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基于TV-Copula-X模型的金砖国家股指收益率与波动率的动态相依关系

Dynamic dependence of return and volatility between BRICS stock markets based on TV-Copula-X model
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摘要 在动态Copula函数中加入外生变量,构建了TV-Copula-X模型,在定义“波动率惊喜”的基础上,从均值溢出和波动溢出两个角度研究了金砖国家股市间相依结构是否会受到美国股市的影响.选取金砖四国和美国股市的数据进行实证研究,实证结果显示,金砖国家之间在收益率和波动率上均有显著的相依关系.金砖国家波动率之间全部呈现非对称的相依结构,然而仅部分国家收益率之间存在非对称的相依结构.美国股市对部分金砖国家间相依关系产生一定的影响,并且当金融危机发生或者当金砖国家间发生正向积极事件时,金砖国家股市间的相关性都会增强. The TV-Copula-X model was constructed with the addition of an exogenous variable the dynamic Copula function.Based on the definition of‘volatility surprise’,the dependence structures of the BRICS were studied from the perspectives of mean spillover and volatility spillover,and whether the structures would be affected by the US stock market.The data of the BRICS and the US stock markets was selected for empirical research.The results show that the BRICS have significant dependence from the aspects of return and volatility.There are asymmetric dependent structures between the volatility of the BRICS but only some countries of BRICS have asymmetric dependent structures between their yields.The US stock market has a certain impact on the interdependence of some BRICS countries,and the correlation between the BRICS stock markets will increase when a financial crisis or positive events occurs.
作者 叶五一 丁雅霖 焦守坤 YE Wuyi;DING Yalin;JIAO Shoukun(School of Management, University of Science and Technology of China, Hefei 230026, China;International Institute of Finance, University of Science and Technology of China, Hefei 230601,China)
出处 《中国科学技术大学学报》 CAS CSCD 北大核心 2020年第5期612-628,共17页 JUSTC
基金 国家自然科学基金面上项目(71973133,71671171) 国家自然科学基金重点项目(71631006)资助.
关键词 金砖国家 “波动率惊喜” TV-Copula-X模型 均值溢出 波动溢出 BRICS ‘volatility surprise’ the TV-Copula-X model mean spillover volatility spillover
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  • 1何光辉,杨咸月.金砖新兴股票市场国际定位及其溢出效应检验[J].财经研究,2010,36(4):91-102. 被引量:7
  • 2龚锐,陈仲常,杨栋锐.GARCH族模型计算中国股市在险价值(VaR)风险的比较研究与评述[J].数量经济技术经济研究,2005,22(7):67-81. 被引量:99
  • 3李秀敏,史道济.沪深股市相关结构分析研究[J].数理统计与管理,2006,25(6):729-736. 被引量:19
  • 4[1]Nelsen, R. B (1998), An Introduction to Copulas, Lectures Notes in Statistics, 139,Springer Verlag, New York.
  • 5[2]Embrechts, P., Lindskog, F. And McNeil, A. (2001), Modelling Dependence with Copulas and Applications to Risk Management. Dept. of Math. CH-8092, Zürich, Switzerland.
  • 6[3]Bouyé, E. (2000), Copulas for Finance, A Reading Guide and Some Applications. City University Business School,London.
  • 7De la Pe Pefia, Victor, Loran Chollete, and Ching-Chih Lu. Comovement of International Fi-nancial Markets ,Working paper [J].Calumbia Univers- ity, 2004.
  • 8Fortin,Ines,and Christoph Kuzmics. Tail Dependence in Seck-Return Pairs [J].Reihe Oekonomie, 2002,126: 1-35.
  • 9Nelsen, Roger B. An Introduction to Copulas [J].Springer, New York, 1998.
  • 10Hu, L. Dependence patterns across financial markets : a mixed copula app- roach [J].Applied Financial Econonfics,2006,16:717-729.

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