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A method for analyzing correlation between multiscale and multivariate systems—Multiscale multidimensional cross recurrence quantification (MMDCRQA)

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  • He, Qian
  • Huang, Jingjing

Abstract

In this paper, multiscale multidimensional cross recurrence quantification analysis (MMDCRQA) is introduced and we employ this method to investigate the correlation between two systems with multiscales and multidimensions. Compared with single time scale, the MMDCRQA based on multiscale time series can show richer and more recognizable information. Both model systems (Lorenz and Rössler systems) and stock market indexes (SSEC and SZSE) exhibit that the MMDCRQA can explore the dynamic characteristics at different time scales. It demonstrates that the MMDCRQA can investigate the dynamic characteristics and correlation between two multidimensional systems at different time scales.

Suggested Citation

  • He, Qian & Huang, Jingjing, 2020. "A method for analyzing correlation between multiscale and multivariate systems—Multiscale multidimensional cross recurrence quantification (MMDCRQA)," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:chsofr:v:139:y:2020:i:c:s096007792030463x
    DOI: 10.1016/j.chaos.2020.110066
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    References listed on IDEAS

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    Cited by:

    1. M. Shabani & M. Magris & George Tzagkarakis & J. Kanniainen & A. Iosifidis, 2023. "Predicting the state of synchronization of financial time series using cross recurrence plots," Post-Print hal-04415269, HAL.
    2. Mostafa Shabani & Martin Magris & George Tzagkarakis & Juho Kanniainen & Alexandros Iosifidis, 2022. "Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots," Papers 2210.14605, arXiv.org, revised Nov 2022.

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