银行信贷资产证券化信用风险度量及传染研究——基于修正KMV模型和MST算法的实证  

Credit Risk Measurement and Infection Research of Bank Credit Assets Securitization:Empirical Research Based on Modified KMV Model and MST Algorithm

作　　者：谢赤[1,2] 凌毓秀 XIE Chi;LINGYuxiu(Business School,Hunan University,Changsha,Hunan 410082,China;Centrr of Finance and Investment Management,Hunan Un ivers ty,Changsha,Hunan 410082,China)

机构地区：[1]湖南大学工商管理学院,湖南长沙410082 [2]湖南大学金融与投资管理研究中心,湖南长沙410082

出　　处：《财经理论与实践》2018年第3期2-8,共7页The Theory and Practice of Finance and Economics

基　　金：国家自然科学基金项目(71373072);国家自然科学基金项目(71340014)

摘　　要：精准科学地度量和描述信用风险及传染机制有利于银行信贷资产证券化的高效健康发展和货币市场系统性风险的防范。运用修正KMV模型测度银行信贷资产证券化产品在不同时期的信用风险,并采用最小生成树(MST)算法考察银行间信用风险的传染机制。结果显示:政策性银行和大型商业银行发行的产品在各个时期信用风险均处于较低水平;股份制银行、城商行和农商行发行的产品违约率前期略高于前两类银行,但后期明显下降;后三类银行位于银行股票收益率网络的中心位置,具有传递信息和维系网络稳定的重要作用。Based on the background of loan interest rate liberalization,a ccurate and scientific measurement of credit risk and description of its contagion mechanisms are conducive to the efficient and healthy development of bank credit asset securitization.Using the modified KMV model and the minimum spanning tree（MST）algorithm,the empirical research results show that the credit risk of the products issued by policy banks and large commercial banks is at a low level and the product default rates issued by joint-stock banks,city commercial banks and rural commercial banks are slightly higher than the previous two types of banks.At the same time,the latter three types of banks play an important role in transmitting information and maintaining network stability.

关 键 词：商业银行 信贷资产证券化 信用风险 修正KMV模型 最小生成树(MST) 

分 类 号：F830.91[经济管理—金融学]