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Non-criticality of interaction network over system's crises: A percolation analysis.


ABSTRACT: 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 Erd?s-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.

SUBMITTER: Shirazi AH 

PROVIDER: S-EPMC5696469 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Non-criticality of interaction network over system's crises: A percolation analysis.

Shirazi Amir Hossein AH   Saberi Abbas Ali AA   Hosseiny Ali A   Amirzadeh Ehsan E   Toranj Simin Pourya P  

Scientific reports 20171120 1


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 correl  ...[more]

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