In this study, we present a novel measurement approach for systemic risk by considering an indirect network structure. In a departure from previous studies, this measurement method captures spillovers arising from deleveraging and price impact in financial systems and calculates the amplification of losses during the contagion process. We show the relationship between a bank's vulnerability and its network connections. Applying the model to Chinese banks, we evaluate the fire-sale loss of each bank and quantify the impact of each asset in different simulated stress scenarios. Using both theoretical and empirical evidence, we show the ability of network centrality to explain systemic risk contribution: a bank with more network connections is systemically more important. We also present an optimal strategy to mitigate and govern systemic risk. Our result implies that the systemic importance of a bank is based not only on its size but also on the kinds of assets it holds; it provides useful systemic risk monitoring tools complementary to those currently used by supervisors.
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Cao et al. (2021) studied this question.
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