Network Sensitivity of Systemic Risk
Domenico Di Gangi, Donald Ruggiero Lo Sardo, Valentina Macchiati, Tuan Minh Pham, Francesco Pinotti, Amanah Ramadiah, Mateusz Wiliński, Giulio Cimini
Abstract
Domenico Di Gangi, Donald Ruggiero Lo Sardo, Valentina Macchiati, Tuan Minh Pham, Francesco Pinotti, Amanah Ramadiah, Mateusz Wiliński, Giulio Cimini
Abstract
The recent stream of literature of systemic risk in financial markets emphasized the key importance of considering the complex interconnections among financial institutions. Much efforts has been put to model the contagion dynamics of financial shocks, and to assess the resilience of specific financial markets---either using real data, reconstruction techniques or simple toy networks. Here we address the more general problem of how the shock propagation dynamics depends on the topological details of the underlying network. To this end, we consider different network topologies, all consistent with balance sheets information obtained from real data on financial institutions. In particular, we consider networks with varying density and mesoscale structures, and vary as well the details of the shock propagation dynamics. We show that the systemic risk properties of a financial network are extremely sensitive to its network features. Our results can thus aid in the design of regulatory policies to improve the robustness of financial markets.
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The recent stream of literature of systemic risk in financial markets emphasized the key importance of considering the complex interconnections among financial institutions. Much efforts has been put to model the contagion dynamics of financial shocks, and to assess the resilience of specific financial markets---either using real data, reconstruction techniques or simple toy networks. Here we address the more general problem of how the shock propagation dynamics depends on the topological details of the underlying network. To this end, we consider different network topologies, all consistent with balance sheets information obtained from real data on financial institutions. In particular, we consider networks with varying density and mesoscale structures, and vary as well the details of the shock propagation dynamics. We show that the systemic risk properties of a financial network are extremely sensitive to its network features. Our results can thus aid in the design of regulatory policies to improve the robustness of financial markets.
Key concepts: Systemic risk, Financial networks, Robustness (evolution), Balance sheet, Financial market, Financial contagion, Resilience (materials science), Network topology