我国银行体系的系统性关联度分析:基于不对称CoVaR

陈国进, 钟灵, 张宇

系统工程理论与实践 ›› 2017, Vol. 37 ›› Issue (1) : 61-79.

PDF(924 KB)
PDF(924 KB)
系统工程理论与实践 ›› 2017, Vol. 37 ›› Issue (1) : 61-79. DOI: 10.12011/1000-6788(2017)01-0061-19
论文

我国银行体系的系统性关联度分析:基于不对称CoVaR

    陈国进1,2, 钟灵1, 张宇1
作者信息 +

Systemic linkages in the Chinese banking system: The asymmetric CoVaR approach

    CHEN Guojin1,2, ZHONG Ling1, ZHANG Yu1
Author information +
文章历史 +

摘要

根据系统性关联度的定义,使用不对称CoVaR方法,对我国单个银行与银行体系之间的系统性关联度和任意两个银行间的系统性关联度进行了测算.研究结果表明,我国银行体系的系统性关联度存在不对称性,使用不对称CoVaR方法重新估算我国银行体系的系统性关联度能为我国系统重要性银行的甄别和银行间系统性风险溢出的评估提供依据.进一步地,探讨出上述两种系统性关联度的主要影响因素为银行自身的特征变量,如贷款总额,股本,留存收益等.基于此,为我国银行业监管者提升银行风险监管水平和银行管理者制定准确的风险控制体系提供有益帮助.

Abstract

Based on the definition of systemic linkages, we employ the asymmetric CoVaR approach to estimate the systemic linkages between each Chinese bank and the Chinese banking system and the systemic linkages between two individual Chinese banks. We show that the systemic linkages in the Chinese banking system have asymmetric properties, thus we use the asymmetric CoVaR approach to reestimate the systemic linkages in the Chinese banking system. Our approach can be used to identify the systemically important banks in China and to assess the systemic risk spillovers in the Chinese banking system. Furthermore, we find that the determinants of the two kinds of systemic linkages are some bank characteristics, such as total loans, common equity, retained earnings and so on. These measures of systemic linkages serve as useful additional toolboxes to both bank supervisors and bank managers.

关键词

系统性关联度 / 我国银行体系 / 不对称CoVaR方法 / 系统性关联度影响因素

Key words

systemic linkages / the Chinese banking system / the asymmetric CoVaR approach / systemic linkages determinants

引用本文

导出引用
陈国进 , 钟灵 , 张宇. 我国银行体系的系统性关联度分析:基于不对称CoVaR. 系统工程理论与实践, 2017, 37(1): 61-79 https://doi.org/10.12011/1000-6788(2017)01-0061-19
CHEN Guojin , ZHONG Ling , ZHANG Yu. Systemic linkages in the Chinese banking system: The asymmetric CoVaR approach. Systems Engineering - Theory & Practice, 2017, 37(1): 61-79 https://doi.org/10.12011/1000-6788(2017)01-0061-19
中图分类号: F832   

参考文献

[1] IMF. Global financial stability report-Responding to the financial crisis and measuring systemic risks[R]. Washington: IMF, 2009.
[2] 汪冬华, 黄康, 龚朴. 我国商业银行整体风险度量及其敏感性分析——基于我国商业银行财务数据和金融市场公开数据[J]. 系统工程理论与实践, 2013, 33(2): 284-295. Wang D H, Huang K, Gong P. Integrated risk measurement of Chinese commercial banks and its sensitivity-Based on the financial data of Chinese commercial banks and the open data of the financial market[J]. Systems Engineering-Theory & Practice, 2013, 33(2): 284-295.
[3] Adrian T, Brunnermeier M K. CoVaR[J]. American Economic Review, 2016, 106(7): 1705-1741.
[4] Roengpitya R, Rungcharoenkitkul P. Measuring systemic risk and financial linkages in the Thai banking system[EB/OL].[2014-10-08]. https: //papers.ssrn.com/sol3/papers.cfm?abstract_id=1773208.
[5] Bernal O, Gnabo J Y, Guilmin G. Assessing the contribution of banks, insurance and other financial services to systemic risk[J]. Journal of Banking & Finance, 2014, 47: 270-287.
[6] Brunnermeier M K, Dong G N, Palia D. Banks' non-interest income and systemic risk[C]//American Finance Association 2012 Chicago Meetings Paper, 2012.
[7] Drakos A A, Kouretas G P. Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR[J]. International Review of Economics & Finance, 2015, 40: 127-140.
[8] Beber A, Brandt M W. When it cannot get better or worse: The asymmetric impact of good and bad news on bond returns in expansions and recessions[J]. Review of Finance, 2010, 14(1): 119-155.
[9] López-Espinosa G, Moreno A, Rubia A, et al. Short-term wholesale funding and systemic risk: A global CoVaR approach[J]. Journal of Banking & Finance, 2012, 36(12): 3150-3162.
[10] López-Espinosa G, Moreno A, Rubia A, et al. Systemic risk and asymmetric responses in the financial industry[J]. Journal of Banking & Finance, 2015, 58: 471-485.
[11] 肖璞, 刘轶, 杨苏梅. 相互关联性、风险溢出与系统重要性银行识别[J]. 金融研究, 2012, 12: 96-106.Xiao P, Liu Y, Yang S M. Interconnectedness, risk spillover and systemically important banks identification[J]. Journal of Financial Research, 2012, 12: 96-106.
[12] 白雪梅, 石大龙. 中国金融体系的系统性风险度量[J]. 国际金融研究, 2014, 6: 75-85.Bai X M, Shi D L. Measure systemic risk of Chinese financial system[J]. Studies of International Finance, 2014, 6: 75-85.
[13] 陆静, 胡晓红. 基于条件在险价值法的商业银行系统性风险研究[J]. 中国软科学, 2014, 4: 25-42.Lu J, Hu X H. Study on systemic risk of commercial banks based on conditional Value at Risk[J]. China Soft Science, 2014, 4: 25-42.
[14] 刘向丽, 顾舒婷. 房地产对金融体系风险溢出效应研究——基于AR-GARCH-CoVaR方法[J]. 系统工程理论与实践, 2014, 34(S1): 106-111.Liu X L, Gu S T. Research on risk spillovers from the real estate department to financial system based on AR-GARCH-CoVaR[J]. Systems Engineering-Theory & Practice, 2014, 34(S1): 106-111.
[15] 周天芸, 杨子晖, 余洁宜. 机构关联、风险溢出与中国金融系统性风险[J]. 统计研究, 2014, 31(11): 43-49.Zhou T Y, Yang Z H, Yu J Y. Interconnectedness, risk spillovers and China's financial systemic risk[J]. Statistical Research, 2014, 31(11): 43-49.
[16] IMF, BIS, FSB. Guidance to assess the systemic importance of financial institutions, markets and instruments: Initial considerations[R]. Report to the G20 Finance Ministers and Governors, 2009.

基金

国家自然科学基金(71471154);中央高校基本科研业务费专项资金(T2013221045)
PDF(924 KB)

521

Accesses

0

Citation

Detail

段落导航
相关文章

/