基于变结构Copula函数的上证综指波动溢出效应研究
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摘要
波动溢出效应是指一个金融市场的波动不仅受到本身历史波动程度的影响,而且还可能会受到其他市场波动程度的制约。金融危机的发生,破坏了市场之间的相关关系,并使市场之间的相关性显著增强,即可认为市场之间存在波动溢出效应。金融波动和危机的频繁发生,使风险管理和多变量金融时间序列分析成为国内外关注的焦点,但基于线性理论的新古典经济学在解释一些新的经济现象时,往往显得不是很有效,原有的多变量金融模型已不能完全满足发展的需要。因此Copula函数在金融领域的应用为波动溢出效应的分析研究提供了一个有效的工具。
基于此,本文首先对各股市收益率序列进行边缘分布的估计,然后分别从静态和动态角度对各股指与上证综指的相关关系进行分析,并运用Bayes时序诊断法和Z检验方法诊断出各序列的变结构点,最后通过构建分阶段Copula函数和相关参数的Z检验来判断各股市对上海股市是否存在波动溢出效应。研究结果表明,各股指与上证综指的相关关系具有地域性,深圳成指与上证综指的相关性最强,但各股指波动趋势总体上看是一致的,另外,在2008年次贷危机发生并对世界各国产生广泛影响期间,各国股市对上海股票市场都有较强的波动溢出效应,并且这种效应非常显著。这表明,在金融危机发生时,世界各主要股票市场的股指对上证综指存在显著的波动溢出效应。
Volatility spillover effect means that the volatility of a financial market is influenced not only by the historical volatility of its own, but also by the volatility of other markets. When the financial crisis occur, the relationship between markets is destroyed, the correlation between markets increased significantly, and we can think that there is the volatility spillover effect between markets. Financial volatility and frequent crises make risk management and multivariate financial time series analysis to be the focus of attention at home and abroad. But the neo-classical economics based on the linear theory often seems not very effective when explains the new economic phenomenon, and the original multi-variable financial model can not fully meet the financial needs of the development. Therefore the application of Copula function in the financial sector provides an effective tool for the analysis of volatility spillovers.
Based on this, we first estimated the marginal distribution of the the stock market return rate sequence, and then analyzed the correlation between other stock markets and the Shanghai stock market separately from the static and dynamic perspectives, and diagnosed the variable structure points by the application of Bayes sequential diagnosis method and Z method, and finally determined whether volatility spillover effect of the others stock markets on the Shanghai stock market exist through building phased Copula functions and the Z test of relevant parameters. The results show that the correlation between the indexes and the Shanghai Composite Index is regional, and the relationship between Shenzhen Component Index and Shanghai Composite Index are the strongest, but the whole trend of the indexes volatility is the same, and the other, when subprime motagage crisis occurred and produced the worldwide impact in the 2008, States stock markets all had strong volatility spillover effects on the Shanghai stock market, and this effect is very significant. This indicates that the world's major stock market indexes have significant volatility spillover effects on the Shanghai Composite Index when the financial crisis occur.
基于此,本文首先对各股市收益率序列进行边缘分布的估计,然后分别从静态和动态角度对各股指与上证综指的相关关系进行分析,并运用Bayes时序诊断法和Z检验方法诊断出各序列的变结构点,最后通过构建分阶段Copula函数和相关参数的Z检验来判断各股市对上海股市是否存在波动溢出效应。研究结果表明,各股指与上证综指的相关关系具有地域性,深圳成指与上证综指的相关性最强,但各股指波动趋势总体上看是一致的,另外,在2008年次贷危机发生并对世界各国产生广泛影响期间,各国股市对上海股票市场都有较强的波动溢出效应,并且这种效应非常显著。这表明,在金融危机发生时,世界各主要股票市场的股指对上证综指存在显著的波动溢出效应。
Volatility spillover effect means that the volatility of a financial market is influenced not only by the historical volatility of its own, but also by the volatility of other markets. When the financial crisis occur, the relationship between markets is destroyed, the correlation between markets increased significantly, and we can think that there is the volatility spillover effect between markets. Financial volatility and frequent crises make risk management and multivariate financial time series analysis to be the focus of attention at home and abroad. But the neo-classical economics based on the linear theory often seems not very effective when explains the new economic phenomenon, and the original multi-variable financial model can not fully meet the financial needs of the development. Therefore the application of Copula function in the financial sector provides an effective tool for the analysis of volatility spillovers.
