详细信息

Joint multifractal analysis based on wavelet leaders  ( SCI-EXPANDED收录)  

文献类型:期刊文献

英文题名:Joint multifractal analysis based on wavelet leaders

作者:Jiang, Zhi-Qiang[1,2,3,4];Yang, Yan-Hong[1,2,3,4];Wang, Gang-Jin[3,4,5,6];Zhou, Wei-Xing[1,2,7]

机构:[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[3]Boston Univ, Dept Phys, Boston, MA 02215 USA;[4]Boston Univ, Ctr Polymer Studies, Boston, MA 02215 USA;[5]Hunan Univ, Business Sch, Changsha 410082, Hunan, Peoples R China;[6]Hunan Univ, Ctr Finance & Investment Management, Changsha 410082, Hunan, Peoples R China;[7]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China

年份:2017

卷号:12

期号:6

外文期刊名:FRONTIERS OF PHYSICS

收录:;WOS:【SCI-EXPANDED(收录号:WOS:000411012200009)】;

基金:We acknowledge financial support from the National Natural Science Foundation of China (11375064 and 71532009), the Program for Changjiang Scholars and Innovative Research Team in University (IRT1028), and the Fundamental Research Funds for the Central Universities.

语种:英文

外文关键词:joint multifractal analysis; wavelet leader; binomial measure; bivariate fractional Brownian motion; econophysics; online world

摘要:Mutually interacting components form complex systems and these components usually have longrange cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method 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 dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

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