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如何准确度量金融市场风险在金融风险管理中扮演着重要角色,而极值理论能对极端风险进行较准确的度量。通过对沪深300指数的实证研究表明,广义帕累托分布能够很好地拟合极端日收益率数据,从而用建立在广义帕累托分布基础上的POT模型来度量投资者所面临的市场风险是合适的。结果显示:基于正态分布假设得到的风险值小于POT模型的风险值。
How to accurately measure financial market risk plays an important role in financial risk management, and extreme value theory can make a more accurate measurement of extreme risk. Empirical studies on the CSI300 Index show that the generalized Pareto distribution can well fit the extreme daily rate of return data and thus measure the market investors face with the POT model based on the generalized Pareto distribution Risk is appropriate. The results show that the risk value based on the assumption of normal distribution is less than the risk value of POT model.