Based on this, we first estimated the marginal distribution of the the stock market return rate sequence, and then analyzed the correlation between other stock markets and the Shanghai stock market separately from the static and dynamic perspectives, and diagnosed the variable structure points by the application of Bayes sequential diagnosis method and Z method, and finally determined whether volatility spillover effect of the others stock markets on the Shanghai stock market exist through building phased Copula functions and the Z test of relevant parameters. The results show that the correlation between the indexes and the Shanghai Composite Index is regional, and the relationship between Shenzhen Component Index and Shanghai Composite Index are the strongest, but the whole trend of the indexes volatility is the same, and the other, when subprime motagage crisis occurred and produced the worldwide impact in the 2008, States stock markets all had strong volatility spillover effects on the Shanghai stock market, and this effect is very significant. This indicates that the world's major stock market indexes have significant volatility spillover effects on the Shanghai Composite Index when the financial crisis occur.
引文
[1]King, Mervyn and Sushil Wadhwani. Transmission of volatility between stock markets[J]. Review of Financial Studies,1990,3,5-33) (King, Mervyn, Enrique Sentana and Sushil Wadhwani. Volatillity and links between national stock markets[J]. Econometrica,1994,62,901-933.
[2]Chan, K.C., G. Andrew Karolyi, and Rene M. Stulz. Global financial market and the tisk premium on US equity[J]. Journal of Financial Economics,1992, (32):137-167.
[3]Forbes, Kristin J. and Roberto Rigobon. No Contagion, Only Interdependence:Measuring Stock Market Comoverments[J]. Journal of Finance,2002,57:2223-2261.
[4]Corsetti, Giancarlo, Marcello Pericoli, and Massimo Sbracia. Some Contagion, Some Interdependence. More Pitfalls in Tests of Financial Contagion[J]. Yale Manuscrip, European University Institute,2003, working paper.
[5]Bekaert, Geert, Campbell R. Harvey and Angela Ng, Market Intergration and Contagion[J]. Journal of Business,2005,78:39-69.
[6]Pesaran, M. Hashem and Andreas Pick, Econometric Issues in the Analysis of Contagion[J]. mimeo, University of Cambridge,2003.
[7]HAHN S L. International transmission of stock market movements:A wavelet analysis on MENA stock markets[A]. ERF's Eighth Annual Conference[C]. Cairo:[s.n.],2002.
[8]EUN C, SHIM S. International transmission of stock market movements[J]. Journal of Financial and Quantitative Analysis,1989,24(2):241-256.
[9]Hamao, Y., Masulis, R.W.& Ng, V. Correlations in price changes and volatility across international stock markets[J]. Reviews of Financial Studies,1990, (3):281-307.
[10]Engle, Robert F., Takatoshi Ito, and Wen-Ling Lin,1990, Meteor Showers or HeatWawes? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market, Econometrica 58,525-542.
[11]Lin, W., Engle, R.F.& Ito, T. Do bulls and bears move across borders? International transmission of stock returns and volatility[J]. Review of Financial Studies,1994, (7):507-538.
[12]Sang-Moon Hahm. Transmission of stock and volatility:the case of Korea[J]. Working paper, 2003.
[13]Gerard L Gannon. Simultaneous volatility transmisson and spillover effects[J]. Workiong paper, 2004.
[14]Ling, S. and M. McAleer. Asymptotic Theory for a Vector ARMA-GARCH Model[J]. Econometric Theory,2003,19,278-308.
[15]Harvey A. and E. Ruiz and Shephard. Multivariate stochastic variance models[J]. Reciew of Economic Studies,1994, (61):247-264.
