2022International Journal of Finance & EconomicsRequires access

Systemic risk and idiosyncratic networks among global systemically important banks

Xue Cui, Lu Yang

Open publisher page 11 citations

Abstract

Abstract In this article, we investigate the role played by idiosyncratic networks in systemic risk transmission among global systemically important banks. To construct idiosyncratic networks, we employ the conditional Granger causality approach and find they are unstable in the short term and stable in the long term. Additionally, we visualise dynamic idiosyncratic networks and confirm that their evolutionary pattern is similar to that of systemic risk. Moreover, we further explore systemic risk and idiosyncratic networks at an individual level and determine that in‐degree and in‐strength measures negatively influence systemic risk. This indicates that a well‐connected idiosyncratic network in the banking system is prone to risk spillover and cause idiosyncratic contagion. The results of the network analysis indicate that global banking idiosyncratic networks are a complex system and can serve as a valuable reference for investors and policymakers.

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What this paper is about

Abstract In this article, we investigate the role played by idiosyncratic networks in systemic risk transmission among global systemically important banks. To construct idiosyncratic networks, we employ the conditional Granger causality approach and find they are unstable in the short term and stable in the long term. Additionally, we visualise dynamic idiosyncratic networks and confirm that their evolutionary pattern is similar to that of systemic risk. Moreover, we further explore systemic risk and idiosyncratic networks at an individual level and determine that in‐degree and in‐strength measures negatively influence systemic risk. This indicates that a well‐connected idiosyncratic network in the banking system is prone to risk spillover and cause idiosyncratic contagion. The results of the network analysis indicate that global banking idiosyncratic networks are a complex system and can serve as a valuable reference for investors and policymakers.

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Available abstract

Abstract In this article, we investigate the role played by idiosyncratic networks in systemic risk transmission among global systemically important banks. To construct idiosyncratic networks, we employ the conditional Granger causality approach and find they are unstable in the short term and stable in the long term. Additionally, we visualise dynamic idiosyncratic networks and confirm that their evolutionary pattern is similar to that of systemic risk. Moreover, we further explore systemic risk and idiosyncratic networks at an individual level and determine that in‐degree and in‐strength measures negatively influence systemic risk. This indicates that a well‐connected idiosyncratic network in the banking system is prone to risk spillover and cause idiosyncratic contagion. The results of the network analysis indicate that global banking idiosyncratic networks are a complex system and can serve as a valuable reference for investors and policymakers.

Key concepts: Systemic risk, Systematic risk, Spillover effect, Causality (physics), Construct (python library), Economics, Econometrics, Monetary economics

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