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Endogenous and exogenous dynamics in the fluctuations of capital fluxes

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  • Z.-Q. Jiang
  • L. Guo
  • W.-X. Zhou

Abstract

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is carried out on the Chinese stock market using mean-variance analysis, fluctuation analysis, and their generalizations to higher orders. Non-universal dynamics have been found not only in the scaling exponent α, which is different from the universal values 1/2 and 1, but also in the distributions of the ratio η= σ exo / σ endo of individual stocks. Both the scaling exponent α of fluctuations and the Hurst exponent H i increase in logarithmic form with the time scale Δt and the mean traded value per minute 〈f i 〉, respectively. We find that the scaling exponent α endo of the endogenous fluctuations is independent of the time scale. Multiscaling and multifractal features are observed in the data as well. However, the inhomogeneous impact model is not verified. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Suggested Citation

  • Z.-Q. Jiang & L. Guo & W.-X. Zhou, 2007. "Endogenous and exogenous dynamics in the fluctuations of capital fluxes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(3), pages 347-355, June.
    • Handle: RePEc:spr:eurphb:v:57:y:2007:i:3:p:347-355
    DOI: 10.1140/epjb/e2007-00174-7
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    References listed on IDEAS

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    1. János Kertész & Zoltán Eisler, 2006. "Non-trivial scaling of fluctuations in the trading activity of NYSE," Springer Books, in: Hideki Takayasu (ed.), Practical Fruits of Econophysics, pages 19-23, Springer.
    2. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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    Cited by:

    1. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2009. "Detrended fluctuation analysis of intertrade durations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 433-440.
    2. Yang, Yan-Hong & Xie, Wen-Jie & Li, Ming-Xia & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2017. "Statistical properties of user activity fluctuations in virtual worlds," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 271-278.
    3. Tahira, Yoshifumi & Mizuno, Takayuki, 2016. "Amount of news before stock market fluctuations," HIT-REFINED Working Paper Series 45, Institute of Economic Research, Hitotsubashi University.
    4. Zhou, Wei-Xing, 2012. "Finite-size effect and the components of multifractality in financial volatility," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 147-155.
    5. Ren, Fei & Guo, Liang & Zhou, Wei-Xing, 2009. "Statistical properties of volatility return intervals of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 881-890.
    6. Mu, Guo-Hua & Zhou, Wei-Xing, 2008. "Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5211-5218.
    7. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2008. "Multifractal analysis of Chinese stock volatilities based on the partition function approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(19), pages 4881-4888.
    8. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    9. Yoshifumi Tahira & Takayuki Mizuno, 2016. "Trading strategy of a stock index based on the frequency of news releases for listed companies," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 437-444, December.

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