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

本文以33家上市金融机构为研究样本，利用滚动窗口动态Copula模型对金融机构与金融系统之间相依关系的时变结构与时变系数进行双时变拟合，测度了金融机构的系统性风险溢出和贡献，从宏观、行业和机构层面分析了系统性风险贡献的影响因素。研究发现：证券类机构贡献了最多的系统性风险，而银行类机构对整个金融系统最具有潜在威胁性；金融机构与金融系统的相依结构决定了机构风险的外溢程度，而金融机构与金融系统之间相依程度以及系统自身波动性会显著影响整个系统的系统性风险；中国金融风险与财政风险之间存在相互转换的现象，化解系统性风险的根本办法是不断改善金融生态环境。本文可能的贡献有两点：第一，建立具有双时变特征的滚动窗口动态Copula模型，使模型设定和估计结果更接近真实情形；第二，从宏观、行业、机构三个层面分析机构系统性风险贡献的影响因素，这有助于从系统性风险产生的源头进行风险防控，供监管部门决策参考。

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

In recent years, China's financial sector has encountered more and more unstable factors than before. A number of factors, domestic and foreign, such as the increasing fiscal deficit of the central government, the heavy debt of local government, and the rising bad loans of banks, the trade conflicts between China and the United States and other developed countries, directly or indirectly pose a potential threat to the normal operation of China's financial sector and enhancing the expectation of financial instability of China. Due to China's current macroeconomic environment and uncertainty faced by China's financial sector, the decision-making authorities of Chinese government attach great importance to the prevention and resolution of systemic financial risks. How to continuously improve the accuracy of the model for risk measurement and prediction, and provide more reliable, multi-level and multi-perspective reference for the formulation and implementation of effective regulatory policies is the direction of joint efforts of academia and regulatory authorities. In view of this, this paper takes 33 listed financial institutions in the four industries, banking, securities, insurance and comprehensive financial services in China, as samples to empirically study their systemic risk spillovers, their systemic risk contributions and the determinants. The rolling window dynamic copula model is applied to fit both the time-varying structures and the time-varying coefficients of the dependence between financial institutions and the financial system. The systemic risks of sample financial institutions are measured with this dynamic dependent structure fitting framework, and the determinants of the systemic risk contributions of these financial institutions are investigated through macro, industry and institution-level analyses. The main conclusions are as follows. First, the systemic risk contributions of financial institutions in securities industry are the largest, while banking institutions are the biggest potential threat to the financial system. Second, the dependence structures of institutions and the system determine the size of institutional risk spillovers, and the degree of dependence between institutions and the system, and the volatility of the system significantly affect the systemic risk of the system as a whole. Third, there is a phenomenon of mutual transformation between financial risk and fiscal risk in China. The fundamental way to resolve the systemic financial risk is sticking to the improvement of the financial ecological environment. The contributions of this paper are as follows. Firstly, an improved dynamic copula model with dual time-varying characteristics is established to make the model settings and estimation closer to the real. Secondly, the determinants of systemic risk contributions of the financial institutions are analyzed from macro, industry and institution levels, which helps prevent and control risks from the source of systemic risk and can be used as a reference for regulatory decision-making.