摘要
以中国上海证券交易所的金融地产、原材料、工业、可选消费、主要消费、公用事业、能源、电信业务、医药卫生和信息技术十大行业指数为研究对象,运用能够同时考察多市场相关关系的Vine Copula方法,对这十大行业指数间的净相关关系进行实证分析。主要结果表明:中国上证行业指数之间具有显著的非对称和厚尾相关特征;非条件下两个行业指数之间以及条件下一些3个或者4个行业指数之间有较强的相关性;而5个或5个以上行业指数之间的条件相关性表现出相互独立,因而在熊市时选择5个及以上不同行业同时投资,能够达到有效分散风险的目的;与D_Vine Copula及C_Vine Copula模型相比,R_Vine Copula模型更适合于刻画中国行业指数之间的相关关系。
It is of great significance for portfolio decision-making and investment risk reduction to study the correlation among the different industries of listed companies in Shanghai Stock Exchange. Vine Copula method, which is capable of viewing the correlation among multi-markets, was used to measuring the net relationship between the different industries, with the daily return of all ten indexes of Financial & Real Estate, Raw Materials, Industry, Optional Consumption, Main Consumption, Public Utilities, Energy,Telecommunication, Medicine & Health Care and Information Technology as sample. The main empirical results show that: there is significant asymmetric and fat tail correlation characteristic between the different industry indexes; there is a strong correlation between every two industry indexes under non-conditions and among some three or four industry indexes while taking all the industry indexes into account; As is shown, the conditional correlation among five or more than five indexes is mutually independent, so investment in five or more than five industries could meet the goal of avoiding the risk. R_Vine Copula model is more suitable for measuring the net correlation of industry indexes in the Shanghai Stock Exchange compared with the D_Vine and C_Vine Copula model.
出处
《北京理工大学学报（社会科学版）》
CSSCI
2015年第3期100-108,共9页
Journal of Beijing Institute of Technology：Social Sciences Edition
基金
国家自然科学基金(71371157
71071131
71090402)
教育部创新团队发展计划(PCSIRT0860)
中央高校基本科研业务费专项资金资助项目(SWJTU11ZT30
SWJTU11CX137)
