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# Network Risk and Forecasting Power in Phase-Flipping Dynamical Networks

## Author

Listed:
• B. Podobnik
• A. Majdandzic
• C. Curme
• Z. Qiao
• W. -X. Zhou
• H. E. Stanley
• B. Li

## Abstract

In order to model volatile real-world network behavior, we analyze phase-flipping dynamical scale-free network in which nodes and links fail and recover. We investigate how stochasticity in a parameter governing the recovery process affects phase-flipping dynamics, and find the probability that no more than q% of nodes and links fail. We derive higher moments of the fractions of active nodes and active links, $f_n(t)$ and $f_{\ell}(t)$, and define two estimators to quantify the level of risk in a network. We find hysteresis in the correlations of $f_n(t)$ due to failures at the node level, and derive conditional probabilities for phase-flipping in networks. We apply our model to economic and traffic networks.

## Suggested Citation

• B. Podobnik & A. Majdandzic & C. Curme & Z. Qiao & W. -X. Zhou & H. E. Stanley & B. Li, 2014. "Network Risk and Forecasting Power in Phase-Flipping Dynamical Networks," Papers 1401.7450, arXiv.org.
• Handle: RePEc:arx:papers:1401.7450
as

File URL: http://arxiv.org/pdf/1401.7450

## References listed on IDEAS

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1. Robert L. Hetzel, 1991. "Too big to fail : origins, consequences, and outlook," Economic Review, Federal Reserve Bank of Richmond, issue Nov, pages 3-15.
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## Citations

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Cited by:

1. Yao, Can-Zhong & Lin, Ji-Nan & Zheng, Xu-Zhou & Liu, Xiao-Feng, 2015. "The study of RMB exchange rate complex networks based on fluctuation mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 359-376.

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