系统管理学报2011，Vol.20Issue(2)：136-142,7.
国际股指波动性的非对称效应异方差模型及聚类分析
Asymmetric and Heteroskedastic Model of Volatility of International Stock Index and its Clustering Analysis
摘要
Abstract
In order to analyze the similarity of volatility of stock indices between China and other counties or areas that have already introduced stock index futures, this paper utilizes traditional time series model a-nalysis and data mining method to perform clustering analysis on stock index volatilities of 23 countries or areas. Firstly, asymmetrical heteroskedastic models are developed for the asymmetric and heteroskedastic properties of stock return time series, and the coefficients are then estimated. Secondly, Euclidean distance is used to justify the degree of similarity of the features extracted from the coefficients series, and hierarchical clustering is performed also. Finally, by empirically examining the similarity of stock index volatilities in each country or area, those countries or areas that are similar to that of China are found. The effectiveness of this method is thus demonstrated.关键词
股票指数/非对称性/波动性/GARCH模型/聚类分析Key words
stock index/ asymmetric/ volatility/ GARCH model/ clustering analysis分类
经济学引用本文复制引用
柴尚蕾,郭崇慧,张震..国际股指波动性的非对称效应异方差模型及聚类分析[J].系统管理学报,2011,20(2):136-142,7.基金项目
国家自然科学基金资助项目(70871015) （70871015）
