Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

M. Wang, J. Wang and B.T. Wang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 492, issue C, 1481-1494

Abstract: Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Keywords: Multiscale synchrony analysis; 3D multi-continuum percolation system; Random price series model; Empirical mode decomposition algorithm; Cross recurrence quantification analysis; Multiscale cross-sample entropy (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:492:y:2018:i:c:p:1481-1494

DOI: 10.1016/j.physa.2017.11.075

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