Cascading Failures in Interdependent Economic Networks

Abstract

Throughout the past decade, there has been a significant advance in understanding the structure and function of networks, and mathematical models of networks are now widely used to describe a broad range of complex systems, such as socio-economic systems. However, the significant majority of methods have dealt almost exclusively with individual networks treated as isolated systems. In reality an individual network is often just one component in a much larger complex multi-level network (network of networks, NON). The NON framework provides critical new insights into the structure and function of real-world complex systems. One such insight is that NON system is significantly more vulnerable to shocks and damages, which has lead to the development of the theory of cascading failures in interdependent networks. Here we provide an overview of this theory, and one example of its application to economic systems. IntroductionThe growth of technology, globalization, and urbanization has caused world-wide human social and economic activities to become increasingly interdependent [1][2][3][4][5][6][7][8][9][10][11][12][13]. From the recent financial crisis it is clear that components of this complex system have become increasingly susceptible to collapse. Current models have been unable to predict instability, provide scenarios for future stability, or control or even mitigate systemic failure. Thus, there is a need of new ways of quantifying complex system vulnerabilities as well as new strategies for mitigating systemic damage and increasing system resiliency [14,15]. Achieving this would also provide new insight into such key issues as financial contagion [16,17] and systemic risk [18][19][20] and would provide a way of maintaining economic and financial stability in the future.

The general dynamic risk assessment for the enterprise by the hologram approach in financial technology

“…For example, there is a strong coupling between human mobility (which can be tracked by mobile networks) and transport networks. In these interdependent networks, the failures of nodes in one network will cause failures of dependent nodes in other networks, and vice versa (see Parshani et al (2010), Bashan et al (2013), Gao et al (2012), , Boccaletti et al (2014), Lee et al (2012), Baxter et al (2012), Forbes and Rigobon (2002) on interdependence for the study of stock market co-movements, and references therein), and the survey reference on the cascading failures in interdependent economic networks for related advanced study by Havlin and Kenett (2015) and references therein. At the same time, though the study of systemic risk in banking ecosystems becomes a challenging issue, this has been attracted by a number of scholars internationally.…”

A Stochastic Model for Cascading Failures in Financial Networks

“…The literature on cascading failures is vast and grows in several directions, some of which depart from the scope of this article. For instance, the vulnerability of interdependent economic networks, also referred to as network of networks, is studied in [12]. The entanglement of financial and biological interdependent contagion networks is analyzed in [13].…”

“…For each company, we simulate the sample error according to dynamics (12), the mean error according to dynamics (15) and the variance error according to dynamics (22). The results are depicted in Fig.…”

“…5. Time plot of the evolution of the error X(t) obtained from (12) for increased noise parameter K = 300. Fig.…”

Evolution of threats in the global risk network

“…Unlike here, the authors do not even attempt to match the model with historical data. In (Kenett et al 2015 ; 2012 ; Raddant and Kenett 2016 ; Havlin and Kenett 2015 ), the authors observe historical correlations between stock prices and build stock dependency networks. They also consider events that may affect the stock market such as “tsunami in Japan”.…”