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Abstract and Applied Analysis
Volume 2014, Article ID 965081, 13 pages
Research Article

Nonlinear Behaviors of Tail Dependence and Cross-Correlation of Financial Time Series Model

Institute of Financial Mathematics and Financial Engineering, School of Science, Beijing Jiaotong University, Beijing 100044, China

Received 20 March 2014; Revised 30 April 2014; Accepted 2 May 2014; Published 28 May 2014

Academic Editor: Rehana Naz

Copyright © 2014 Wei Deng and Jun Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Nonlinear behaviors of tail dependence and cross-correlation of financial time series are reproduced and investigated by stochastic voter dynamic system. The voter process is a continuous-time Markov process and is one of the interacting dynamic systems. The tail dependence of return time series for pairs of Chinese stock markets and the proposed financial models is studied by copula analysis, in an attempt to detect and illustrate the existence of relevant correlation relationships. Further, the multifractality of cross-correlations for return series is studied by multifractal detrended cross-correlation analysis, which indicates the analogous cross-correlations and some fractal characters for both actual data and simulative data and provides an intuitive evidence for market inefficiency.