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基于Markov-vine copula的我国网贷平台对传统金融机构风险传染效应研究
引用本文:韦起,魏云捷.基于Markov-vine copula的我国网贷平台对传统金融机构风险传染效应研究[J].系统工程理论与实践,2018,38(2):317-328.
作者姓名:韦起  魏云捷
作者单位:1. 长城资产管理股份有限公司, 北京 100045;2. 中国科学院 预测科学研究中心, 北京 100190;3. 中国科学院 数学与系统科学研究院, 北京 100190
基金项目:国家自然科学基金(71390330,71390331)
摘    要:近年来,网络借贷发展迅速,并且随着互联网技术的运用和网络借贷自身所蕴含的独特风险方式,使得其局部风险更容易蔓延至整个网贷市场,有可能会迅速波及,传染到其他类型的金融市场.本文将Markov区制转换模型和vine copula相结合,用来研究我国网络借贷平台对传统金融机构的动态风险传染效应.研究结果表明:我国网络借贷平台和相应的传统金融机构在不同阶段呈现出不同的"杠杆效应";我国网络借贷平台以及相关的传统金融机构均具有较为明显的区制转换特征;比较三个阶段的情况,网络借贷平台对商业银行的风险传染效应要大于其他的传统金融机构,其次是网络借贷平台对信托业的风险传染效应;在各阶段,网络借贷平台对传统金融机构的风险传染效应不对称,下尾相关系数基本大于上尾相关系数.

关 键 词:网络借贷平台  风险传染效应  Markov区制转换  藤copula  
收稿时间:2017-08-28

An empirical study of contagion effect from the Internet lending platform of China to the traditional financial institutions based on Markov-vine copula
WEI Qi,WEI Yunjie.An empirical study of contagion effect from the Internet lending platform of China to the traditional financial institutions based on Markov-vine copula[J].Systems Engineering —Theory & Practice,2018,38(2):317-328.
Authors:WEI Qi  WEI Yunjie
Institution:1. China Great Wall Asset Management Corporation, Beijing 100045, China;2. Center for Forecasting Science, Chinese Academy of Sciences, Beijing 100190, China;3. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
Abstract:In recent years, the Internet lending platform has developed rapidly. Due to the development of the Internet technology and the characters of the Internet lending platform, the regional risk can be spread to the entire lending market much easier. The risk even could rapidly contagion to the traditional financial markets. This paper utilizes the Markov regime switching model and the vine copula to analyse the contagion effect from China's Internet lending platform to the traditional financial institutions. The empirical results indicate:China's Internet lending platform and the traditional financial institutions show different "leverage effects" at different stages; China's Internet lending platform and the associated traditional financial institutions have an obvious characteristic of regime switching; compared with the situation of the three periods, the contagion effect of the Internet lending platform to the commercial banks is the largest, followed by trust industry risk; the contagion effect of the Internet lending platform to the traditional financial institutions is asymmetric at each period and the correlation coefficient of the lower tail is basically greater than that of the upper tail.
Keywords:Internet lending platform  contagion effect  Markov regime switching  vine copula  
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