Fractal approach towards power-law coherency to measure cross-correlations between time series
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00473066" target="_blank" >RIV/67985556:_____/17:00473066 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.cnsns.2017.02.018" target="_blank" >http://dx.doi.org/10.1016/j.cnsns.2017.02.018</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.cnsns.2017.02.018" target="_blank" >10.1016/j.cnsns.2017.02.018</a>
Alternative languages
Result language
angličtina
Original language name
Fractal approach towards power-law coherency to measure cross-correlations between time series
Original language description
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 Hp 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 104 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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
<a href="/en/project/GP14-11402P" target="_blank" >GP14-11402P: Bivariate long memory analysis of financial time series</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Communications in Nonlinear Science and Numerical Simulation
ISSN
1007-5704
e-ISSN
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Volume of the periodical
50
Issue of the periodical within the volume
1
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
8
Pages from-to
193-200
UT code for WoS article
000399513200015
EID of the result in the Scopus database
2-s2.0-85014923760