中国上市商业银行系统性风险测度——基于SCCA方法的分析

发布时间：2018-07-05 13:44

本文选题：SCCA + 时变多元Copula函数　；参考：《金融与经济》2017年02期

【摘要】：本文利用系统性或有权益分析法(SCCA),优化采用时变多元Copula函数测度了我国14家上市银行2007年第4季度至2016年第3季度的系统性风险。实证结果表明:基于时变多元Copula函数的SCCA方法能很好地体现银行系统性风险的整体性和时变性;回归分析证明银行资产的流动性水平、资本充足率、信贷资产质量和宏观经济形势等对系统性风险都有显著影响。本研究对我国商业银行风险监管提供了理论支持。
[Abstract]:In this paper, the systematic contingent Analysis (SCCA) is used to optimize the use of time-varying multivariate Copula function to measure the systemic risk of 14 listed banks from the fourth quarter of 2007 to the third quarter of 2016. The empirical results show that the SCCA method based on time-varying multivariate Copula function can well reflect the integrity and temporal variability of bank systemic risk, and the regression analysis proves that the liquidity level and capital adequacy ratio of bank assets can be improved. Credit asset quality and macroeconomic situation have a significant impact on systemic risk. This study provides theoretical support for risk supervision of commercial banks in China.
【作者单位】：南京师范大学商学院金融工程研究所;
【基金】：国家社会科学基金青年项目(12CJY108) 教育部“长江学者和创新团队发展计划”资助项目(IRT13020)
【分类号】：F832.33

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