2017/10/30 by Amir Hossein Shirazi, Abbas Ali Saberi, Shirazi, Amir Hossein +7
Physics and Astronomy · #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.stat-mech #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1710.11267
10 pages, 6 figures, to appear in Scientific Reports (2017)
arxiv created 2017/10/30 · arxiv updated 2017/11/01
Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.