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Non-extensive behavior of a stock market index at microscopic time scales

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  • Cortines, A.A.G.
  • Riera, R.

Abstract

This paper presents an empirical investigation of the intraday Brazilian stock market price fluctuations, considering q-Gaussian distributions that emerge from a non-extensive statistical mechanics. Our results show that, when price returns are measured over intervals less than one hour, the empirical distributions are well fitted by q-Gaussians with exponential damped tails. Scaling behavior is also observed for these microscopic time intervals. We find that the time evolution of the return distributions is according to a super-diffusive q-Gaussian stationary process within a nonlinear Fokker–Planck equation. This regime breaks down due to the exponential fall-off of the tails, which in turn, governs the transient dynamics to the long-term macroscopic Gaussian regime. This exponentially damped, non-extensive modeling provides a new framework to investigate the dynamics of other stock markets intraday price fluctuations.

Suggested Citation

  • Cortines, A.A.G. & Riera, R., 2007. "Non-extensive behavior of a stock market index at microscopic time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 181-192.
    • Handle: RePEc:eee:phsmap:v:377:y:2007:i:1:p:181-192
    DOI: 10.1016/j.physa.2006.10.099
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    References listed on IDEAS

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    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, September.
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    Cited by:

    1. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Nonextensive triplets in cryptocurrency exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1069-1074.
    2. Sosa-Correa, William O. & Ramos, Antônio M.T. & Vasconcelos, Giovani L., 2018. "Investigation of non-Gaussian effects in the Brazilian option market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 525-539.
    3. Rui Pascoal & Ana Margarida Monteiro, 2013. "Market Efficiency, Roughness and Long Memory in the PSI20 Index Returns: Wavelet and Entropy Analysis," GEMF Working Papers 2013-27, GEMF, Faculty of Economics, University of Coimbra.
    4. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    5. Sandhya Devi, 2016. "Financial Market Dynamics: Superdiffusive or not?," Papers 1608.07752, arXiv.org, revised Sep 2017.
    6. Devi, Sandhya, 2016. "Financial Market Dynamics: Superdiffusive or not?," MPRA Paper 73327, University Library of Munich, Germany, revised 24 Aug 2016.
    7. Devi, Sandhya, 2021. "Asymmetric Tsallis distributions for modeling financial market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    8. Ramos, Antônio M.T. & Carvalho, J.A. & Vasconcelos, G.L., 2016. "Exponential model for option prices: Application to the Brazilian market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 161-168.

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