Abstract
The study presents FRM@China, a novel risk meter that uses quantile-lasso regression to detect systemic financial risk and dependencies of tail-events among critical financial institutions in China. The analysis demonstrates the high level of robustness of FRM@China in predicting tail-event risks and a negative correlation between FRM@China and FIs' TE risk interconnectedness. To address limitations of the current FRM approach, the study employs the Shapley value to assess the impact of different macroeconomic variables. The results offer policymakers a valuable tool for monitoring market liquidity and evaluating financial policy responses to prevent severe financial risks.
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