Economics at your fingertips  

Joint multifractal analysis based on wavelet leaders

Zhi-Qiang Jiang, Yan-Hong Yang, Gang-Jin Wang and Wei-Xing Zhou
Additional contact information
Zhi-Qiang Jiang: ECUST, BU
Yan-Hong Yang: ECUST, BU

Papers from

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
New Economics Papers: this item is included in nep-ecm and nep-ets
References: Add references at CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

Published in Frontiers of Physics 12 (6), 128907 (2017)

Downloads: (external link) Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Papers from
Bibliographic data for series maintained by arXiv administrators ().

Page updated 2023-09-17
Handle: RePEc:arx:papers:1611.00897