Abstract
We analyse systemic risk in the core global banking system using a new network-based spectral eigen-pair method, which treats network failure as a dynamical system stability problem. This is compared with market price-based Systemic Risk Indexes (SRIs), viz. Marginal Expected Shortfall (MES), Delta Conditional Value-at-Risk (Delta-CoVaR), and Conditional Capital Shortfall Measure of Systemic Risk (SRISK) in a cross-border setting. Unlike paradoxical market price based risk measures, which underestimate risk during periods of asset price booms, the eigen-pair method based on bilateral balance sheet data gives early-warning of instability in terms of the tipping point that is analogous to the R number in epidemic models. For this regulatory capital thresholds are used. Furthermore, network centrality measures identify systemically important and vulnerable banking systems. Market price-based SRIs are contemporaneous with the crisis and they are found to covary with risk measures like VaR and betas.
Highlights
The importance of banking system stability and cross-border propagation of contagion has been underscored by the 2007 Global Financial Crisis (GFC)
One of the clear shortcomings of macro-prudential analyses has been the lack of systemic risk models that can, even after the event, identify the threats from large exposures that the global banking system had to US banking sector liabilities in the run up to the GFC
It is increasingly being understood, and as underscored in this study, that paradoxical systemic risk measures based on market price data will fail to give early warning of banking system crises from growing interbank liabilities
Summary
The importance of banking system stability and cross-border propagation of contagion has been underscored by the 2007 Global Financial Crisis (GFC). The necessity of the fixed point algorithm that produces internal consistency of an interconnected system has been recommended by Gauthier et al (2012) for systemic risk indexes By tracking these SRI indexes over time for financial networks directly based on contractual balance sheet data for national and global banking systems, there can be early warning of potential systemic failure and for the identification of sudden changes in the rank order for the centrality of nodes. The latter can help in regulatory interventions as well as the in the design of Pigou type externalities funds that can stabilze the system, Markose et al (2017).
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