基于复杂网络的我国信贷风险问题研究  

Research on the Credit Risk in China Based on the Complex Network

作　　者：张昴 聂广礼[2] 

机构地区：[1]北京大学经济学院,北京100871 [2]浙江大学宁波理工学院,浙江宁波315100

出　　处：《当代经济科学》2017年第3期32-39,共8页Modern Economic Science

基　　金：国家自然科学基金项目“基于数据挖掘-Copula理论的银行信贷中观组合管理研究”(71201143)

摘　　要：近年来,我国商业银行不良贷款率升高,信贷投放面临着行业和客户的选择困难。但是,现阶段我国仍缺乏关于行业资金投放的理论和方法。本文利用复杂网络的方法研究经济系统中行业的信贷风险,提出地位系数这一指标来衡量局部行业间投入产出网络的对称性。然后,考察地位系数与KMV模型中行业违约距离之间的负相关性,并根据宏观经济以及国家政策对低风险和高风险行业的地位系数进行对比说明。最终,提出了切实可行的政策建议。In recent years,the bad loan rate in many commercial banks of China increases. And we are faced with difficulty of sector and customer choice. However,we still lack theory of sector credit and methods now. This paper investigates credit risk in economic system using complex network method and proposes the new concept of status coefficient to measure the symmetry of local input and output network. Then we verify the negative correlation between the status coefficient and the default distance of industry by KMV model. Finally,we put forward some feasible suggestions for the commercial banks to avoid the risk of the sector.

关 键 词：信贷风险 投入产出网络 行业地位系数 KMV模型 

分 类 号：F832.4[经济管理—金融学]