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Discrete scale-invariance in cross-correlations between time series

Author

Listed:
  • Xiao, Qin
  • Pan, Xue
  • Stephen, Mutua
  • Yang, Yue
  • Li, Xinli
  • Yang, Huijie

Abstract

The de-trended cross-correlation analysis (DCCA) is converted to a new form, which turns out to be a periodic function modulated power-law, to evaluate discrete-scale long-range cross-correlation between time series. If the modulator is dominated with one frequency, the derived form will degenerate to a log-periodic power-law. We investigate a total of five important stock markets distributing in different continents. Calculations show that the cross-correlations between different stock markets may hint at log-periodic oscillations. This finding may be helpful for us to evaluate financial state in a global way.

Suggested Citation

  • Xiao, Qin & Pan, Xue & Stephen, Mutua & Yang, Yue & Li, Xinli & Yang, Huijie, 2015. "Discrete scale-invariance in cross-correlations between time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 161-170.
    • Handle: RePEc:eee:phsmap:v:421:y:2015:i:c:p:161-170
    DOI: 10.1016/j.physa.2014.11.032
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    Citations

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    Cited by:

    1. Yue Yang & Changgui Gu & Qin Xiao & Huijie Yang, 2017. "Evolution of scaling behaviors embedded in sentence series from A Story of the Stone," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-14, February.
    2. Wang, Yan-Jun & Zhu, Yun-Feng & Zhu, Chen-Ping & Wu, Fan & Yang, Hui-Jie & Yan, Yong-Jie & Hu, Chin-Kun, 2019. "Indicator of serious flight delays with the approach of time-delay stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 363-373.
    3. Wang, Lei & Liu, Lutao, 2020. "Long-range correlation and predictability of Chinese stock prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).

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