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Titulo |
Non-criticality of interaction network over system´s crises: A percolation analysis |
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Autoría |
Shirazi AH, Saberi AA, Hosseiny A, Amirzadeh E, Toranj Simin P. |
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Fuente |
Sci Rep. 2017 Nov 20;7(1):15855. doi: 10.1038/s41598-017-16223-6. |
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Resumen |
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. |
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URL |
www.ncbi.nlm.nih.gov/pubmed/29158531 |
