Systemic risk and idiosyncratic networks among global systemically important banks

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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“…Inspired by the growing financial literature focused on identifying risk networks in the financial system [13,[23][24][25], these studies aim to identify the international stock price network and uncover the primary risk contributor and intensity of the interconnectedness Disclaimer/Publisher's Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.…”

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“…Inspired by the growing financial literature focused on identifying risk networks in the financial system [10,[20][21][22], these studies aim to identify the international stock price network and uncover the primary risk contributor and intensity of the interconnectedness of extreme Systems 2023, 11, 207 2 of 17 risk within the network. Understanding the structure and dynamics of connectedness in the international stock market network by measuring extreme risk spillovers is of great significance, with this information being crucial for identifying early signs of systemic risk and enhancing the stock price network's resilience to systemic events.…”