基于溢出效应的金融危机早期预警方法研究

doi:10.16381/j.cnki.issn1003-207x.2020.1190

中国管理科学 ›› 2023, Vol. 31 ›› Issue (4): 35-45.doi: 10.16381/j.cnki.issn1003-207x.2020.1190

基于溢出效应的金融危机早期预警方法研究

郝俊¹, 李建平¹, 冯倩倩², ³, 孙晓蕾², ³

1.中国科学院大学经济与管理学院，北京 100190；2.中国科学院科技战略咨询研究院，北京 100190；3.中国科学院大学公共政策与管理学院，北京 100049

收稿日期:2020-06-22 修回日期:2021-03-12 出版日期:2023-04-20 发布日期:2023-05-06
通讯作者: 孙晓蕾(1981-)，女(汉族)，山东烟台人，中国科学院科技战略咨询研究院,研究员，博士，研究方向：风险管理，Email:xlsun@casisd.cn. E-mail:xlsun@casisd.cn
基金资助:
国家自然科学基金资助项目(72201265，72071197，92046023，T2293774)；中国博士后科学基金资助项目(2022M723105)，中央高校基本科研业务费专项资金资助项目（E2E40803）；中国科学院大学数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育)基金资助项目

Early Warning of Financial Crisis Based on the Spillover Effects

HAO Jun¹, LI Jian-ping¹, FENG Qian-qian², ³, SUN Xiao-lei², ³

1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China；2. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China；3. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100149, China

Received:2020-06-22 Revised:2021-03-12 Online:2023-04-20 Published:2023-05-06
Contact: 孙晓蕾 E-mail:xlsun@casisd.cn

摘要/Abstract

摘要： 新冠肺炎疫情冲击，叠加油价下跌等不确定性因素使得全球金融市场承受巨大的下行压力；且金融市场内部的联动性不断增强，金融变量间的波动溢出效应往往会放大风险水平，因此国际社会对美国金融市场动荡是否会演化成金融危机保持极大担忧与高度警惕。在此背景下，如何有效刻画金融市场间的溢出效应，并实现对美国金融危机早期预警已成为关注焦点。对此，本文首先考虑疫情冲击下金融市场波动特点，构建涵盖9个市场、涉及15项指标的危机预警指标体系；其次，引入广义预测误差方差分解和复杂网络技术，刻画金融市场间的溢出效应；最后，将溢出效应引入传统KLR模型之中，实现了考虑指标间溢出效应的危机预警信号综合集成。结果表明：基于溢出效应强度构建的综合预警模型能够更为精准地捕捉危机信号；危机预警信号在2020年4月已接近2008年金融危机的早期水平，但仍存在一定距离，需要持续关注其未来走势。

关键词: 金融危机；危机预警；信号分析；溢出效应

Abstract: Affected by the COVID-19 epidemic and falling oil prices, global financial markets are under tremendous downward pressure. There is great concern and vigilance about whether the turmoil in the US financial market will evolve into a financial crisis. At the same time, the spillover effects between financial sub-markets have multiplier influences on the financial crisis. Under this circumstance, this study focuses on effectively describing the spillovers among financial sub-markets and accurately realizing the early warning of the financial market crisis in the United States. Firstly, based on the characteristics of recent financial market volatility under the impact of the epidemic, 15 financial crisis warning indicators covering 9 sub-markets are selected. Secondly, a novel volatility spillover network method, which is based on generalized prediction error variance decomposition and complex network technology, is adopted to characterize the spillover features among financial markets. Then, two integrated strategies for crisis warning signals are generated based on traditional integration weights and considering the spillover effects of warning indicators. Finally, the KLR signal model is operated to extract and quantify the crisis early warning signals of the US financial market under the impact of the COVID-19 epidemic, which will help our country avoid or reduce the possible damage caused by the financial crisis, ensure high-quality economic development and maintain social prosperity stable.

