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由于原油市场的收益率具有尖峰厚尾的特征,因此,可以利用GARCH模型中的条件方差来度量Va R(Value at Risk)。本文基于AR-GARCH模型的Va R方法对美国中质原油市场(WTI)和英国布伦特原油市场(Brent)进行了分析。结果表明能源市场价格波动具有尖峰、厚尾、有偏的特征,更为符合t分布;样本市场的收益率序列呈现出自相关、波动聚类和条件方差的典型特征;基于不同分位点处的Va R序列具有显著的同步性,但是美国WTI原油市场价格的Va R序列比英国Brent原油市场价格的Va R序列波动更为剧烈,尤其是在金融危机期间,表现的更为明显。
Because the crude oil market returns have the characteristic of peak and thick tail, VaR (Value at Risk) can be measured by conditional variance in GARCH model. In this paper, VaR method based on AR-GARCH model is used to analyze the WTI and Brent in the United States. The results show that the energy market volatility has peak, thick tail and biased features, more in line with the t distribution; the sample market returns series presents a typical feature of self-correlation, volatility clustering and conditional variance; based on the different sub-site However, the VaR sequence of the market price of WTI crude oil in the United States is more volatile than the VaR sequence of the market price of Brent crude oil in the United Kingdom, especially during the financial crisis.