摘要
银行业与实体行业间存在复杂网络连接,银行系统稳定受各行业影响。本文将实体行业纳入银行系统性风险分析框架,基于金融加速器理论,探讨实体—银行间系统性风险双向反馈机理,对风险在实体—银行间的传递渠道和溢出效应进行剖析。随后,构建时变t-Copula-CoVaR模型,测度我国各实体行业与银行业间的系统性风险溢出效应。结果发现,实体—银行间系统性风险溢出效应显著,且呈时变特征。具体来看,房地产业对银行业的风险溢出效应最大;其次为交通运输业、采掘业、钢铁业、化工业。银行业对各行业的风险溢出存在差异,风险溢出效应最大的为房地产业;再次为钢铁业、有色金属业、采掘业、交通运输业等。管理银行业系统性风险不仅需加强银行内部风险控制,还应重点关注系统重要性行业、系统脆弱性行业对银行业的风险溢出,建立风险监控体系,形成风险隔离屏障。
There are complex connections between the banking industry and the real industry.The stability of the banking system is affected by various industries.In this paper,the entity industries are brought into the framework of bank systemic risk analysis.Based on the theory of financial accelerator,the two-way feedback mechanism of entity-bank systemic risk is proposed,and the transmission channel and risk overflow of systemic risk in entity-bank are analyzed.Then,based on the time-varying t-copula model,the CoVaR model is used to measure the systemic risk spillover effect between the real industry and the banking industry in China.The results show that:the systemic risk spillover effect between entities and banks is significant and time-varying.Specifically,the real estate industry has the largest risk spillover effect on the banking industry,followed by the transportation industry,mining industry,steel industry and chemical industry.There are differences in the risk spillover effect of the banking industry to various industries.The real estate industry has the largest risk spillover effect,followed by steel industry,non-ferrous metal industry,mining industry,transportation industry and so on.To manage systematic risks in the banking industry,it is not only necessary to strengthen the internal risk control of banks,but also to focus on the risk spillovers between systemically important industries,systemically vulnerable industries and the banking industry,so as to establish a risk monitoring system and form a risk isolation barrier.
出处
《国际金融研究》
CSSCI
北大核心
2019年第12期74-84,共11页
Studies of International Finance
基金
国家社科基金项目“金融—实体双向反馈网络下的银行业系统性风险评估与防控研究”(18BJY247)
教育部人文社会科学研究规划项目“基于Copula风险度量模型的养老基金资产配置问题研究”(16YJA790063)资助