Key words: financial crisis; early warning; signal analysis; spillover effect

中图分类号:

F830.9

郝俊, 李建平, 冯倩倩, 孙晓蕾. 基于溢出效应的金融危机早期预警方法研究[J]. 中国管理科学, 2023, 31(4): 35-45.

HAO Jun, LI Jian-ping, FENG Qian-qian, SUN Xiao-lei. Early Warning of Financial Crisis Based on the Spillover Effects[J]. Chinese Journal of Management Science, 2023, 31(4): 35-45.

参考文献

［1］ Hazera A, Quirvan C, Triki A. Too big to fail and bank loan accounting in developing nations: evidence from the Mexican financial crisis［J］. Research in Accounting Regulation, 2017, 29(2): 109-118.
［2］张雪彤,张卫国,王超.发达市场与新兴市场的尾部风险—溢出、传染与传染动因检验［J］.中国管理科学2023, DOI:10.16381/j.cnki.issn1003-207x.2021.2441.Zu Xuetong, Zhang Weiguo, Wang Chao. Tail risks in developed and emerging markets—Test of spillover, contagion and contagion determinants［J］. Chinese Journal of Management Science, 2023, DOI:10.16381/j.cnki.issn1003-207x.2021.2441.
［3］杨子晖, 陈雨恬, 张平淼. 重大突发公共事件下的宏观经济冲击、金融风险传导与治理应对［J］. 管理世界, 2020, 36(5): 13-35+17.Yang Zihui, Chen Yutian, Zhang Pingmiao. Macroeconomic shock, financial risk transmission and governance response to major public emergencies［J］. Management World, 2020, 36(5): 13-35+17.
［4］刘世锦, 韩阳, 王大伟. 基于投入产出架构的新冠肺炎疫情冲击路径分析与应对政策［J］. 管理世界, 2020, 36(5): 1-12+51+263.Liu Shijin, Han Yang, Wang Dawei. An impact path analysis of covid-19 outbreak in china and policy response［J］. Management World, 2020, 36(5): 1-12+51+263.
［5］ Salvatore D. Growth and trade in the United States and the world economy: overview［J］. Journal of policy modeling. 2020, 42(4): 750-759.
［6］ Bekiros S D. Contagion, decoupling and the spillover effects of the US financial crisis: evidence from the BRIC markets［J］. International Review of Financial Analysis, 2014, 33: 58-69.
［7］ Chadwick M G. Dependence of the “Fragile Five” and “Troubled Ten” emerging market financial systems on US monetary policy and monetary policy uncertainty［J］. Research in International Business and Finance, 2019, 49: 251-268.
［8］ Frankel J A, Rose A K. Currency crashes in emerging markets: an empirical treatment［J］. Journal of International Economics, 1996, 41: 351-366.
［9］ Sachs J, Tornell A, Velasco A. The Mexican peso crisis: sudden death or death foretold［J］. Journal of International Economics, 1996, 41: 265-283.
［10］ Kaminsky G, Lizondo S, Reinhart C M. Leading indicators of currency crise［J］. Palgrave Macmillan Journals, 1998, 45(1): 1-48.
［11］ Peng Duan, Bajona Cuan. China’s vulnerability to currency crisis: a KLR signals approach［J］. China Economic Review, 2008, 19(2): 138-151.
［12］ Abdelsalam M A M, Abdel-Latif H. An optimal early warning system for currency crises under model uncertainty［J］. Central Bank Review. 2020, 20(3): 99-107.
［13］ Illing M, Liu Ying. An index of financial stress for canada, bank of canada working paper［R］. Working Paper, 2003.
［14］ Frankel J, Saravelos G. Can leading indicators assess country vulnerability? Evidence from the 2008-2009 Global Financial Crisis［J］. Journal of International Economics, 2012, 87(2): 216-231.
［15］ Coudert V, Idier J. Reducing model risk in early warning systems for banking crises in the euro area ［J］. International Economics, 2018, 156: 98-116.
［16］ Dawood M, Horsewood N, Strobel F. Predicting sovereign debt crises: an early warning system approach ［J］. Journal of Financial Stability, 2017, 28: 16-28.
