主管：中国科学院
主办：中国优选法统筹法与经济数学研究会
　　　中国科学院科技战略咨询研究院
中国管理科学

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

• 论文 • 上一篇    

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. 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 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. 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 Published:2023-05-06
  • Contact: 孙晓蕾 E-mail:xlsun@casisd.cn

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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

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