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Power–law properties of Chinese stock market

Author

Listed:
  • Yan, C.
  • Zhang, J.W.
  • Zhang, Y.
  • Tang, Y.N.

Abstract

Price changes of primary returns of Chinese stock market are analyzed over a period of about 8 years. The probability distribution of relative changes in returns satisfies the power–law form. However, the distribution is not consistent with the analysis of US and other stock markets that seem to contain the exponent of an inverse cube. Furthermore, we find that the positive and negative returns do not behave consistently, which indicates a significant asymmetry in the distribution.

Suggested Citation

  • Yan, C. & Zhang, J.W. & Zhang, Y. & Tang, Y.N., 2005. "Power–law properties of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 425-432.
    • Handle: RePEc:eee:phsmap:v:353:y:2005:i:c:p:425-432
    DOI: 10.1016/j.physa.2005.02.010
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    References listed on IDEAS

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    1. Roehner,Bertrand M., 2002. "Patterns of Speculation," Cambridge Books, Cambridge University Press, number 9780521802635, October.
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    Cited by:

    1. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.
    2. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    3. Peng Liu & Yanyan Zheng, 2022. "Precision measurement of the return distribution property of the Chinese stock market index," Papers 2209.08521, arXiv.org, revised Nov 2023.
    4. Tabak, B.M. & Takami, M.Y. & Cajueiro, D.O. & Petitinga, A., 2009. "Quantifying price fluctuations in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 59-62.
    5. Federico Botta & Helen Susannah Moat & H Eugene Stanley & Tobias Preis, 2015. "Quantifying Stock Return Distributions in Financial Markets," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-10, September.
    6. Luo, Jiawen & Chen, Langnan & Liu, Hao, 2013. "Distribution characteristics of stock market liquidity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6004-6014.
    7. Wang, Lei & Liu, Lutao, 2020. "Long-range correlation and predictability of Chinese stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    8. Göncü, Ahmet & Yang, Hao, 2016. "Variance-Gamma and Normal-Inverse Gaussian models: Goodness-of-fit to Chinese high-frequency index returns," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 279-292.
    9. Enrico Geretto & Rubens Pauluzzo, 2012. "Stock Exchange Markets in China: Structure and Main Problems," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 19(1), pages 89-106, September.
    10. Meng, Xiangyi & Zhang, Jian-Wei & Guo, Hong, 2016. "Quantum Brownian motion model for the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 281-288.

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