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On the interplay between short and long term memory in the power-law cross-correlations setting

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  • Ladislav Kristoufek

Abstract

We focus on emergence of the power-law cross-correlations from processes with both short and long term memory properties. In the case of correlated error-terms, the power-law decay of the cross-correlation function comes automatically with the characteristics of separate processes. Bivariate Hurst exponent is then equal to an average of separate Hurst exponents of the analyzed processes. Strength of short term memory has no effect on these asymptotic properties. Implications of these findings for the power-law cross-correlations concept are further discussed.

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  • Ladislav Kristoufek, 2014. "On the interplay between short and long term memory in the power-law cross-correlations setting," Papers 1409.6444, arXiv.org, revised Dec 2014.
    • Handle: RePEc:arx:papers:1409.6444
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    References listed on IDEAS

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    1. Wen-Jen Tsay, 2007. "Maximum Likelihood Estimation of Stationary Multivariate ARFIMA Processes," IEAS Working Paper : academic research 07-A011, Institute of Economics, Academia Sinica, Taipei, Taiwan.
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    Cited by:

    1. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    2. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    3. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
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    5. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    6. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.

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