引入持仓量的沪铜指数长记忆波动性研究  

Based on Long Memory Research of Copper Index Fluctuation with Introducing Positions

作　　者：杨桂元[1] 刘坤[1] 

机构地区：[1]安徽财经大学数量经济研究所,安徽蚌埠233030

出　　处：《统计与信息论坛》2010年第8期88-94,共7页Journal of Statistics and Information

基　　金：教育部人文社会科学研究项目<基于风险约束的委托资产组合管理PBF合同研究>(08JA630003)

摘　　要：通过协整关系检验、误差修正模型、向量自回归模型、格兰杰因果关系检验、脉冲响应函数证明了在建立模型时引入持仓量序列的必要性。运用修正R/S分析,建立了沪铜指数收益率波动的ARFIMA、FI-GARCH、ARFIMA-FIGARCH模型,并运用此种模型对沪铜指数的收益率序列rt、收益率波动序列|rt|及残差序列|εt|进行相关研究和分析,结果表明:ARFIMA(0,d1,0)-FIGARCH(1,d2,1)模型的预测效果比较好。This paper introduces Cointegration test、Modified model for error、Vector autoregression、 Granger causality test、Impulse response function,and proves the necessity in the process of establishment for models with the sequence of positions.Using of modified R/S methods,we have built up the ARFIMA models、FIGARCH models、ARFIMA-FIGARCH models for the fluctuation of copper index earnings,and have given the analysis of the sequence of earnings rt、the sequence of fluctuation for earnings｜rt｜、the sequence of residual｜εt｜.Futhermore,we can make more precise forecast with the models ARFIMA（0,d1,0）-FIGARCH（1,d2,1）.

关 键 词：期货 长记忆 ARFIMA模型 FIGARCH模型 ARFIMA-FIGARCH模型 

分 类 号：F224.0[经济管理—国民经济]