Emergence of frustration signals systemic risk
arXiv:1807.02923 · doi:10.1103/PhysRevE.99.052306
Abstract
We show that the emergence of systemic risk in complex systems can be understood from the evolution of functional networks representing interactions inferred from fluctuation correlations between macroscopic observables. Specifically, we analyze the long-term collective dynamics of the New York Stock Exchange between 1926-2016, showing that periods marked by systemic crisis, viz., around the Great Depression of 1929-33 and the Great Recession of 2007-09, are associated with emergence of frustration indicated by the loss of structural balance in the interaction networks. During these periods the dominant eigenmodes characterizing the collective behavior exhibit delocalization leading to increased coherence in the dynamics. The topological structure of the networks exhibits a slowly evolving trend marked by the emergence of a prominent core-periphery organization around both of the crisis periods.
arXiv comment6 pages, 4 figures
References in corpus (18)
- Statistical physics of social dynamics
- Mixing patterns in networks
- Noise Dressing of Financial Correlation Matrices
- Emergent complex neural dynamics
- Universal and non-universal properties of cross-correlations in financial time series
- A Random Matrix Approach to Cross-Correlations in Financial Data
- Herd behavior and aggregate fluctuations in financial markets
- Clustering and information in correlation based financial networks
- Dynamics of Social Balance on Networks
- Analysis of community structure in networks of correlated data
- Pathways towards instability in financial networks
- Collective behavior of stock price movements in an emerging market
- Mapping multiplex hubs in human functional brain network
- The cost of attack in competing networks
- Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize
- How Damage Diversification Can Reduce Systemic Risk
- Systemic risk in dynamical networks with stochastic failure criterion
- Localization in covariance matrices of coupled heterogenous Ornstein-Uhlenbeck processes