［17］李建平, 王军, 冯倩倩,等. 基于多元驱动因素的主权CDS利差预测研究［J］. 计量经济学报, 2021,1(2): 362-376.Li Jianping, Wang Jun, Feng Qianqian, et al. Forecasting sovereign CDS spreads based on multiple determinants［J］. China Journal of Econometrics, 2021,1(2): 362-376.
［18］刘超,张瑞雪,朱相宇.金融风险与宏观经济风险的交互行为研究［J］.管理评论,2022,34(2):46-61.Liu Chao, Zhang Ruixue, Zhu Xiangyu. Research on the interaction between financial risk and macroeconomic risk［J］. Management Review, 2022,34(2):46-61.
［19］ Feng Qianqian, Wang Yijing, Sun Xiaolei, et al. What drives cross-border spillovers among sovereign CDS, foreign exchange and stock markets? ［J］. Global Finance Journal, 2022, DOI: 10.1016/j.gfj.2022.100773
［20］傅强,石泽龙.系统性金融风险的联合网络关联度测量及频率研究——基于局部平稳的非参数时变VHAR模型［J］.中国管理科学,2023,DOI:10.16381/j.cnki.issn1003-207x.2021.1266.Fu Qiang, Shi Zelong. Research on frequency of the joint network connectedness of systemic financial risks in china: based on the locally stationary non-parametric time-varying vector HAR model［J］. Chinese Journal of Management Science, 2023, DOI:10.16381/j.cnki.issn1003-207x.2021.1266.
［21］范宏, 陈乃熙.基于溢出效应的多级风险传染机理及实证研究［J］.中国管理科学,2020, DOI:10.16381/j.cnki.issn1003-207x.2020.1572.Fan Hong, Chen Naixi. Multi-stage risk contagion mechanism and empirical study based on spillover effect［J］. Chinese Journal of Management Science, 2020, DOI:10.16381/j.cnki.issn1003-207x.2020.1572.
［22］孙灏, 朱晓谦, 李建平. 考虑财务报告中文本风险信息的财务困境预测. 系统管理学报, 2022, 31(6): 1204-1215.Sun Hao, Zhu Xiaoqian, Li Jianping. Financial distress prediction based on textual risk disclosures in financial reports［J］. Journal of Systems & Management, 2022, 31(6): 1204-1215.
［23］ Flavin T J, Sheenan L. The Role of U.S. subprime mortgage-backed assets in propagating the crisis: contagion or interdependence? ［J］. The North American Journal of Economics and Finance, 2015, 34: 167-186.
［24］ IMF. Global Financial Stability Report: Responding to the Financial Crisis and Measuring Systemic Risk ［R］. 2009.
［25］杨子晖, 周颖刚. 全球系统性金融风险溢出与外部冲击［J］. 中国社会科学, 2018(12): 69-90+200-201.Yang Zihui, Zhou Yinggang. Global systemic financial risk spillovers and their external shocks［J］. Social Sciences in China, 2018(12): 69-90+200-201.
［26］姚晓阳, 孙晓蕾, 李建平. 考虑市场相关性的中国金融压力指数构建方法与实证［J］. 管理评论, 2019, 31(4): 34-41.Yao Xiaoyang, Sun Xiaolei, Li Jianping. China financial stress index under correlations between markets［J］. Management Review, 2019, 31(4): 34-41.
［27］姚晓阳, 孙晓蕾, 吴登生,等. 基于互信息熵的国家风险相关性研究［J］. 系统工程理论与实践, 2015, 35(7): 1657-1665.Yao Xiaoyang, Sun Xiaolei, Wu Dengsheng, et al. Correlation research of country risk based on mutual information［J］. Systems Engineering Theory & Practice, 2015, 35(7): 1657-1665.
［28］赵林海, 陈名智. 金融机构系统性风险溢出和系统性风险贡献——基于滚动窗口动态Copula模型双时变相依视角［J］. 中国管理科学,2021,29(7):71-83.Zhao Linhai, Chen Mingzhi. Systemic risk spillovers and systemic risk contributions of financial institutions in china: a perspective of dual time-varying dependence of rolling window dynamic copula model［J］. Chinese Journal of Management Science,2021,29(7):71-83.
［29］钟婉玲, 李海奇, 杨胜刚. 国际油价、宏观经济变量与中国股市的尾部风险溢出效应研究［J］. 中国管理科学, 2022,30(2):27-37.Zhong Wanling, Li Haiqi, Yang Shenggang. Tail risk spillover effects among crude oil price, macroeconomic variables, and china’s stock market［J］. Chinese Journal of Management Science, 2022,30(2):27-37.
［30］ 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.

