金融风险与风险传染——基于CCA方法的宏观金融网络分析  

Financial Risk and Risk Contagion: A Study of the Macro-Financial Network with A CCA Model

作　　者：刘磊 刘健[3] 郭晓旭 LIU Lei;LIU Jian;GUO Xiaoxu

机构地区：[1]中国社会科学院经济研究所 [2]国家金融与发展实验室 [3]中央财经大学保险学院 [4]美国哥伦比亚大学

出　　处：《金融监管研究》2019年第9期35-50,共16页Financial Regulation Research

基　　金：中国社会科学院当代中国马克思主义政治经济学创新智库资助项目成果

摘　　要：本文用CCA模型来分析基于SNA体系的中国各部门资产负债表,并通过改进宏观金融网络模型,借鉴谷歌网页排名算法,重新构建了网络调整后的各部门金融风险指数,用于综合考虑风险在部门间的传染。研究结果表明,实体经济部门中的主要风险集中于非金融企业,其资产和负债两端所蕴含的风险都为最大。2009年-2015年,各部门以资产负债率为代表的风险指标并未出现显著变化,资产与负债以相似的速度上升。但2015年后,各项风险指标都出现恶化,应予以充分重视,有必要继续推进结构性去杠杆。本文研究得出的市场隐含的无效资产占比,大于官方公布的规模,但并不十分夸张。研究结果还表明,当前宏观金融网络有利于部门间风险的分散,居民部门在网络中吸收了一定的风险。This paper applies a Contingent Claim Analysis(CCA) model to China’s national balance sheet data, and re-constructs a financial index of all sectors through improving the macro-financial network model with the Google PageRank algorithm. This index is then used to study financial contagion between different sectors. We find that the non-financial enterprises sector has the highest financial risk in the real sector;in particular, the asset and liability of the sector both contains the highest risk. During 2009 to 2015, the financial risk indicator represented by debt-asset ratio had not changed much in all sectors. But since 2015, all indicators are worsening, thus the structural de-leveraging should be continued. This paper concludes that the amount of invalid assets is larger than that of the official data, though not by much. This paper also finds that the macro-financial network is beneficial to dispersing financial risk because the private sector has absorbed certain risk.

关 键 词：风险传染 宏观金融网络 CCA方法 

分 类 号：F832[经济管理—金融学]