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• W4310896185 abstract "Accurately measuring systemic risk in the banking industry and identifying systemically important banks are significant parts of macro-prudential supervision. However, there is a lack of research on measuring systemic risk and identifying important banks under the same framework. And there are relatively few studies comparing different indicators of systemically important banks in the context of China's banking industry. Therefore, this paper first constructs a new Merton model to measure the dynamically evolving systemic risk of China's banking system. Then combine the Merton model with the Shapley value to construct the Merton-Shapley framework, and propose a new indicator MShv to identify systemically important banks. At last, use the data of China's banking industry from 2006 to 2019 to conduct an empirical study. The research results show that the systemic risk in China peaked in 2008 and 2015 near the stock market crash, after 2008 the risk appeared a fluctuating decline. And it is found that MShv can accurately identify important banks and simultaneously is conducive to policy implementation. By a comparison between MShv and other systemic risk contribution indicators such as ΔCoVaR, MES, and SRISK, we find that there are many differences for different indicators in the applicability of identifying systemically important banks, the information reflected, and so on. Regulators can consider using several indicators synthetically to supervise banks during different risk periods, in order to maintain the stability of the financial system." @default.
• W4310896185 created "2022-12-20" @default.
• W4310896185 creator A5047831569 @default.
• W4310896185 creator A5087439364 @default.
• W4310896185 date "2022-12-01" @default.
• W4310896185 modified "2023-09-30" @default.
• W4310896185 title "Identification of systemically important banks in China based on Merton-Shapley model and a comparison between different indicators" @default.
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• W4310896185 doi "https://doi.org/10.1016/j.heliyon.2022.e12238" @default.
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