人民币汇率与股市的风险溢出效应再检验——基于马尔科夫转换GARCH模型和混合时变copula模型的研究

财经论丛 ›› 2018, Vol. 34 ›› Issue (9): 55-65.

人民币汇率与股市的风险溢出效应再检验——基于马尔科夫转换GARCH模型和混合时变copula模型的研究

赵放¹, 刘雅君²

1.吉林大学经济学院,吉林长春 130012;
2.吉林省社会科学院《社会科学战线》杂志社,吉林长春 130031

收稿日期:2018-03-02 出版日期:2018-09-10 发布日期:2018-09-11
作者简介:赵放(1983-),男,吉林长春人,吉林大学经济学院副教授,博士生导师;刘雅君(1983-),女,河北邯郸人,吉林省社会科学院《社会科学战线》杂志社副研究员,博士。
基金资助:
吉林省科技厅软科学项目(20180418026FG);吉林省教育厅“十三五”社科项目(JJKH20180300JY)

Revaluation of RMB Exchange Rate and Stock Market Risk Spillover Effect: Research on Markov Switching Model Based on Markov Switching and Mixed Time-Varying Copula

ZHAO Fang¹, LIU Yajun²

1.School of Economics, Jilin University, Changchun 130012, China;
2.“Social Science Front” Magazine, Jilin Academy of Social Science, Changchun 130031,China

Received:2018-03-02 Online:2018-09-10 Published:2018-09-11

摘要/Abstract

摘要： 本文以人民币兑美元汇率和沪深300指数为研究对象,使用马尔科夫转换GARCH模型分析了两者的波动非线性特征,利用该模型将汇率波动按照低频和高频状态分成了三个区间,并且从时间上与2015年的汇改相重合。同时,使用混合时变copula对三个子样本上汇率市场和股票市场波动率关联性建模。研究发现:2015年的汇率改革重塑我国汇率市场和股票市场的风险溢出效应;汇改后,两市风险关联性增加,并表现出了正面溢出效应。

关键词: 马尔科夫转换GARCH模型, 混合时变copula模型, 汇率, 风险溢出效应

Abstract: This paper uses the exchange rate of RMB against the US dollar and the CSI 300 Index as the research objects, and applies the Markov-Switching GARCH model to analyze the nonlinear characteristics of the two. The exchange rate fluctuations are divided into three intervals according to the low-frequency and high-frequency conditions, which coincide with the 2015 reform in terms of time. We then use the mixed time-varying copula to construct a model of the volatility of the exchange rate and the stock market in three sub-samples. The study finds that the exchange rate reform in 2015 reshaped the risk spillover effect of China's exchange rate market and stock market. After the exchange rate reform, the risk correlation between the two markets has increased and showed a positive spillover effect.

Key words: Markov-switch GARCH Model, Mixed Time-varying Copula, Exchange Rate, Risk Spillover Effect

中图分类号:

F832.5

赵放, 刘雅君. 人民币汇率与股市的风险溢出效应再检验——基于马尔科夫转换GARCH模型和混合时变copula模型的研究[J]. 财经论丛, 2018, 34(9): 55-65.

ZHAO Fang, LIU Yajun. Revaluation of RMB Exchange Rate and Stock Market Risk Spillover Effect: Research on Markov Switching Model Based on Markov Switching and Mixed Time-Varying Copula[J]. , 2018, 34(9): 55-65.

参考文献

[1] 刘莉, 万解秋. 我国股市与汇市之间关系的再检验——基于滚动时间窗口技术和阈值误差修正模型的证据[J]. 国际金融研究, 2011,(7):90-96.
[2] 周爱民, 韩菲. 股指期货与现货市场的风险溢出研究[J]. 财贸经济, 2017, (8):52-65.
[3] 曹广喜, 崔维军, 韩彦. 人民币汇率弹性调整对我国汇市与股市关系的影响——基于长记忆VAR-(BEKK)MVGARCH模型[J]. 数理统计与管理, 2014, (6):1101-1112.
[4] Dornbusch R., Fischer S. Exchange Rates and the Current Account[J]. The American Economic Review, 1980, 70(5): 960-971.
[5] Branson W. H. Macroeconomic Determinants of Real Exchange Rates[Z]. NBER Working Paper,1981.
[6] Granger C. W. J., Huangb B. N., Yang C. W. A Bivariate Causality between Stock Prices and Exchange Rates: Evidence from Recent Asianflu[J]. Quarterly Review of Economics & Finance, 1998, 40(3):337-354.
[7] 张兵, 封思贤, 李心丹,等. 汇率与股价变动关系:基于汇改后数据的实证研究[J]. 经济研究, 2008,(9):70-81.
[8] Chien Chung Nieh, HweyYun Yau. The Impact of Renminbi Appreciation on Stock Prices in China[J]. Emerging Markets Finance & Trade, 2010, 46(1):16-26.
[9] 张碧琼, 李越. 汇率对中国股票市场的影响是否存在:从自回归分布滞后模型(ARDL-ecm)得到的证明[J]. 金融研究, 2002,(7):26-35.
[10] 周虎群, 李育林. 国际金融危机下人民币汇率与股价联动关系研究[J]. 国际金融研究, 2010,(8):69-76.
[11] 陈云, 陈浪南, 林鲁东. 人民币汇率与股票市场波动溢出效应研究[J]. 管理科学, 2009, (3):104-112.
[12] 何诚颖, 刘林, 徐向阳,等. 外汇市场干预、汇率变动与股票价格波动——基于投资者异质性的理论模型与实证研究[J]. 经济研究, 2013,(10):29-42.
[13] Hamilton J. D. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle[J]. Econometrica, 1989, 57(2): 357-384.
[14] Gray S. F. Modeling the Conditional Distribution of Interest Rates as a Regime-Switching Process[J]. Journal of Financial Economics, 1996, 42(1): 27-62.
[15] Haas M., Mittnik S., Paolella M. S. A New Approach to Markov-switching GARCH Models[J]. Journal of Financial Econometrics, 2004, 2(4): 493-530.
[16] Sklar M. Fonctions Derepartition an Dimensions et Leurs Marges[D]. Publ. Inst. Statist. Univ. Paris, 1959, 8: 229-231.
[17] Engle R. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models[J]. Journal of Business & Economic Statistics, 2002, 20(3): 339-350.