The statistical model of frequency and intensity of anomalous microtherm events in Nanjing is established by means of the extreme value distribution theory of stationary time series.

本文借助于平稳时间序列的极值分布理论，对南京地区异常低温事件频次和强度建立统计模型。

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Some statistical test methods on "fat tail" distribution of time series are obtained by using properties of extreme value theory and extreme index estimator under large sample.

使用极值理论和极值指数估计量的性质，在大样本的情况下得到序列分布“肥尾”现象的检验方法。

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Extreme value theory models the tail of the return distribution rather than the whole distribution. It can capture the tail risk which often causes large losses in financial institutions.

而应用极值理论计算风险时注重对分布尾部的近似表达，并不是对整个分布进行建模，能更有效地捕捉可能导致金融机构重大损失的尾部风险。

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