title: Multifractal detrended cross-correlation analysis for two nonstationary signals.
abstract: We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.
authors.affiliation: School of Business, School of Science, Research Center for Econophysics, and Research Center of Systems Engineering, East China University of Science and Technology, Shanghai 200237, China. wxzhou@ecust.edu.cn
authors.forename: Wei-Xing
authors.initials: WX
authors.lastname: Zhou