IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v515y2019icp388-402.html
   My bibliography  Save this article

Multiscale joint permutation entropy for complex time series

Author

Listed:
  • Yin, Yi
  • Shang, Pengjian
  • Ahn, Andrew C.
  • Peng, Chung-Kang

Abstract

In this paper, we propose the multiscale joint permutation entropy (MJPE) to study the synchronism between two complex time series from the view of ordinal pattern and multiple scales. First, we use the Rossler system using active control, two-component ARFIMA processes to test the effectiveness of MJPE and also add some noise to the ARFIMA time series and apply MJPE to find the effect of noise. The results show the necessity of investigating the synchronism on the multiple scales, prove the effectiveness of MJPE method and show the sensitiveness of MJPE method to noise. Then MJPE method is employed to financial time series and traffic time series to validate the applicability of the proposed MJPE method for the complex time series in the real world. The conclusion from these MJPE results for financial time series is consistent with the actual situation of the synchronism and correlation between stock indices. Meanwhile, the results for traffic time series suggest the need for study the synchronism from the perspective of multiple scales and point out the different synchronisms for traffic time series of weekdays and weekends. MJPE method has a broad application prospect on the investigation of synchronism on the complex time series from different fields.

Suggested Citation

  • Yin, Yi & Shang, Pengjian & Ahn, Andrew C. & Peng, Chung-Kang, 2019. "Multiscale joint permutation entropy for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 388-402.
    • Handle: RePEc:eee:phsmap:v:515:y:2019:i:c:p:388-402
    DOI: 10.1016/j.physa.2018.09.179
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118313098
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2018.09.179?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yin, Yi & Shang, Pengjian, 2013. "Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6442-6457.
    2. Bentes, Sónia R. & Menezes, Rui & Mendes, Diana A., 2008. "Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3826-3830.
    3. Shang, Pengjian & Lin, Aijing & Liu, Liang, 2009. "Chaotic SVD method for minimizing the effect of exponential trends in detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 720-726.
    4. Plerou, Vasiliki & Gopikrishnan, Parameswaran & Rosenow, Bernd & Amaral, Luis A.N. & Stanley, H.Eugene, 2000. "Econophysics: financial time series from a statistical physics point of view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 279(1), pages 443-456.
    5. Yin, Yi & Shang, Pengjian & Feng, Guochen, 2016. "Modified multiscale cross-sample entropy for complex time series," Applied Mathematics and Computation, Elsevier, vol. 289(C), pages 98-110.
    6. Jing Wang & Pengjian Shang & Xiaojun Zhao & Jianan Xia, 2013. "Multiscale Entropy Analysis Of Traffic Time Series," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-14.
    7. Dirk Helbing & Bernardo A. Huberman, 1998. "Coherent moving states in highway traffic," Nature, Nature, vol. 396(6713), pages 738-740, December.
    8. Thuraisingham, Ranjit A. & Gottwald, Georg A., 2006. "On multiscale entropy analysis for physiological data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 323-332.
    9. Xu, Na & Shang, Pengjian & Kamae, Santi, 2009. "Minimizing the effect of exponential trends in detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 311-316.
    10. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    11. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    12. Kai Nagel & Steen Rasmussen, 1994. "Traffic at the Edge of Chaos," Working Papers 94-06-032, Santa Fe Institute.
    13. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    14. Podobnik, Boris & Horvatic, Davor & Lam Ng, Alfonso & Eugene Stanley, H. & Ivanov, Plamen Ch., 2008. "Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3954-3959.
    15. Xin-Gang Li & Zi-You Gao & Jian-Feng Zheng & Bin Jia, 2010. "Network Analysis Of The Evolution Of Traffic Flow With Speed Information," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 177-188.
    16. Costa, M. & Peng, C.-K. & L. Goldberger, Ary & Hausdorff, Jeffrey M., 2003. "Multiscale entropy analysis of human gait dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 53-60.
    17. Shang, Pengjian & Li, Xuewei & Kamae, Santi, 2005. "Chaotic analysis of traffic time series," Chaos, Solitons & Fractals, Elsevier, vol. 25(1), pages 121-128.
    18. Yin, Yi & Shang, Pengjian, 2015. "Modified cross sample entropy and surrogate data analysis method for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 17-25.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shubo Hu & Feixiang Peng & Zhengnan Gao & Changqiang Ding & Hui Sun & Wei Zhou, 2019. "Sample Entropy Based Net Load Tracing Dispatch of New Energy Power System," Energies, MDPI, vol. 12(1), pages 1-23, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yin, Yi & Shang, Pengjian & Feng, Guochen, 2016. "Modified multiscale cross-sample entropy for complex time series," Applied Mathematics and Computation, Elsevier, vol. 289(C), pages 98-110.
    2. Zhang, Ningning & Lin, Aijing & Ma, Hui & Shang, Pengjian & Yang, Pengbo, 2018. "Weighted multivariate composite multiscale sample entropy analysis for the complexity of nonlinear times series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 595-607.
    3. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    4. Zhao, Xiaojun & Shang, Pengjian & Lin, Aijing & Chen, Gang, 2011. "Multifractal Fourier detrended cross-correlation analysis of traffic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3670-3678.
    5. Xu, Kaiye & Shang, Pengjian & Feng, Guochen, 2015. "Multifractal time series analysis using the improved 0–1 test model," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 134-143.
    6. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    7. Yin, Yi & Shang, Pengjian, 2016. "Weighted permutation entropy based on different symbolic approaches for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 137-148.
    8. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    9. He, Jiayi & Shang, Pengjian & Xiong, Hui, 2018. "Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 210-221.
    10. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    11. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    12. Yin, Yi & Wang, Xi & Li, Qiang & Shang, Pengjian, 2020. "Generalized multivariate multiscale sample entropy for detecting the complexity in complex systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    13. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    14. Zhang, Yali & Shang, Pengjian & Sun, Zhenghui, 2018. "Diversity analysis based on ordered patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1126-1133.
    15. Zhang, Yali & Shang, Pengjian & He, Jiayi & Xiong, Hui, 2020. "Cumulative Tsallis entropy based on multi-scale permuted distribution of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    16. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    17. Xu, Meng & Shang, Pengjian, 2018. "Analysis of financial time series using multiscale entropy based on skewness and kurtosis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1543-1550.
    18. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2019. "Complex and composite entropy fluctuation behaviors of statistical physics interacting financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 97-113.
    19. Li, Hongtao & Gedikli, Ersegun Deniz & Lubbad, Raed, 2020. "Exploring time-delay-based numerical differentiation using principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    20. Zhao, Xiaojun & Shang, Pengjian & Zhao, Chuang & Wang, Jing & Tao, Rui, 2012. "Minimizing the trend effect on detrended cross-correlation analysis with empirical mode decomposition," Chaos, Solitons & Fractals, Elsevier, vol. 45(2), pages 166-173.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:515:y:2019:i:c:p:388-402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.