Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 403, Issue -, Pages 35-44Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2014.02.023
Keywords
Multiscale analysis; Multifractal analysis; Detrended cross-correlation analysis; Financial time series
Categories
Funding
- China National Science [61071142, 61371130]
- Beijing National Science [4122059]
- Fundamental Research Funds for the Central Universities [2013JBM089]
- China Postdoctoral Science Foundation [2012M520156]
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In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way. (c) 2014 Elsevier B.V. All rights reserved.
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