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The dynamics of traded value revisited

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  • Eisler, Zoltán
  • Kertész, János

Abstract

We conclude from an analysis of high resolution NYSE data that the distribution of the traded value fi (or volume) has a finite variance σi for the very large majority of stocks i, and the distribution itself is non-universal across stocks. The Hurst exponent of the same time series displays a crossover from weakly to strongly correlated behavior around the time scale of 1 day. The persistence in the strongly correlated regime increases with the average trading activity 〈fi〉 as Hi=H0+γlog〈fi〉, which is another sign of non-universal behavior. The existence of such liquidity dependent correlations is consistent with the empirical observation that σi∝〈fi〉α, where α is a non-trivial, time scale dependent exponent.

Suggested Citation

  • Eisler, Zoltán & Kertész, János, 2007. "The dynamics of traded value revisited," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 66-72.
    • Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:66-72
    DOI: 10.1016/j.physa.2007.02.009
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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, October.
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    Cited by:

    1. Wei-Xing Zhou, 2012. "Universal price impact functions of individual trades in an order-driven market," Quantitative Finance, Taylor & Francis Journals, vol. 12(8), pages 1253-1263, June.
    2. Ni, Xiao-Hui & Jiang, Zhi-Qiang & Gu, Gao-Feng & Ren, Fei & Chen, Wei & Zhou, Wei-Xing, 2010. "Scaling and memory in the non-Poisson process of limit order cancelation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2751-2761.
    3. Charutha, S. & Gopal Krishna, M. & Manimaran, P., 2020. "Multifractal analysis of Indian public sector enterprises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    4. Wang, Yanjun & Zhang, Qiqian & Zhu, Chenping & Hu, Minghua & Duong, Vu, 2016. "Human activity under high pressure: A case study on fluctuation scaling of air traffic controller’s communication behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 151-157.
    5. Hasan, Rashid & Mohammed Salim, M., 2017. "Power law cross-correlations between price change and volume change of Indian stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 620-631.
    6. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    7. Qing Cai & Hai-Chuan Xu & Wei-Xing Zhou, 2016. "Taylor's Law of temporal fluctuation scaling in stock illiquidity," Papers 1610.01149, arXiv.org.

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