国际股市对中国股市风险溢出的叠加效应研究——基于FNAC-ΔCoES模型

管理评论 ›› 2023, Vol. 35 ›› Issue (3): 49-60.

国际股市对中国股市风险溢出的叠加效应研究——基于FNAC-ΔCoES模型

曹洁¹, 雷良海², 雷其然³

1. 盐城师范学院数学与统计学院, 盐城 224002;
2. 上海理工大学管理学院, 上海 200093;
3. 上海东方证券资本投资有限公司, 上海 200010

收稿日期:2021-03-02 出版日期:2023-03-28 发布日期:2023-04-28
通讯作者: 雷良海(通讯作者)，上海理工大学管理学院教授，博士生导师，博士。
作者简介:曹洁，盐城师范学院数学与统计学院副教授，博士；雷其然，上海东方证券资本投资有限公司研究
基金资助:
江苏省高等学校自然科学研究面上项目（20KJB110020）；上海市科学技术委员会软科学重点课题（18692103000）。

Research on the Superposition Effect of Risk Spillovers from International Stock Markets to China: Based on the FNAC-delta CoES Model

Cao Jie¹, Lei Lianghai², Lei Qiran³

1. School of Mathematics and Statistics, Yancheng Teachers University, Yancheng 224002;
2. Business School, University of Shanghai for Science and Technology, Shanghai 200093;
3. Shanghai Orient Securities Capital Investment Co., Ltd., Shanghai 200010

Received:2021-03-02 Online:2023-03-28 Published:2023-04-28

摘要/Abstract

摘要： 为了考察多个国际股票市场对中国股票市场风险溢出的叠加效应，将二维ΔCoES拓展至多维ΔCoES，并基于完全嵌套阿基米德Copula（FNAC）推导出多维ΔCoES的显式解，同时给出了风险溢出叠加效应的度量公式和显著性检验方法。实证研究结果显示：两个国际股市同时发生风险时，对中国股市的风险溢出存在显著的、非线性的叠加效应，但这种叠加效应不一定会随着陷入风险的国际股市数量的继续增多而持续加强；此外，通过对比不同国际股市组合下的风险溢出叠加效应发现，欧洲股票市场对叠加效应的影响相对更大；最后，鲁棒性检验结果显示，FNAC-ΔCoES模型具有良好的稳健性。

关键词: 风险溢出, 叠加效应, 完全嵌套阿基米德Copula, ΔCoES, 股票市场

Abstract: To investigate the superposition effect of risk spillovers from multiple international stock markets to China, this paper extends the two-dimensional delta CoES to multi-dimensional delta CoES, and derives its explicit solution based on the fully nested Archmedean Copula (FNAC). Then the measurement formula and significance test method of the superposition effect of risk spillover are given. The empirical results show that: when two international stock markets are at risk at the same time, there is a significant and non-linear superposition effect on risk spillovers from them to China’s stock market, but the superposition effect does not necessarily continue to strengthen with the increasing number of international stock markets at risk. In addition, by comparing the superposition effect of risk spillovers from different international stock market combinations, we find that European stock markets have the greatest impact on the superposition effect. Finally, the results of a robustness test show that the FNAC-delta CoES model is robust.

Key words: risk spillovers, superposition effect, fully nested Archimedean Copula, delta CoES, stock markets

曹洁, 雷良海, 雷其然. 国际股市对中国股市风险溢出的叠加效应研究——基于FNAC-ΔCoES模型[J]. 管理评论, 2023, 35(3): 49-60.

Cao Jie, Lei Lianghai, Lei Qiran. Research on the Superposition Effect of Risk Spillovers from International Stock Markets to China: Based on the FNAC-delta CoES Model[J]. Management Review, 2023, 35(3): 49-60.