[16]So Mike K. P., W. K. Lam. Multivariate modeling of the autoregressive random bariance process[J]. Journal of Time Series Analysis.1997,18,:429-446.
[17]Eichengreen, Barry J., Andrew K. Rose, and Charles A. Wyplosz. Contagious currency crises[J]. Scandinavian Journal of Economics,1996, (98):463-484.
[18]DeGregorio, J., and R. Valdes. Crisis transmissions:Evidence from the debt, Tequila and Asian flu crises[J]. Universidad de Chile working paper,2000.
[19]Glick, R., and A. K. Rose. Contagion and trade[J]. Journal of International Money & Finance, 1999,18,603-617.
[20]Kaminsky, G. L., and C. Reinhart. On crises, contagion and confusion[J]. Journal of International Economics,2000,51,145-168.
[21]Bae, Kee-Hong, G. Andrew Karolyi, and Rene M. Stulz. A new approach to measuring financial Contagion[J]. Review of Financial Studies,2003, (16):717-763.
[22]Longin, Francois and Bruno Solnik, Is the correlation in international equity returns constant: 1970-1990[J]. Journal of International Money and Finance,1995,14,3-26.///Longin, Francois and Bruno Solnik. Extrenme Correlation of international equity markets[J]. Journal of Finance,2001,56, 649-76.
[23]Hartmann, P., S. Straetmans and C. G. De Vries. Asset Market Linkages in Crisis Periods[J]. ECB Working paper,2001,71.
[24]Nelsen R B. An Introduction to Copulas [M], New York:Springer-Volga,1999.
[25]Rockinger M, Jondeau E. Conditional dependency of financial series:an application of copulas. Working Paper of Department of Finance, HEC School of Management, Paris,2001.
[26]Thierry Ane, Chiraz Labidi. Spillover and conditional dependence[J]. International Review of Economics and Finances 2006,15:417-442.
[27]Eric Jondeau, Michael Rockinger. The Copula-GARCH model of conditional dependencies:An international stock market application[J]. Journal of International Money and Finance 2006, 25:827-853.
[28]Sohnke M. Bartram etc. The Euro and European financial market dependence[J]. Journal of Banking & Finance,2007.
[29]Lamoureux C G, Lastrapes W D. Persistence in variance, structural change, and the GARCH model[J]. Journal of Business & Economic Statistic,1990,8:225-234.
[30]Hamilton J D. A new approach to the economic analysis of nonstationary time series and the business cycle[J]. Econometrica,1989(57):358-384.
[31]Patton A J. Modeling time-varying exchange rate dependence using the conditional copula[Z]. Department of Economics, University of California, San Diego,2001.
[32]刘金全,崔畅.中国沪深股市收益率和波动性的实证分析.经济学(季刊),2002,1(4)：885-898.
[33]赵留彦,王一鸣.A、B股之间的信息流动与波动溢出.金融研究,2003，(10)：37-52.
[34]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.
[35]洪永淼,成思危等,中国股市与世界其他股市之间的大风险溢出效应[J].经济学.2004,3(3)：703-726.
[36]张碧琼.中国股票市场信息国际化：基于EGARCH模型的检验.国际金融研究,2005,(5)：68-73.
[37]张瑞峰.金融市场协同波动溢出分析及实证研究[J].数量经济技术经济研究,2006,23(10)：141-149.
[38]张瑞峰,张世英.金融市场波动溢出分析及实证研究[J].中国管理科学.2006，14(5)：14-22.
[39]谷耀,陆丽娜.沪、深、港股市信息溢出效应与动态相关性——基于DCC-(BV) EGARCH-VAR的检验.数量经济技术经济研究,2006.,(8)：142-151.
[40]张瑞峰,张世英.基于VS-MSV模型的金融市场波动溢出分析及实证研究[J].系统工程.2007，25(8)：1-6.
[41]万军,谢敏,熊正德.金融市场间波动溢出效应研究[J].统计与决策(理论版),2007,(18)：98-101.