[1]	成思聪,王天一. 引入隔夜信息的期权定价模型研究[J]. 中国管理科学, 2024, 32(9): 1-10.
[2]	吴鑫育,谢海滨,马超群. 经济政策不确定性与人民币汇率波动率[J]. 中国管理科学, 2024, 32(8): 1-14.
[3]	于孝建,刘国鹏,刘建林,肖炜麟. 基于LSTM网络和文本情感分析的股票指数预测[J]. 中国管理科学, 2024, 32(8): 25-35.
[4]	倪宣明,郑田田,赵慧敏,武康平. 基于最优异质收益率因子的资产定价研究[J]. 中国管理科学, 2024, 32(8): 50-60.
[5]	蔡毅,唐振鹏,吴俊传,杜晓旭,陈凯杰. 基于灰狼优化的混频支持向量机在股指预测与投资决策中的应用研究[J]. 中国管理科学, 2024, 32(5): 73-80.
[6]	张雪彤,张卫国,王超. 发达市场与新兴市场的尾部风险[J]. 中国管理科学, 2024, 32(4): 14-25.
[7]	尹海员,寇文娟. 基于朴素贝叶斯法的投资者情绪度量及其对股票特质风险的影响[J]. 中国管理科学, 2024, 32(4): 38-47.
[8]	吴鑫育,姜晓晴,李心丹,马超群. 基于已实现EGARCH-FHS模型的上证50ETF期权定价研究[J]. 中国管理科学, 2024, 32(3): 105-115.
[9]	冯倩倩,孙晓蕾,郝俊. 基于状态转移回归的动态集成时序预测方法[J]. 中国管理科学, 2024, 32(2): 307-314.
[10]	盛积良,黄毅,李居超. 我国行业风险敞口与行业网络结构的相关性研究[J]. 中国管理科学, 2024, 32(2): 199-209.
[11]	白兰,魏宇. 投资者公共卫生事件关注度与我国行业股票市场信息溢出效应研究[J]. 中国管理科学, 2024, 32(1): 54-64.
[12]	孟斌,廉荣文隽,隋聪,匡海波. 重大事件是否影响了航运市场溢出传递的稳定性[J]. 中国管理科学, 2023, 31(11): 46-57.
[13]	王明涛,李茜. 融资融券降低了交易中的信息不对称程度吗？[J]. 中国管理科学, 2023, 31(10): 1-11.
[14]	郭延禄,罗公利,侯贵生,王晓彤. “种草”与“翻车”：网红直播带货的产品质量问题与治理研究[J]. 中国管理科学, 2023, 31(10): 162-174.
[15]	冯易,王杜娟,胡知能,崔少泽. 基于改进LightGBM集成模型的胃癌存活性预测方法[J]. 中国管理科学, 2023, 31(10): 234-244.

基于溢出效应的金融危机早期预警方法研究

Early Warning of Financial Crisis Based on the Spillover Effects

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0