参考文献

[1] Bollerslev T. Financial Econometrics:Past Developments and Future Challenges[J]. Journal of Econometrics, 2001,100(1):339-350
[2] King M. A., Wadhwani S. Transmission of Volatility between Stock Markets[J]. Review of Financial Studies, 1990,3(1):5-33
[3] Forbes K., Rigobon R. No Contagion, Only Interdependence:Measuring Stock Market Co-movements[J]. The Journal of Finance, 2002,57(5):2223-2261
[4] Kaminsky G., Reinhart C. M. On Crises, Contagion, and Confusion[J]. Journal of International Economics, 2000,51(1):145-168
[5] Engle R. F. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation[J]. Econometrics, 1982,50(4):987-1008
[6] Juri A., Wüthrich M. V. Copula Convergence Theorems for Tail Events[J]. Insurance Mathematics&Economics, 2002,30(3):405-420
[7] Diebold F. X., Yilmaz K. Better to Give than to Receive:Predictive Directional Measurement of Volatility Spillovers[J]. International Journal of Forecasting, 2012,28(1):57-66
[8] Adrian T., Brummermeier M. K. CoVaR[J]. American Economic Review, 2016,106(7):1705-1741
[9] Reboredo J. C., Ugolini A. Systemic Risk in European Sovereign Debt Markets:A CoVaR-copula Approach[J]. Journal of International Money and Finance, 2015,51(C):214-244
[10] Ji Q., Liu B. Y., Nehler H., et al. Uncertainties and Extreme Risk Spillover in the Energy Markets:A Time-varying Copula-based CoVaR Approach[J]. Energy Economics, 2018,76(10):115-126
[11] Tian C., Zhang B., Duan J. Based on Copula-CoVaR Model of Risk Spillover Effect of Oil Markets and Other Commodity Markets[J]. Journal of Intelligent and Fuzzy Systems, 2020,38(1990):1-11
[12] 李丛文,闫世军.我国影子银行对商业银行的风险溢出效应--基于GARCH-时变Copula-CoVaR模型的分析[J].国际金融研究, 2015,(10):64-75
[13] 侯县平,傅春燕,林子枭,等.极端风险溢出效应的定量测度及非对称性--来自中国股市与债市的经验证据[J].管理评论, 2020,32(9):55-67
[14] 张兴敏,傅强,张帅,等.金融系统的网络结构及尾部风险度量--基于动态半参数分位数回归模型[J].管理评论, 2021,33(4):59-70
[15] Acerbi C., Tasche D. On the Coherence of Expected Shortfall[J]. Journal of Banking&Finance, 2002,26(7):1487-1503
[16] Mainik G., Schaanning E. On Dependence Consistency of CoVaR and Some Other Systemic Risk Measures[J]. Statistics&Risk Modeling, 2014,31(1):49-77
[17] 张冰洁,汪寿阳,魏云捷,等.基于CoES模型的我国金融系统性风险度量[J].系统工程理论与实践, 2018,38(3):565-575
[18] Su E., Wong K. W. Measuring Bank Downside Systemic Risk in Taiwan[J]. The Quarterly Review of Economics and Finance, 2018,70(11):172-193
[19] 李政,梁琪,方意.中国金融部门间系统性风险溢出的监测预警研究--基于下行和上行ΔCoES指标的实现与优化[J].金融研究, 2019,(2):40-58
[20] Zhu B. Z., Zhou X. X., Liu X. F., et al. Exploring the Risk Spillover Effects among China's Pilot Carbon Markets:A Regular Vine Copula-CoES Approach[J]. Journal of Cleaner Production, 2020,242(1):118455
[21] 李强.基于Copula-CoES的资本市场、支柱行业及汇率风险溢出研究[J].管理工程学报, 2021,35(1):12-26
[22] 曹洁,雷良海.基于广义CoES方法的金融业与房地产业风险溢出研究[J].运筹与管理, 2021,30(4):200-205
[23] Cao Z. Multi-CoVaR and Shapely Value:A Systemic Risk Measure[R]. Working Paper of Banque de France DSF-SMF, 2014
[24] 许启发,王侠英,蒋翠侠,等.基于藤copula-CAViaR方法的股市风险溢出效应研究[J].系统工程理论与实践, 2018,38(11):2738-2749
[25] 张连增,胡祥.基于分层阿基米德Copula的金融时间序列的相关性分析[J].统计与信息论坛, 2014,29(6):34-40
[26] 严伟祥,徐玉华.基于分层阿基米德Copula的金融行业尾部风险相依性研究[J].金融经济学研究, 2017,32(6):23-33
[27] Nelsen R. An Introduction to Copulas[M]. Berlin:Springer Press, 2006
[28] Sklar A. Fonctions de Répartition á n Dimensions et leurs Marges[J]. Publication de l'lnstitut de Statistique de l'Universitdde Paris, 1959,8(1):229-231
[29] Joe H. Multivariate Models and Dependence Concepts[M]. London:Chapman&Hall Press, 1997
[30] McNeil A. J. Sampling Nested Archimedean Copulas[J]. Journal of Statistical Computation and Simulation, 2008,78(6):567-581
[31] Girardi G., Ergün A. T. Systemic Risk Measurement:Multivariate GARCH Estimation of CoVaR[J]. Journal of Banking&Finance, 2013,37:3169-3180
[32] Abadie A. Bootstrap Tests for Distributional Treatment Effects in Instrumental Variables Models[J]. Journal of the American Statistical Association, 2002,97(457):284-292
[33] Zheng Q. H., Song L. R. Dynamic Contagion of Systemic Risks on Global Main Equity Markets Based on Granger Causality Networks[J]. Discrete Dynamics in Nature and Society, 2018,2018:9461870
[34] 何敏园,李红权.全球股市间的相依结构与极值风险溢出:基于藤Copula的金融复杂性分析[J].管理评论, 2020,32(7):102-110