Abstract:

Reasonable measurement and accurate identification of financial market risks are of great significance for stabilizing the economy and effectively preventing financial risks. According to the characteristics of China's financial market, this paper uses the dynamic CRITIC method to establish the measurement model to calculate the financial stress index, and estimates and identifies the distribution and risk state of financial stress index through non-parametric statistical kernel density method and B-N data decomposition method and the Markov Regime Switching Model is used to test the high and low risk transformation probability of financial stress index to compare with the results identified by deterministic items. The research results indicate that the financial pressure index based on dynamic CRITIC weighting method can better reflect the extreme values and financial risks of the financial market. Random shocks are an important factor affecting China's financial pressure index, and both financial risk identification methods can identify the financial risk status and each has its own advantages. In the future, it is of great necessity to establish a more complete risk measurement index system, further improve the regulatory system, and strengthen macro-prudential management and prevention of financial risks.

Key words: financial stress index, dynamic CRITIC method, B-N data decomposition method, Markov regime switching model