摘要
传统未分组的藤Copula模型可用于刻画金融资产间的相依性,但存在将所有不同行业资产视为一个整体的问题。本文在充分考虑金融市场中各机构所属行业不同的基础上,提出了藤Copula分组模型,给出了该模型算法的具体步骤,并证明了算法的收敛性。最后通过返回检验方法,对比研究了藤Copula分组模型和未分组的藤Copula模型对银行业、证券业和保险业间VaR估计的精度差异,结果表明藤Copula分组模型的预测效果更准确且更有效。
The traditional Vine Copula model can be used to describe the dependence among financial assets,but it ignores the fact that the assets belong to different industries. Based on fully considering the different industries of financial institutions in financial market,this paper proposes a Vine Copula grouped model,offers the concrete steps of the model algorithm and proves the convergence of the algorithm. Finally,by the backtesting analysis method,it undergoes a comparative research on the precision of the risk measurement among banking,securities and insurance industries using the Vine Copula grouped model and the traditional Vine Copula model. The result shows that the former predicts more accurately and more effectively than the latter.
作者
陈振龙
郝晓珍
Chen Zhenlong;Hao Xiaozhen
出处
《统计研究》
CSSCI
北大核心
2018年第6期77-84,共8页
Statistical Research
基金
国家自然科学基金项目"各向异性随机场与随机偏微分方程的几何性质及其应用"(11371321)
全国统计科学研究项目"基于藤Copula分组模型的金融市场相依风险度量研究"(2017LY51)
浙江省一流学科A类(浙江工商大学统计学)项目资助