四川大学学报（自然科学版）2011，Vol.48Issue(6)：1245-1252,8.DOI:10.3969/j.issn.0490-6756.2011.06.004
资产收益率时间序列的条件异方差模型新探
A new conditionally heteroscedasic model for asset returns time series
摘要
Abstract
Conditionally heteroscedastic models for time series play an important role in todays financial risk management,which typically tries to make financial decisions based on observed discrete time asset price and log-returns.This paper develops a new conditionally heteroscedastic model to fit asset returns,which is driven by bivariate normal continuous mixture of normal(termed BNC-MN) distributed innovations.The model can fully capture the stylized facts of asset returns time series,such as asymmetry,excess kurtosis and volatility clustering,even leverage effect.Meantime it can lend itself to reasonable economic interpretation of these stylized facts,and partly reveal the rationality of generalized autoregressive conditional heteroscedasticity (GARCH)-structure when employed to model asset returns time series.关键词
资产收益率时间序列/条件异方差模型/BNC-MN分布/金融新息/典型特征/尾部在险价值Key words
asset returns time series/conditional heteroscedastic model/BNC-MN distribution/financial innovations/the stylized facts/TVaR分类
数理科学引用本文复制引用
苟中华,张琳,唐亚勇..资产收益率时间序列的条件异方差模型新探[J].四川大学学报（自然科学版）,2011,48(6):1245-1252,8.基金项目
国家自然科学基金数学天元基金(10726019) （10726019）
