期刊文献+

基于ICA-SV模型的金融市场协同波动溢出分析及实证研究 被引量:8

Common Volatility Spiilover Analysis and Empirical Study on the Financial Market Base on SV Model
原文传递
导出
摘要 对于动态投资组合与风险管理来说,测定波动溢出效应是非常重要的.已有的文献证明SV模型比GARCH模型能够更好地刻画金融市场的波动,使用SV模型研究两个金融市场间波动溢出的文献并不多见,而使用SV模型研究多个金融市场对一个金融市场协同波动溢出的文献则更为少见.本文以独立成分表示金融市场波动的协同指标,提出了独立成分SV模型(ICA-SV),并研究了多个金融市场对一个金融市场的协同波动溢出,实证结果验证了ICA-SV模型在分析金融市场协同波动溢出是可行的. It is very important to mensurate the volatility spillover for the dynamic investment portfolio and risk management. The known literature have showed that describing the volatility of financial market with SV model is better than GARCH models. There are few literatures to study volatility spillover of the financial market with SV model, and even fewer literatures to study common volatility spillover from the Multi-financial Markets to a single financial market with SV model. By using Principal Components, we indicate the common index of volatility of muhi-financial markets. The thesis proposes Independent Components Analysis SV model (ICA-SV), and studies the common volatility spillover of the multi-financial markets to single financial market, the empirical results show that ICA-SV model in the analysis of common volatility spillover of financial market is feasible.
出处 《数学的实践与认识》 CSCD 北大核心 2008年第23期30-39,共10页 Mathematics in Practice and Theory
基金 国家自然科学基金资助项目(70471050) 教育部人文社会科学研究课题(07JC790046) 河北省教育厅科学研究计划项目(2008203) 福建省自然科学基金资助项目(2008J0192)
关键词 SV模型 独立成分分析(ICA) 金融市场 协同波动溢出 SV model independent components analysis (ICA) financial markets common volatility spillover
  • 相关文献

参考文献23

  • 1Taylor S J. Modeling Financial Time Series[M]. Chichester: John Wiley and Sons. 1986.
  • 2Taylor S J. Modeling stochastic volatility[J]. Mathematical Finance, 1994,4 : 183-204.
  • 3Shepard N. Statistical aspects of ARCH and stochastic volatility[J]. Time Series Model in Econometrics, 1996.1- 67.
  • 4Jacquier Eric, Nicholas G Poison, Rossi P E. Bayesian analysis of stochastic volatility models[J]. Journal of Business & Economic Statistics, 1994,12( 4 ) : 371-388.
  • 5李汉东,张世英.ARCH模型与SV模型之间的关系研究[J].系统工程学报,2003,18(2):97-103. 被引量:8
  • 6余素红,张世英.SV与GARCH模型对金融时间序列刻画能力的比较研究[J].系统工程,2002,20(5):28-33. 被引量:38
  • 7余素红,张世英,宋军.基于GARCH模型和SV模型的VaR比较[J].管理科学学报,2004,7(5):61-66. 被引量:76
  • 8Harvey A, Ruiz E, Shephard. Multivariate stochastic variance models[J]. Review of Economic Studies, 1994,61 : 247-264.
  • 9Harvey Andrew C. Neil Shephard. Estimation of an asymmetic stochastic volatility model for asset returns[J]. Journal of Business & Economic Statistica, 1996,14 : 429-434.
  • 10Harvey Andrew, Mariane Streibel. Testing for a slowly changing level with special reference to stochastic votatility[J]. Journal of Eeonometries,1998,87:167-189.

二级参考文献68

  • 1汪素南,潘云鹤.美国股市与中国股市间溢出效应的实证研究[J].浙江大学学报(工学版),2004,38(11):1431-1435. 被引量:30
  • 2胡素华,张世英,张彤.金融工程中资产收益的连续时间模型评述[J].中国管理科学,2006,14(2):24-32. 被引量:10
  • 3李汉东.多变量时间序列波动持续性研究[M].天津:天津大学,2000..
  • 4[1]Jonathan H. Wright. A new estimator of the fractionally integrated stochastic volatility model[J]. Economics letters, 1999, 63: 295~303.
  • 5[2]Taylor, S. J. Modelling stochastic volatility[J]. Mathematical Finance, 1994, 4: 183~204.
  • 6[3]Shepard, N. Statistical aspects of ARCH and stochastic volatility [J]. Time Series Models in Econometrics, 1996, 1~67.
  • 7[4]Mandelbrot, B. B. The Variation of Certain Speculative Prices[J]. Journal of Business. 1963, 36: 394~416.
  • 8[5]Fama, E. F. Mandelbrot and The Stable Paretain Distribution[J]. Journal of Business, 1963, 36: 420~429.
  • 9[6]Terāsvirta, T. Two stylized facts and the GARCH (1,1) model[J]. Stockholm School of Economics, Working paper. 1996, No.96.
  • 10[7]Bollerslev, T. A conditionally heteroskedastic time series model for speculative prices and rates of return[J]. The Review of Economics and St6atistics,1987, 59: 542~547.

共引文献162

同被引文献134

二级引证文献52

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