  It is ubiquitous in natural and social sciences that two variables, recorded
temporally or spatially in a complex system, are cross-correlated and possess
multifractal features. We propose a new method called multifractal detrended
cross-correlation analysis (MF-DXA) to investigate the multifractal behaviors
in the power-law cross-correlations between two records in one or higher
dimensions. The method is validated with cross-correlated 1D and 2D binomial
measures and multifractal random walks. Application to two financial time
series is also illustrated.
