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时变Copula模型非参数估计的大样本性质 被引量：2

Large sample properties of nonparametric estimation in time-varying Copula model
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摘要 运用Copula模型研究随机变量间的相关结构,是近年来金融统计分析中的一个热点.在龚金国和史代敏提出时变Copula非参数模型的基础上,利用时间序列的极限理论研究了时变参数估计量的大样本性质,并给出了时变Copula模型的非参数估计算法.研究结果表明,时变Copula非参数模型的时变参数估计量具有一致性和渐近正态性. It becomes a hot topic in the financial statistics analysis that Copula model is applied to discuss the dependence structure among random variables.Based on the time-varying Copula nonparametric model given by GONG Jin-guo and SHI Dai-min(2011),this paper mainly discusses the large sample properties of the estimators of time-varying parameters by the asymptotic theory for time series and gives the algorithm of nonparametric estimation in time-varying Copula model.The result shows that the nonparametric estimators of time-varying parameters have consistency and asymptotic normality.
作者 龚金国 史代敏
机构地区 西南财经大学统计学院
出处 《浙江大学学报（理学版）》 CAS CSCD 2012年第6期630-634,642,共6页 Journal of Zhejiang University（Science Edition）
基金 国家社会科学基金青年项目(12CTJ007) 国家自然科学基金面上项目(71171166 71171168) 教育部人文社会科学研究西部和边疆地区项目(11XJC910001) 西南财经大学科研基金资助项目(2011XG119) 西南财大"211工程"三期青年成长项目(211QN2011031)
关键词 时变COPULA 局部极大似然估计 一致性 渐近正态性 time-varying Copula local maximum likelihood estimation consistency asymptotic normality
分类号 O211.4 [理学—概率论与数理统计]
  • 相关文献

参考文献9

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二级参考文献13

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共引文献11

同被引文献16

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引证文献2

二级引证文献3

浙江大学学报（理学版）
2012年 第6期

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