摘要
对于多元金融资产组合,针对资产收益的厚尾性、波动的异方差性及资产间的非线性相关结构等特征,采用SV-t模型与极值理论结合刻画单个资产收益的波动性及尾部分布特征,应用Copula函数处理多元资产间的相关性,并结合Monte Carlo模拟对投资组合进行风险测度.通过对华安创新基金的实证分析结果表明,基于SV-GPD的边缘分布模型能有效地刻画金融资产收益时序并较为精确地处理资产收益尾部的异常变化,相比其他风险度量模型具有更好的优越性,基于Copula-SV-GPD模型的多元资产组合对风险测度能力更强,能有效地管理投资风险.
In view of the characteristics of fat tail, fluctution heteroscedasticity and nonlinear correlation of the combination of multiple financial portfolios, this paper combines the SV-t models with the EVT to depict the single asset return volatility and tail characteristics, and applies the Copula function to treat with the non-linear structures among assets and measures the risk of portfolio by Monte Carlo simulation. By empirical research of Hua An Innovation Fund, it is found that the risk measurement model can effectively manage investment risk based on Copula-SV-GPD method, which could effectively depict the time series of returns of financial assets and accurately treat abnormal changes of the tail.
出处
《管理科学学报》
CSSCI
北大核心
2012年第12期70-78,共9页
Journal of Management Sciences in China
基金
国家自然科学基金资助项目(70473107)
中央高校基本科研业务费资助项目(CDJXS11021112)
作者简介
周孝华（1965-），男，湖南武冈人，博士，教授，博士生导师．Email：zhxiaoh@yahoo．com．cn
