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dc.contributor.author王娜
dc.contributor.author钱争鸣
dc.date.accessioned2018-11-26T07:38:46Z
dc.date.available2018-11-26T07:38:46Z
dc.date.issued2016-09-10
dc.identifier.citation统计与信息论坛,2016,31(09):10-17
dc.identifier.issn1007-3116
dc.identifier.otherTJLT201609002
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/163635
dc.description.abstract考虑到在进行指数跟踪时影响强度大并且流动性好的成份股往往是被偏好的,结合股票市场的网络结构和指数的编制规则,提出基于偏好变量的指数跟踪方法;对沪深300指数进行实证分析,从跟踪偏离度、平均超额收益和年跟踪误差三方面对新方法进行评估,并与非负LASSO模型进行对比分析。实证结果显示,新方法不仅优于非负LASSO模型,而且优于市场上大多数指数基金。
dc.description.abstractThis paper proposes the prefered-variable-based index tracking after considering the network structure of stock market and index methodology which tell us the stock with great infulence-strength and good liquidity should be prefered.Then we applied this method in tracking CSI 300 stock index and evaluated new method from tracking difference,average excess return and annual tracking error,and compared it with nonnegative-LASSO.The empirical results show that this method performs better than nonnegative-LASSO and most of index funds in the market.
dc.description.sponsorship教育部重点研究基地重大项目《开放经济条件下资源环境约束强化、技术进步与中国经济增长效率》(12JJD790027)
dc.language.isozh_CN
dc.subject无标度网络
dc.subject影响强度
dc.subject流动性
dc.subject指数跟踪
dc.subjectscale-free network
dc.subjectinfluence-strength
dc.subjectliquidity
dc.subjectindex tracking
dc.title基于偏好变量的指数跟踪方法
dc.title.alternativePrefered-variable-based Index Tracking
dc.typeArticle


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