Abstract
From the perspective of financial risk–a more macro level, this letter selected three levels of indicators which reflect emerging risks, synthesized seven dimensional indices, and developed a China financial risk index using two different methods, identifying the risk regime by Markov switching model. The convolution for neural network–long short-term memory model was used to construct an early warning system for financial risks. The model was optimized using regime-based prediction. The empirical results show that the composite dynamic monitoring system and the early warning system have good effects.
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