基于单因子MSV-CoVaR模型的金融市场风险溢出度量研究
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摘要
在全球经济一体化进程加速的背景下,信息、资本的自由流动变得更加畅通,金融市场风险从一个市场传向了另一个市场,金融市场风险溢出效应研究也成了金融监管部门以及国内外学者关注的焦点。本文以条件在险价值(CoVaR)法为基础,结合单因子MSV模型分析了我国股票市场与ETF市场之间的风险溢出效应。结果表明,股票市场与ETF市场之间存在双向风险溢出效应,且股票市场对ETF市场的风险溢出效应强于ETF市场对股票市场的风险溢出效应。此外,文章还发现波动冲击对股票市场与ETF市场的影响都较为持久。本文的实证结果能够为投资者在进行股票和ETF投资时提供决策依据,对金融市场监管也有一定的参考价值。
Under the background of economic globalization,with the process of the world economic integration,the free flow of information and capital becomes more clear,and the financial market risk transfer from one market to another market.Therefore,study of the risk spillover effect of financial markets has become the focus of financial supervision departments and scholars.In paper,the risk spillover effect between stock market and ETF market in china is analyzed based on CoVaR method combined with Afactor-MSV model.This combined model can measure the risk spillover effect between two different markets without copula functions,and it has higher fitting degree in reality than other models.In the first step,joint distribution model of stock market and ETF market is established by using the Afactor-MSV model,and MCMC method based on Gibbs sampling is put forward to estimate parameters of the combined model.Then,the risk spillover intensity between two markets is measured by using CoVaR function.Based on the daily prices of Chinese stock market index and ETF market index over January 4,2010-April 30,2015,our results demonstrate that there is two-way spillover effect between stock market and ETF market in china,the degree of risk spillover effect from stock market to ETF market is stronger than that of from ETF market to stock market.Meanwhile,it is also found that there is long-lasting effect of volatility shock on stock market and ETF Market.The empirical results can provide the reference for investors making investment decisions,and it is also valuable for regulation of financial markets.
Under the background of economic globalization,with the process of the world economic integration,the free flow of information and capital becomes more clear,and the financial market risk transfer from one market to another market.Therefore,study of the risk spillover effect of financial markets has become the focus of financial supervision departments and scholars.In paper,the risk spillover effect between stock market and ETF market in china is analyzed based on CoVaR method combined with Afactor-MSV model.This combined model can measure the risk spillover effect between two different markets without copula functions,and it has higher fitting degree in reality than other models.In the first step,joint distribution model of stock market and ETF market is established by using the Afactor-MSV model,and MCMC method based on Gibbs sampling is put forward to estimate parameters of the combined model.Then,the risk spillover intensity between two markets is measured by using CoVaR function.Based on the daily prices of Chinese stock market index and ETF market index over January 4,2010-April 30,2015,our results demonstrate that there is two-way spillover effect between stock market and ETF market in china,the degree of risk spillover effect from stock market to ETF market is stronger than that of from ETF market to stock market.Meanwhile,it is also found that there is long-lasting effect of volatility shock on stock market and ETF Market.The empirical results can provide the reference for investors making investment decisions,and it is also valuable for regulation of financial markets.
引文
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[4]熊正德,韩丽君.金融市场间波动溢出效应研究——GC-MSV模型及其应用[J].中国管理科学,2013,21(2):32-41.
[5]史永东,丁伟,袁绍锋.市场互联、风险溢出与金融稳定——基于股票市场与债券市场溢出效应分析的视角[J].金融研究,2013,(3):170-180.
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[10]李成,马文涛,王彬.我国金融市场间溢出效应研究——基于四元VAR-GARCH(1,1)-BEKK模型的分析[J].数量经济技术经济研究,2010,(6):3-19.
[11]熊正德,文慧,熊一鹏.我国外汇市场与股票市场间波动溢出效应实证研究——基于小波多分辨的多元BEKK-GARCH(1,1)模型分析[J].中国管理科学,2015,23(4):30-38.
[12]邓超,陈学军.基于复杂网络的金融传染风险模型研究[J].中国管理科学,2014,22(11):11-18.
[13]欧阳红兵,刘晓东.中国金融机构的系统重要性及系统性风险传染机制分析——基于复杂网络的视角[J].中国管理科学,2015,23(10):30-37.
[14]Adrian T,Brunnermeier M K.CoVaR[J].American Economic Review,2016,106(7):1705-1741.
