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Financial factor influence on scaling and memory of trading volume in stock market

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  • Wei Li
  • Fengzhong Wang
  • Shlomo Havlin
  • H. Eugene Stanley
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    Abstract

    We study the daily trading volume volatility of 17,197 stocks in the U.S. stock markets during the period 1989--2008 and analyze the time return intervals $\tau$ between volume volatilities above a given threshold q. For different thresholds q, the probability density function P_q(\tau) scales with mean interval as P_q(\tau)= ^{-1}f(\tau/ ) and the tails of the scaling function can be well approximated by a power-law f(x)~x^{-\gamma}. We also study the relation between the form of the distribution function P_q(\tau) and several financial factors: stock lifetime, market capitalization, volume, and trading value. We find a systematic tendency of P_q(\tau) associated with these factors, suggesting a multi-scaling feature in the volume return intervals. We analyze the conditional probability P_q(\tau|\tau_0) for $\tau$ following a certain interval \tau_0, and find that P_q(\tau|\tau_0) depends on \tau_0 such that immediately following a short/long return interval a second short/long return interval tends to occur. We also find indications that there is a long-term correlation in the daily volume volatility. We compare our results to those found earlier for price volatility.

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    File URL: http://arxiv.org/pdf/1106.1415
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1106.1415.

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    Date of creation: Jun 2011
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    Handle: RePEc:arx:papers:1106.1415

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    Cited by:
    1. Xie, Wen-Jie & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2014. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Economic Modelling, Elsevier, Elsevier, vol. 36(C), pages 8-17.
    2. F. Y. Ouyang & B. Zheng & X. F. Jiang, 2014. "Spatial and temporal structures of four financial markets in Greater China," Papers 1402.1046, arXiv.org.
    3. Delignières, Didier & Marmelat, Vivien, 2014. "Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 394(C), pages 47-60.
    4. Miśkiewicz, Janusz, 2013. "Power law classification scheme of time series correlations. On the example of G20 group," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 392(9), pages 2150-2162.
    5. Xiao, Weilin & Zhang, Weiguo & Zhang, Xili & Chen, Xiaoyan, 2014. "The valuation of equity warrants under the fractional Vasicek process of the short-term interest rate," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 394(C), pages 320-337.
    6. Ouyang, F.Y. & Zheng, B. & Jiang, X.F., 2014. "Spatial and temporal structures of four financial markets in Greater China," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 402(C), pages 236-244.

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