nep-ets New Economics Papers
on Econometric Time Series
Issue of 2016‒11‒06
one paper chosen by
Yong Yin
SUNY at Buffalo

  1. Joint multifractal analysis based on wavelet leaders By Zhi-Qiang Jiang; Yan-Hong Yang; Gang-Jin Wang; Wei-Xing Zhou

  1. By: Zhi-Qiang Jiang (ECUST, BU); Yan-Hong Yang (ECUST, BU); Gang-Jin Wang (HNU, BU); Wei-Xing Zhou (ECUST)
    Abstract: Mutually interacting components form complex systems and the outputs of these components are usually long-range cross-correlated. Using wavelet leaders, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable to detect the cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to the pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and find an intriguing joint multifractal behavior.
    Date: 2016–11

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