[15]Girardi G,Ergün A T,Systemic risk measurement:Multivariate GARCH estimation of CoVaR[J].Journal of Banking&Finance,2013,37(8):3169-3180.
[16]熊正德,韩丽君.基于MSV类模型的中国汇市与股市间溢出效应[J].系统工程,2010,28(10):47-53.
[17]张瑞锋,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.
[18]Harvey A,Ruiz E,Shephard N.Multivariate stochastic variance models[J].Review of Economic Studies,1994,61(2):247-264.
[19]Jacquier,Polson N G,Rossi P E.Models and priors for multivariate stochastic volatility[R].CIRANO Working Paper,1995.
[20]Jacquier,Polson N G,Rossi P E.Stochastic volatility:Univariate and multivariate extensions[R].CIRANO Working Paper,1999.
[21]Diebold F X,Nerlove M.The dynamics of exchange rate volatility:A multivariate latent factor ARCH model[J].Journal of Applied Econometrics,1989,4(1):1-21.
[22]Yu Jun,Meyer R.Multivariate stochastic volatility models:Bayesian estimation and model comparison[J].Econometric Reviews,2006,25(2-3):361-384.
[2]洪永淼,成思危,刘艳辉,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(季刊),2004.3(3):703-726.
[3]刘晓星,段斌,谢福座.股票市场风险溢出效应研究:基于EVT-Copula-CoVaR模型的分析[J].世界经济,2011,(11):145-159.
[4]熊正德,韩丽君.金融市场间波动溢出效应研究——GC-MSV模型及其应用[J].中国管理科学,2013,21(2):32-41.
[5]史永东,丁伟,袁绍锋.市场互联、风险溢出与金融稳定——基于股票市场与债券市场溢出效应分析的视角[J].金融研究,2013,(3):170-180.
[6]柏满迎,吴琪,吴天都.我国股票市场与基金市场间的风险溢出研究[J].统计研究,2014,(4):108-109.
[7]Hong Yongmiao,Liu Yanhui,Wang Shouyang.Detecting extreme risk spillover between financial markets[R].Working Paper,Cornell University,2003.
[8]Hong Yongmiao.Granger causility in risk and detection of risk between two time series[R].Working Paper,Corneu University,2001.
[9]潘慧峰,张金水.国内外石油市场的极端风险溢出检验[J].中国管理科学,2007,15(3):25-30.
[10]李成,马文涛,王彬.我国金融市场间溢出效应研究——基于四元VAR-GARCH(1,1)-BEKK模型的分析[J].数量经济技术经济研究,2010,(6):3-19.
[11]熊正德,文慧,熊一鹏.我国外汇市场与股票市场间波动溢出效应实证研究——基于小波多分辨的多元BEKK-GARCH(1,1)模型分析[J].中国管理科学,2015,23(4):30-38.
[12]邓超,陈学军.基于复杂网络的金融传染风险模型研究[J].中国管理科学,2014,22(11):11-18.
[13]欧阳红兵,刘晓东.中国金融机构的系统重要性及系统性风险传染机制分析——基于复杂网络的视角[J].中国管理科学,2015,23(10):30-37.
[14]Adrian T,Brunnermeier M K.CoVaR[J].American Economic Review,2016,106(7):1705-1741.
[15]Girardi G,Ergün A T,Systemic risk measurement:Multivariate GARCH estimation of CoVaR[J].Journal of Banking&Finance,2013,37(8):3169-3180.
[16]熊正德,韩丽君.基于MSV类模型的中国汇市与股市间溢出效应[J].系统工程,2010,28(10):47-53.
[17]张瑞锋,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.
[18]Harvey A,Ruiz E,Shephard N.Multivariate stochastic variance models[J].Review of Economic Studies,1994,61(2):247-264.
[19]Jacquier,Polson N G,Rossi P E.Models and priors for multivariate stochastic volatility[R].CIRANO Working Paper,1995.
[20]Jacquier,Polson N G,Rossi P E.Stochastic volatility:Univariate and multivariate extensions[R].CIRANO Working Paper,1999.
[21]Diebold F X,Nerlove M.The dynamics of exchange rate volatility:A multivariate latent factor ARCH model[J].Journal of Applied Econometrics,1989,4(1):1-21.
[22]Yu Jun,Meyer R.Multivariate stochastic volatility models:Bayesian estimation and model comparison[J].Econometric Reviews,2006,25(2-3):361-384.