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Common Scaling Patterns in Intertrade Times of U. S. Stocks

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Author Info

  • Plamen Ch. Ivanov

    (Boston University)

  • Ainslie Yuen

    (Cambridge University)

  • Boris Podobnik

    (University of Rijeka, Croatia)

  • Youngki Lee

    (Yanbian University, China)

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    Abstract

    We analyze the sequence of time intervals between consecutive stock trades of thirty companies representing eight sectors of the U. S. economy over a period of four years. For all companies we find that: (i) the probability density function of intertrade times may be fit by a Weibull distribution; (ii) when appropriately rescaled the probability densities of all companies collapse onto a single curve implying a universal functional form; (iii) the intertrade times exhibit power-law correlated behavior within a trading day and a consistently greater degree of correlation over larger time scales, in agreement with the correlation behavior of the absolute price returns for the corresponding company, and (iv) the magnitude series of intertrade time increments is characterized by long-range power-law correlations suggesting the presence of nonlinear features in the trading dynamics, while the sign series is anti-correlated at small scales. Our results suggest that independent of industry sector, market capitalization and average level of trading activity, the series of intertrade times exhibit possibly universal scaling patterns, which may relate to a common mechanism underlying the trading dynamics of diverse companies. Further, our observation of long-range power-law correlations and a parallel with the crossover in the scaling of absolute price returns for each individual stock, support the hypothesis that the dynamics of transaction times may play a role in the process of price formation.

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    File URL: http://arxiv.org/pdf/cond-mat/0403662
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number cond-mat/0403662.

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    Date of creation: Mar 2004
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    Handle: RePEc:arx:papers:cond-mat/0403662

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    Web page: http://arxiv.org/

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    Cited by:
    1. Vladimir Filimonov & Didier Sornette, 2013. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Papers 1308.6756, arXiv.org, revised Jul 2014.
    2. Sun, Xiao-Qian & Cheng, Xue-Qi & Shen, Hua-Wei & Wang, Zhao-Yang, 2011. "Distinguishing manipulated stocks via trading network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 390(20), pages 3427-3434.
    3. Pyrlik, Vladimir, 2013. "Autoregressive conditional duration as a model for financial market crashes prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 392(23), pages 6041-6051.
    4. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    5. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2009. "Detrended fluctuation analysis of intertrade durations," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 388(4), pages 433-440.
    6. Enrico Scalas, 2005. "Five Years of Continuous-time Random Walks in Econophysics," Papers cond-mat/0501261, arXiv.org.
    7. Ming-Xia Li & Zhi-Qiang Jiang & Wen-Jie Xie & Xiong Xiong & Wei Zhang & Wei-Xing Zhou, 2013. "Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant," Papers 1308.0925, arXiv.org.
    8. Ruan, Yong-Ping & Zhou, Wei-Xing, 2011. "Long-term correlations and multifractal nature in the intertrade durations of a liquid Chinese stock and its warrant," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 390(9), pages 1646-1654.
    9. de Oliveira Santos, Maíra & Stosic, Tatijana & Stosic, Borko D., 2012. "Long-term correlations in hourly wind speed records in Pernambuco, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 391(4), pages 1546-1552.
    10. Politi, Mauro & Scalas, Enrico, 2008. "Fitting the empirical distribution of intertrade durations," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 387(8), pages 2025-2034.
    11. Sun, Lin, 2013. "Pricing currency options in the mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 392(16), pages 3441-3458.
    12. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 389(21), pages 4844-4854.
    13. Ren, Fei & Gu, Gao-Feng & Zhou, Wei-Xing, 2009. "Scaling and memory in the return intervals of realized volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 388(22), pages 4787-4796.
    14. Xiao-Qian Sun & Xue-Qi Cheng & Hua-Wei Shen & Zhao-Yang Wang, 2011. "Distinguishing manipulated stocks via trading network analysis," Papers 1110.2260, arXiv.org.
    15. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 362(2), pages 225-239.
    16. 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, Elsevier, vol. 389(14), pages 2751-2761.
    17. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2008. "Scaling in the distribution of intertrade durations of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 387(23), pages 5818-5825.
    18. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics: empirical facts," Post-Print, HAL hal-00621058, HAL.
    19. 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, Elsevier, vol. 388(6), pages 881-890.

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