APARCH-PET模型的VaR度量
VaR Measure Based on APARCH-PET Models
DOI: 10.12677/SA.2022.116162, PDF,    科研立项经费支持
作者: 徐慧颖*, 魏正元, 何青霞, 杨 洁：重庆理工大学理学院，重庆
关键词: Edgeworth展开；APARCH模型；VaR；Edgeworth Expansion； APARCH Model； VaR
摘要: 本文提出了一种包含PES的正Edgeworth截断分布(PET)，给出了APARCH-PET模型的VaR表达式，研究了APARCH-PET与经典模型的数据拟合效果。选用上证主板招商银行股票数据进行实证分析，结果表明：PET分布在拟合资产收益率数据的尾部特征时更具优势，构建的APARCH-PET模型能更好的刻画金融资产收益率数据分布的尖峰、厚尾特征和非对称性，且一定程度上提高了VaR度量的预测精度。
Abstract: In this paper, a positive Edgeworth truncated distribution (PET) including PES is proposed, the VaR expression of APARCH-PET model is given, and the data fitting effect of APARCH-PET and classical model is studied. The empirical analysis results show that PET distribution has more advantages in fitting the tail characteristics of asset yield data, and the APARCH-PET model can better depict the spike, thick-tail characteristics and asymmetry of financial asset yield data distribution, and improve the prediction accuracy of VaR measurement to a certain extent.
文章引用：徐慧颖, 魏正元, 何青霞, 杨洁. APARCH-PET模型的VaR度量[J]. 统计学与应用, 2022, 11(6): 1564-1573. https://doi.org/10.12677/SA.2022.116162

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