期刊文献+

基于Pair-Copula构造的多元相依结构模型分析 被引量:2

下载PDF
导出
摘要 Copula函数作为一种新型相关性分析工具,近年来在金融领域得到了广泛的应用。文章在分析了基于Pair-Copula构造多元藤结构Copula模型的基础之上,实证分析了大陆上证指数和深证成指以及香港恒生指数三个市场间的相依结构特征,对各个市场指数收益率的边际分布我们采用GARCH(1,1)-t模型进行拟合,而对各Pair-Copula的模型选择采用t-Copula,分析结果表明基于PCC的藤结构模型相对于传统的t多元t-Copula模型在捕捉变量间相依结构时表现更优的效果。
出处 《统计与决策》 CSSCI 北大核心 2014年第19期24-27,共4页 Statistics & Decision
基金 国家自然科学基金青年项目(71101030) 四川省教育厅自然科学基金项目(13ZB0102)
  • 相关文献

参考文献13

  • 1Aas K., Czado C., Frigessi A. Bakken H. Pair-copula Constructions of Multiple Dependence [J]. Insurance: Mathematics and Economics, 2009,(44).
  • 2Bedford, T.Cooke, R.M. Vines-A New Graphical Model for Depen- dent Random Variables [J]. Annals of Statistics, 2002,(30).
  • 3Bollerslev, T. Generalized Autoregressive Conditional Heteroskedas- ticity [J]. Journal of Econometrics, 1986,(31).
  • 4Chen, X., Fan, Y.. Estimation and Model Selection of Semi-paramet- ric Copula-based Multivariate Dynamic Models under Copula Mis- specification [J]. Journal of Econometrics, 2006,(135).
  • 5DiBmann J., Brechmann E.C., Czado C., Kurowicka D. Selecting and Estimating Regular Vine Copulae and Application to Financial Re- turns [J].Computational Statistics & Data Analysis, 2013,(3).
  • 6Engle, R. F. Autoregressive Conditional Heteroskedasticity with Esti- mates of the Variance of United Kingdom Inflation [J].Econometrica, 1982,(50).
  • 7Engle R. F.Dynamic Conditional Correlation- A Simple Class of Mul- tivariate GARCH Models [J]. Journal of Business and Economic Statis- tics, 2002, (20).
  • 8Fischer M.F.,Kock C.,Schlter S. F. W.Multivariate Copula Models at Work [J]. Quantitative Finance, 2009 ,(7).
  • 9Kurowiek D., Cooke R. M. Uncertainty Analysis with High Dimension- al Dependence Modelling[M].New York:John Wiley & Sons, 2006.
  • 10Ljung, T., Box, G.E.P. The Likelihood Function for a Stationary Au- toregressive Moving Average Process [J]. Biometrika, 1979,(66).

二级参考文献23

共引文献37

同被引文献19

  • 1IPCC. Managingthe risks of extreme eventsand disasters to advance climate change adaptation: Special report of the intergovemmental panelon climate change [ M1. Cambridge, UK, NewYork, NY, USA: Cambridge University Press, 2012.
  • 2LiN, I~iu X, Xie W, et al. The return period analysis of natural disasters with statistical modeling of bivariate joint probability dis- tribution[ J]. Risk Analysis, 2013, 33 ( 1 ) : 134 - 145.
  • 3BEDFORD T, COOKE R M. Probability density decomposition for conditionally dependent random variables modeled by vine [J]. Annals of Mathematics and Artificial Intelligence, 2001, 32 : 245 - 268.
  • 4HEINEN A, VALDESOGO A. Asymmetric CAPM dependence for large dimensions: The canonical vine autoreg'essive model [ R]. New York: SSRN, 2009 : 1297506.
  • 5JOE H. Family of m - variate distributions with given margins and m( m - 1 )/2 bivariate dependence parameters [ J]. Lecture Notes - Monograph Series, 1996, 28 : 120 - 141.
  • 6PICKANDS J. Statistical Inference Using Extreme Order Statis- tics [J]. Annals of Statistics, 1975, 3(1 ) : 119 - 131.
  • 7PATTON A J. Estimation of Multivariate Models for Times Series of Possibly Different lengths [ J ]. Journal of Applied Economet- rics, 2006, 21 : 147 - 173.
  • 8MCNEIL A J, FREY R. Estimation of Tail - Related Risk Meas- ures for Heteroscedastic Financial Time Series: An Extreme Val- ue Approach [ J]. Journal of Empirical Finance, 2000, 7 (3) : 271 - 300.
  • 9周玉良,袁潇晨,金菊良,郦建强,宋松柏.基于Copula的区域水文干旱频率分析[J].地理科学,2011,31(11):1383-1388. 被引量:55
  • 10陈子燊,曹深西.基于Copula函数的波高与周期长期联合分布[J].海洋通报,2012,31(6):630-635. 被引量:11

引证文献2

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部