Systemic risk assessment through high order clustering coefficient

In this article we propose a novel measure of systemic risk in the context of financial networks. To this aim, we provide a definition of systemic risk which is based on the structure, developed at different levels, of clustered neighbours around the nodes of the network. The proposed measure incorp...

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Bibliographic Details
Published in:Annals of operations research Vol. 299; no. 1-2; pp. 1165 - 1187
Main Authors: Cerqueti, Roy, Clemente, Gian Paolo, Grassi, Rosanna
Format: Journal Article
Language:English
Published: New York Springer US 01.04.2021
Springer
Springer Nature B.V
Subjects:
Banking
Business and Management
Clustering
Combinatorics
Evaluation
Market risk
Methods
Operations research
Operations Research/Decision Theory
Risk assessment
S.I.: Recent Developments in Financial Modeling and Risk Management
Theory of Computation
Italy
Cross-border banking
G20
C02
Network analysis
Systemic risk
Clustering coefficient
Community structures
G28
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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Summary:In this article we propose a novel measure of systemic risk in the context of financial networks. To this aim, we provide a definition of systemic risk which is based on the structure, developed at different levels, of clustered neighbours around the nodes of the network. The proposed measure incorporates the generalized concept of clustering coefficient of order l of a node i introduced in Cerqueti et al. (2018). Its properties are also explored in terms of systemic risk assessment. Empirical experiments on the time-varying global banking network show the effectiveness of the presented systemic risk measure and provide insights on how systemic risk has changed over the last years, also in the light of the recent financial crisis and the subsequent more stringent regulation for globally systemically important banks.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-020-03525-8