| Author(s): |
prof. PhDr. Ladislav Krištoufek Ph.D.,
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| Type: |
Articles in journals with impact factor |
| Year: |
2017 |
| Number: |
0 |
| ISSN / ISBN: |
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| Published in: |
Communications in Nonlinear Science and Numerical Simulation 50, pp. 193-200 arXiv PDF |
| Publishing place: |
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| Keywords: |
power-law coherency, power-law cross-correlations, correlations |
| JEL codes: |
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| Suggested Citation: |
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| Abstract: |
We focus on power-law coherency as an alternative approach towards studying power-law cross-correlations between simultaneously recorded time series. To be able to study empirical data, we introduce three estimators of the power-law coherency parameter $H_{\rho}$ based on popular techniques usually utilized for studying power-law cross-correlations -- detrended cross-correlation analysis (DCCA), detrending moving-average cross-correlation analysis (DMCA) and height cross-correlation analysis (HXA). In the finite sample properties study, we focus on the bias, variance and mean squared error of the estimators. We find that the DMCA-based method is the safest choice among the three. The HXA method is reasonable for long time series with at least $10^4$ observations, which can be easily attainable in some disciplines but problematic in others. The DCCA-based method does not provide favorable properties which even deteriorate with an increasing time series length. The paper opens a new venue towards studying cross-correlations between time series. |