[42]张瑞峰,张世英.基于ICA-SV模型的金融市场协同波动溢出分析及实证研究[J].数学的实践与认识.2008，38(23)：30-39.
[43]李勇,李传乐.风险传染效应在牛市、熊市中的异化现象——来自A+H双重上市公司的证据.金融发展研究,2008,(11)：62-65.
[44]胡新明,唐齐鸣.B股与H股及红筹股之间的溢出效应与信息流动[J].管理工程学报,2008，(4)：159-162.
[45]张信东,赵芳.沪、深股票市场与香港股票市场的溢出效应——基于发布“港股直通车”方案前后的比较分析[J].南开管理评论,2009,12(4)：99-106.
[46]张尧庭.我们应该选用什么样的相关性指标?[J].统计研究,2002，(9)：41-44.
[47]韦艳华,张世英.金融市场的相关性分析——Copula-GARCH模型及其应用[J].系统工程,2004,22(4)：7-12.
[48]尚英锋,王爱莉.相关风险和的分布边界[J].天津理工大学学报,2005,21(3)：46-48.
[49]曾健,陈俊芳.Copula函数在风险管理中的应用研究——以上证A股与B股的相关结构分析为例[J].当代财经,2005,(02)：35-39.
[50]罗俊鹏,史道济,徐付霞.SHFE和LME期铜相关模式的研究[J].西北农林科技大学学报(社会科学版),2006,(05)：75-80.
[51]吴振翔,陈敏，叶五一,缪柏其.基于Copula-GARCH的投资组合风险分析[J].系统工程理论与实践,2006，(03)：47-54.
[52]孙志宾.混合Copula模型在中国股市的应用[J].数学的实践与认识,2007,(20)：16-20.
[53]霍光耀,郭名媛.金融波动研究的新进展及未来展望[J].西北农林科技大学学报(社会科学版),2007,7(5)：49-55.
[54]韦艳华,张世英.金融市场非对称尾部相关结构的研究[J].管理学报,2005,2(5)：601-605.
[55]韦艳华,张世英.金融市场动态相关结构的研究[J].系统工程学报,2006,21(3)：313-317.
[56]杨绮霞.内地与香港股市金融板块的联动性研究[学位论文].北京：对外经贸大学,2007.
[57]Tversky, A. and Kahneman D. Advances in Prospect Theory:Cumulative Representation of Uncertainty. Joural of Risk and Uncertainty,1992,5:297-323.
[58]Nelsen R B. An Introduction to Copulas[M]. New York:Springer,2006.
[59]韦艳华,张世英.Copula理论及其在金融分析上的应用[M].北京：清华大学出版社,2008,1-2页.
[60]Engle R F. Autoregressive heteroskedasticity with estimation of the variance of U. K. inflation [J]. Econometrica,1982,50:987-1008.
[2]Chan, K.C., G. Andrew Karolyi, and Rene M. Stulz. Global financial market and the tisk premium on US equity[J]. Journal of Financial Economics,1992, (32):137-167.
[3]Forbes, Kristin J. and Roberto Rigobon. No Contagion, Only Interdependence:Measuring Stock Market Comoverments[J]. Journal of Finance,2002,57:2223-2261.
[4]Corsetti, Giancarlo, Marcello Pericoli, and Massimo Sbracia. Some Contagion, Some Interdependence. More Pitfalls in Tests of Financial Contagion[J]. Yale Manuscrip, European University Institute,2003, working paper.
[5]Bekaert, Geert, Campbell R. Harvey and Angela Ng, Market Intergration and Contagion[J]. Journal of Business,2005,78:39-69.
[6]Pesaran, M. Hashem and Andreas Pick, Econometric Issues in the Analysis of Contagion[J]. mimeo, University of Cambridge,2003.
[7]HAHN S L. International transmission of stock market movements:A wavelet analysis on MENA stock markets[A]. ERF's Eighth Annual Conference[C]. Cairo:[s.n.],2002.
