为了量化资产之间相依结构的局部特征,本文将小波阈值规则引入Copula参数估计,提出多元Copula密度的小波局部闽值估计量,发现Copula密度的光滑度指数、维数和采样容量是影响估值精度的重要因素,这一点也得到了以正态Copula为仿真算例的支持。本方法增强了参数Copula建模的局部自适应能力,进而有助于改进资产的市场风险估值与最优化配置。
In order to quantify the local characteristics of the dependency structure among assets, Wavelet threshold rules are introduced into Copula parameter estimation. This paper provides a local threshold estimator of the multivariate copulas density. It is shown that three important factors which have effect on the estimation precision are sample size, variable dimension and smoothness index of copula density, and the following simulation of normal Copula supports the result. Thus, our methods enhance the local self-adaptation of a parametric Copula and help to improve the valuation of Value-at-Risk and optimization of assets allocation.