "Market dynamics immediately before and after financial shocks: quantifying the Omori, productivity and Bath laws," Papers 1006.1882, arXiv.org, revised Oct 2010.
    2. George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
    3. Gopikrishnan, P & Plerou, V & Liu, Y & Amaral, L.A.N & Gabaix, X & Stanley, H.E, 2000. "Scaling and correlation in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 362-373.
    4. Saike He & Xiaolong Zheng & Daniel Zeng & Chuan Luo & Zhu Zhang, 2016. "Exploring Entrainment Patterns of Human Emotion in Social Media," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.
    5. Chester Curme & H. Eugene Stanley & Irena Vodenska, 2015. "Coupled Network Approach To Predictability Of Financial Market Returns And News Sentiments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-26, November.
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    Cited by:

    1. Akyol, Sinem & Alatas, Bilal, 2020. "Sentiment classification within online social media using whale optimization algorithm and social impact theory based optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    2. Gao, Zhenbin & Zhang, Jie, 2023. "The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).

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