上海管理科学2012，Vol.34Issue(4)：68-75,8.
GARCH模型族在沪深300中的比较研究
A Comparative Study on the GARCH Models in CSI 300
摘要
Abstract
Risk measurement has always been a hot topic in the realm of financial research, and how to build an appropriate model to assess the risk has become the focus of many scholars' research. VaR(Value at Risk) is one of the most widely used methods to measure financial risk nowadays, whose core is to build a good volatility estimation model. GARCH Models are considered good conditional heteroscedasticity models at the moment given its well capability of describing heavy tails, volatility clustering and leverage effects of the index' s volatility. This paper delves into the fitting results of GARCH Models (GARCH, EGARCH and PGARCH) under different distribution assumptions (Gaussian distribution, t distribution and generalized error distribution), and hence calculates the VaR of CSI 300, compares and analyzes the fitting performance among the models and picks the most appropriate model as the theoretical basis for standardizing risk management in CSI 300.关键词
沪深300指数/GARCH模型族/VaR计算Key words
CSI 300/ GARCH Models/ VaR calculation分类
管理科学引用本文复制引用
赖艳丽..GARCH模型族在沪深300中的比较研究[J].上海管理科学,2012,34(4):68-75,8.
