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将表现状态转换的Markov过程引入了ARCH模型,通过对上证综指的实证研究,采用SW-ARCH模型并利用非参数核密度估计技术辨识了在全球性金融危机冲击下我国股市出现的大幅异常波动状态,并用Kupiec的失败频率检验法对VaR的准确性进行检验来验证模型的有效性.结果表明:我国股市有着显著的状态转换特征,且重大事件或政策是导致我国股市状态转移的重要原因,基于SW-ARCH模型的VaR能有效反映我国股市风险.
By introducing the Markov process of state transition into the ARCH model, this paper uses the SW-ARCH model and the non-parametric kernel density estimation to identify the significant anomalies in the stock market in the global financial crisis through the empirical research of the Shanghai Composite Index And verifies the validity of the model by using Kupiec’s failure frequency test to verify the validity of the model.The results show that China’s stock market has significant state transition characteristics and major events or policies are the important reasons leading to the state transition of the stock market in our country, VaR based on SW-ARCH model can effectively reflect the risk of China’s stock market.