[8]EUN C, SHIM S. International transmission of stock market movements[J]. Journal of Financial and Quantitative Analysis,1989,24(2):241-256.
[9]Hamao, Y., Masulis, R.W.& Ng, V. Correlations in price changes and volatility across international stock markets[J]. Reviews of Financial Studies,1990, (3):281-307.
[10]Engle, Robert F., Takatoshi Ito, and Wen-Ling Lin,1990, Meteor Showers or HeatWawes? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market, Econometrica 58,525-542.
[11]Lin, W., Engle, R.F.& Ito, T. Do bulls and bears move across borders? International transmission of stock returns and volatility[J]. Review of Financial Studies,1994, (7):507-538.
[12]Sang-Moon Hahm. Transmission of stock and volatility:the case of Korea[J]. Working paper, 2003.
[13]Gerard L Gannon. Simultaneous volatility transmisson and spillover effects[J]. Workiong paper, 2004.
[14]Ling, S. and M. McAleer. Asymptotic Theory for a Vector ARMA-GARCH Model[J]. Econometric Theory,2003,19,278-308.
[15]Harvey A. and E. Ruiz and Shephard. Multivariate stochastic variance models[J]. Reciew of Economic Studies,1994, (61):247-264.
[16]So Mike K. P., W. K. Lam. Multivariate modeling of the autoregressive random bariance process[J]. Journal of Time Series Analysis.1997,18,:429-446.
[17]Eichengreen, Barry J., Andrew K. Rose, and Charles A. Wyplosz. Contagious currency crises[J]. Scandinavian Journal of Economics,1996, (98):463-484.
[18]DeGregorio, J., and R. Valdes. Crisis transmissions:Evidence from the debt, Tequila and Asian flu crises[J]. Universidad de Chile working paper,2000.
[19]Glick, R., and A. K. Rose. Contagion and trade[J]. Journal of International Money & Finance, 1999,18,603-617.
[20]Kaminsky, G. L., and C. Reinhart. On crises, contagion and confusion[J]. Journal of International Economics,2000,51,145-168.
[21]Bae, Kee-Hong, G. Andrew Karolyi, and Rene M. Stulz. A new approach to measuring financial Contagion[J]. Review of Financial Studies,2003, (16):717-763.
[22]Longin, Francois and Bruno Solnik, Is the correlation in international equity returns constant: 1970-1990[J]. Journal of International Money and Finance,1995,14,3-26.///Longin, Francois and Bruno Solnik. Extrenme Correlation of international equity markets[J]. Journal of Finance,2001,56, 649-76.
[23]Hartmann, P., S. Straetmans and C. G. De Vries. Asset Market Linkages in Crisis Periods[J]. ECB Working paper,2001,71.
[24]Nelsen R B. An Introduction to Copulas [M], New York:Springer-Volga,1999.
[25]Rockinger M, Jondeau E. Conditional dependency of financial series:an application of copulas. Working Paper of Department of Finance, HEC School of Management, Paris,2001.
[26]Thierry Ane, Chiraz Labidi. Spillover and conditional dependence[J]. International Review of Economics and Finances 2006,15:417-442.
[27]Eric Jondeau, Michael Rockinger. The Copula-GARCH model of conditional dependencies:An international stock market application[J]. Journal of International Money and Finance 2006, 25:827-853.
[28]Sohnke M. Bartram etc. The Euro and European financial market dependence[J]. Journal of Banking & Finance,2007.
[29]Lamoureux C G, Lastrapes W D. Persistence in variance, structural change, and the GARCH model[J]. Journal of Business & Economic Statistic,1990,8:225-234.
[30]Hamilton J D. A new approach to the economic analysis of nonstationary time series and the business cycle[J]. Econometrica,1989(57):358-384.
[31]Patton A J. Modeling time-varying exchange rate dependence using the conditional copula[Z]. Department of Economics, University of California, San Diego,2001.
[32]刘金全,崔畅.中国沪深股市收益率和波动性的实证分析.经济学(季刊),2002,1(4)：885-898.
