合理测度和准确识别金融市场风险，对于稳定经济、有效防范金融风险意义重大。依据中国金融市场特征，本文采用动态CRITIC法计算权重并建立金融压力指数测度模型，通过非参数统计核密度法和B-N数据分解法对金融压力指数的分布和金融风险状态进行估计与识别，采用马尔科夫区制转换模型检验高低风险转换概率，并与基于确定项进行识别的结果进行对比分析。研究表明：基于动态CRITIC赋权的金融压力指数更能反映金融市场的极端值和金融风险，随机冲击是影响我国金融压力指数的重要因素，两种金融风险识别方法均可识别金融风险状态且各有优势，研究中可以互为补充。今后应建立更加完善的风险测度指标体系，进一步完善监管制度，加强对金融风险的宏观审慎管理和防范。

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.