基于正态逆高斯分布的VaR计算方法OA
VaR calculation method based on normal inverse Gaussian distribution
正态逆高斯(NIG)分布能对金融资产收益率分布做出准确描述.首先,介绍NIG分布及其参数估计方法;其次给出正态逆高斯分布下风险价值(VaR)的2种求法并对上证互联网金融指数进行实证分析,计算正态逆高斯分布下的VaR并与正态分布下的VaR进行比较;最后,进行Kupiec失败频率检验判断计算的合理性.经实证分析得出:正态逆高斯分布能够体现金融资产收益率分布的尖峰厚尾特征,在高置信水平下的VaR计算较正态分布更加准确,使用正态逆高斯分布对金融数据分析能够有效地避免金融风险被低估.
The normal inverse Gaussian distribution can accurately describe the distribution of financial asset returns.Firstly,introduce the normal inverse Gaussian distribution and its parameter estimation methods.Secondly,provide two methods for calculating VaR values under the normal inverse Gaussian distribution.Then,the empirical analysis of the Shanghai Stock Exchange internet financial index is carried out,and the VaR value under the normal inverse Gaussian distribution is calculated and compared with the VaR value under the normal distribution.Finally,conduct a Kupiac failure frequency test to determine the reasonableness of the calculation.Empirical analysis shows that the normal inverse Gaussian distribution can reflect the peak and fat tail characteristics of the distribution of financial asset returns,and the calculation of VaR values at high confidence levels is more accurate than the normal distribution.Using the normal inverse Gaussian distribution for financial data analysis can effectively avoid underestimating financial risks.
刘龙;任芳玲
延安大学数学与计算机科学学院,陕西 延安 716000延安大学数学与计算机科学学院,陕西 延安 716000
管理科学
正态逆高斯分布尖峰厚尾风险价值Kupiec失败频率检验
normal inverse Gaussian distributionpeak thick tailVaRKupiec failure frequency check
《首都师范大学学报(自然科学版)》 2026 (3)
74-79,6
陕西省大学生创新创业训练计划项目(S202410719092)延安大学教学改革研究项目(YDJGZD23-05)
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