[33]赵留彦,王一鸣.A、B股之间的信息流动与波动溢出.金融研究,2003，(10)：37-52.
[34]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.
[35]洪永淼,成思危等,中国股市与世界其他股市之间的大风险溢出效应[J].经济学.2004,3(3)：703-726.
[36]张碧琼.中国股票市场信息国际化：基于EGARCH模型的检验.国际金融研究,2005,(5)：68-73.
[37]张瑞峰.金融市场协同波动溢出分析及实证研究[J].数量经济技术经济研究,2006,23(10)：141-149.
[38]张瑞峰,张世英.金融市场波动溢出分析及实证研究[J].中国管理科学.2006，14(5)：14-22.
[39]谷耀,陆丽娜.沪、深、港股市信息溢出效应与动态相关性——基于DCC-(BV) EGARCH-VAR的检验.数量经济技术经济研究,2006.,(8)：142-151.
[40]张瑞峰,张世英.基于VS-MSV模型的金融市场波动溢出分析及实证研究[J].系统工程.2007，25(8)：1-6.
[41]万军,谢敏,熊正德.金融市场间波动溢出效应研究[J].统计与决策(理论版),2007,(18)：98-101.
[42]张瑞峰,张世英.基于ICA-SV模型的金融市场协同波动溢出分析及实证研究[J].数学的实践与认识.2008，38(23)：30-39.
[43]李勇,李传乐.风险传染效应在牛市、熊市中的异化现象——来自A+H双重上市公司的证据.金融发展研究,2008,(11)：62-65.
[44]胡新明,唐齐鸣.B股与H股及红筹股之间的溢出效应与信息流动[J].管理工程学报,2008，(4)：159-162.
[45]张信东,赵芳.沪、深股票市场与香港股票市场的溢出效应——基于发布“港股直通车”方案前后的比较分析[J].南开管理评论,2009,12(4)：99-106.
[46]张尧庭.我们应该选用什么样的相关性指标?[J].统计研究,2002，(9)：41-44.
[47]韦艳华,张世英.金融市场的相关性分析——Copula-GARCH模型及其应用[J].系统工程,2004,22(4)：7-12.
[48]尚英锋,王爱莉.相关风险和的分布边界[J].天津理工大学学报,2005,21(3)：46-48.
[49]曾健,陈俊芳.Copula函数在风险管理中的应用研究——以上证A股与B股的相关结构分析为例[J].当代财经,2005,(02)：35-39.
[50]罗俊鹏,史道济,徐付霞.SHFE和LME期铜相关模式的研究[J].西北农林科技大学学报(社会科学版),2006,(05)：75-80.
[51]吴振翔,陈敏，叶五一,缪柏其.基于Copula-GARCH的投资组合风险分析[J].系统工程理论与实践,2006，(03)：47-54.
[52]孙志宾.混合Copula模型在中国股市的应用[J].数学的实践与认识,2007,(20)：16-20.
[53]霍光耀,郭名媛.金融波动研究的新进展及未来展望[J].西北农林科技大学学报(社会科学版),2007,7(5)：49-55.
[54]韦艳华,张世英.金融市场非对称尾部相关结构的研究[J].管理学报,2005,2(5)：601-605.
[55]韦艳华,张世英.金融市场动态相关结构的研究[J].系统工程学报,2006,21(3)：313-317.
[56]杨绮霞.内地与香港股市金融板块的联动性研究[学位论文].北京：对外经贸大学,2007.
[57]Tversky, A. and Kahneman D. Advances in Prospect Theory:Cumulative Representation of Uncertainty. Joural of Risk and Uncertainty,1992,5:297-323.
[58]Nelsen R B. An Introduction to Copulas[M]. New York:Springer,2006.
[59]韦艳华,张世英.Copula理论及其在金融分析上的应用[M].北京：清华大学出版社,2008,1-2页.
[60]Engle R F. Autoregressive heteroskedasticity with estimation of the variance of U. K. inflation [J]. Econometrica,1982,50:987-1008.