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多变量随机波动率模型及在中国股市的应用 被引量：2

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摘要 文章在一维随机波动率(SV)模型基础上,通过扩展,建立了多个多变量随机波动率(MSV)模型。首次将MSV模型大规模应用于中国沪深两市指数周收益率数据,利用MCMC方法进行模型估计,选用DIC准则进行模型比较,得出拟合程度最好的MSV模型。结果显示,加入波动率单边Granger因果关系的MSVGt-AR(1)模型对沪深两市的拟合能力最好。
作者 邵锡栋 黄性芳 殷炼乾
机构地区 西安交通大学金禾经济研究中心 西安交通大学理学院
出处 《统计与决策》 CSSCI 北大核心 2008年第18期82-84,共3页 Statistics & Decision
基金 国家985工程二期项目(07200701)
关键词 多变量随机波动率模型 MCMC DIC
分类号 F224.0 [经济管理—国民经济]
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参考文献11

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同被引文献19

  • 1魏宇,余怒涛.中国股票市场的波动率预测模型及其SPA检验[J].金融研究,2007(07A):138-150. 被引量：43
  • 2Epps T W. Comovements in Stock Prices in the Very Short Run [J].Journal of the American Statistical Association,1979, 74(566).
  • 3Bollerslev, T, R. Y. Chou, K. F. Kroner. ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence[J].Journal of Eeonometrics,1992,52(1).
  • 4Alexander C.O. Orthogonal GARCH[C]. C.O. Alexander, Mastering Risk, Volume 2, Financial Times, U.S.A., Prentice Hall, 2001.
  • 5R F Engle. Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models[J].Journal of Business and Economic Statistics, 2002,22(3).
  • 6RueyS.Tsay,AmlysisofFinancialTimeSeries[M].潘家柱,译.201-228.
  • 7Engle,R.F.Dynamic Conditional Cortdation--A Simple Class of Multivariate GARCH Models[J].Journal of Businessand Econometric Statistics,2002,17.
  • 8Chib,S.,Nardari,F.,and Shephard,N.Analysis of high dimensional multivariate stochastic volatility models[D].Working paper,Washington University,St Louis,1999.
  • 9Chib,S.,Nardari,F.and Shephatd,N.Analysis of HigDimensional Multivariate Stochastic Volatility Models [J].Joumaof Econometrics,2005:134.
  • 10YuJ.and Meyer,R.Multivariate Stochastic Volatility Models:Bayesian Estimation and Models Comparison[l].Econometric Reviews,2006:25.

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统计与决策
2008年 第18期

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