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Recurrence duration statistics and time-dependent intrinsic correlation analysis of trading volumes: A study of Chinese stock indices

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  • Niu, Hongli
  • Wang, Weiqing
  • Zhang, Junhuan

Abstract

The trading volume in stock markets is known as an important variable which reflects the liquidity of the financial markets and therefore is regarded to be greatly important for the measurement of market liquidity risk. In this work, a new concept called recurrence duration is introduced for study of daily trading volumes, which is inspired by idea of the volatility duration that was proposed and studied in our previous work. The recurrence duration is thought as the shortest passing time that the following days’ trading volume takes to exceed or go below the current trading volume which is time-varying. Similar to the volatility duration distribution of the price returns, the power-law function could describe the empirical probability distribution of recurrence durations of trading volumes, and their tail distributions can be fitted by two stretched exponential functions. Further, the correlation relationships of trading volumes between Chinese stock indices as well as the correlations of recurrence durations are investigated. One approach employed is a recently proposed method, time-dependent intrinsic correlation (TDIC), which is based on the empirical mode decomposition (EMD) to decompose nonlinear and nonstationary signals into the intrinsic mode functions (IMFs), the instantaneous periods of which are used then in determination of the sizes of sliding windows to compute the running correlation coefficients for the multiscale signals. The empirical results reveal rich patterns of correlations for both trading volumes and recurrence durations at different scales for different modes. Another approach is the widely-used DCCA cross-correlation coefficient, by which the level of cross-correlation is measured for both original series and IMF modes of the stock indices.

Suggested Citation

  • Niu, Hongli & Wang, Weiqing & Zhang, Junhuan, 2019. "Recurrence duration statistics and time-dependent intrinsic correlation analysis of trading volumes: A study of Chinese stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 838-854.
    • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:838-854
    DOI: 10.1016/j.physa.2018.09.115
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    as
    1. Gontis, V. & Havlin, S. & Kononovicius, A. & Podobnik, B. & Stanley, H.E., 2016. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1091-1102.
    2. Ren, F. & Zheng, B. & Lin, H. & Wen, L.Y. & Trimper, S., 2005. "Persistence probabilities of the German DAX and Shanghai Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 439-450.
    3. Paiva, Aureliano Sancho Souza & Rivera-Castro, Miguel Angel & Andrade, Roberto Fernandes Silva, 2018. "DCCA analysis of renewable and conventional energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1408-1414.
    4. Fei Ren & Wei-Xing Zhou, 2010. "Recurrence interval analysis of trading volumes," Papers 1002.1653, arXiv.org.
    5. Andrade, R.F.S. & Schellnhuber, H.J. & Claussen, M., 1998. "Analysis of rainfall records: possible relation to self-organized criticality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 254(3), pages 557-568.
    6. Niu, Hongli & Wang, Jun, 2017. "Return volatility duration analysis of NYMEX energy futures and spot," Energy, Elsevier, vol. 140(P1), pages 837-849.
    7. Xie, Wen-Jie & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2014. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Economic Modelling, Elsevier, vol. 36(C), pages 8-17.
    8. Zhang, Junhuan, 2018. "Influence of individual rationality on continuous double auction markets with networked traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 353-392.
    9. Fengzhong Wang & Kazuko Yamasaki & Shlomo Havlin & H. Eugene Stanley, 2005. "Scaling and memory of intraday volatility return intervals in stock market," Papers physics/0511101, arXiv.org.
    10. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    11. Parameswaran Gopikrishnan & Vasiliki Plerou & Xavier Gabaix & H. Eugene Stanley, 2000. "Statistical Properties of Share Volume Traded in Financial Markets," Papers cond-mat/0008113, arXiv.org.
    12. Grau-Carles, Pilar, 2001. "Long-range power-law correlations in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 521-527.
    13. Gvozdanovic, Igor & Podobnik, Boris & Wang, Duan & Eugene Stanley, H., 2012. "1/f behavior in cross-correlations between absolute returns in a US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2860-2866.
    14. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    15. Junhuan Zhang & Peter McBurney & Katarzyna Musial, 2018. "Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 301-352, January.
    16. Plamen Ch. Ivanov & Ainslie Yuen & Boris Podobnik & Youngki Lee, 2004. "Common Scaling Patterns in Intertrade Times of U. S. Stocks," Papers cond-mat/0403662, arXiv.org.
    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, vol. 387(23), pages 5818-5825.
    18. Sazuka, Naoya, 2007. "On the gap between an empirical distribution and an exponential distribution of waiting times for price changes in a financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 500-506.
    19. Marcus Lim & Richard Coggins, 2005. "The immediate price impact of trades on the Australian Stock Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 365-377.
    20. Karpio, Krzysztof & Załuska–Kotur, Magdalena A. & Orłowski, Arkadiusz, 2007. "Gain–loss asymmetry for emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 599-604.
    21. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    22. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.
    23. Qiu, T. & Zhong, L.X. & Chen, G. & Wu, X.R., 2009. "Statistical properties of trading volume of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2427-2434.
    24. Niu, Hongli & Wang, Jun & Lu, Yunfan, 2016. "Fluctuation behaviors of financial return volatility duration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 30-40.
    25. Magdalena A. Zaluska-Kotur & Krzysztof Karpio & Arkadiusz Orlowski, 2006. "Comparison of gain-loss asymmetry behavior for stocks and indexes," Papers physics/0608214, arXiv.org.
    26. Gabaix, Xavier & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Stanley, Eugene, 2007. "A unified econophysics explanation for the power-law exponents of stock market activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 81-88.
    27. Vygintas Gontis & Shlomo Havlin & Aleksejus Kononovicius & Boris Podobnik & H. Eugene Stanley, 2015. "Stochastic model of financial markets reproducing scaling and memory in volatility return intervals," Papers 1507.05203, arXiv.org, revised Oct 2016.
    28. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    29. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    30. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2003. "A theory of power-law distributions in financial market fluctuations," Nature, Nature, vol. 423(6937), pages 267-270, May.
    31. F. Ren & B. Zheng & H. Lin & L. Y. Wen & S. Trimper, 2005. "Persistence Probabilities of the German DAX and Shanghai Index," Papers nlin/0511048, arXiv.org.
    32. Xi-Yuan Qian & Ya-Min Liu & Zhi-Qiang Jiang & Boris Podobnik & Wei-Xing Zhou & H. Eugene Stanley, 2015. "Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces," Papers 1504.02435, arXiv.org, revised Apr 2015.
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