中国管理科学 ›› 2023, Vol. 31 ›› Issue (4): 260-274.doi: 10.16381/j.cnki.issn1003-207x.2021.0794
陈庭强1, 2, 王杰朋1, 杨晓光2
收稿日期:
2021-04-22
修回日期:
2022-08-05
出版日期:
2023-04-20
发布日期:
2023-05-06
通讯作者:
陈庭强(1983-),男,河南信阳人,教授、博士生导师、博士后,研究方向:金融风险管理;王杰朋(1994-),男,浙江温州人,博士研究生,研究方向:金融风险管理。杨晓光(1964-),男(汉族),安徽凤台人,中国科学院数学与系统科学研究院系统科学研究所,副所长,中国科学院大学经济与管理学院,教授,博士生导师,研究方向:金融风险管理、宏观经济分析、复杂网络、博弈论,Email:xgyang@iss.ac.cn.
E-mail:xgyang@iss.ac.cn
基金资助:
CHEN Ting-qiang1, 2, WANG Jie-peng1, YANG Xiao-guang2
Received:
2021-04-22
Revised:
2022-08-05
Online:
2023-04-20
Published:
2023-05-06
Contact:
陈庭强
E-mail:xgyang@iss.ac.cn
摘要: 信用衍生品具有投资交易和风险管理双重功能,其投资交易行为势必会带来信用风险转移(CRT)市场信用风险的传染。考虑到CRT市场交易对手的潜伏违约状态与交易对手异质性,构造了单层网络下交易对手信用风险传染模型和双层耦合网络下交易对手信用风险传染模型。运用计算实验及仿真模拟计算分析双层耦合网络下CRT市场交易对手信用风险传染行为特征及演化规律,得到了如下主要结论:(1)在单层网络模型中,机制概率具有“全局效应”。(2)CRT市场交易对手异质性对交易对手信用风险传染具有“全局强化”作用,即随着交易对手信用风险偏好程度增大,交易对手信用风险认知水平降低,信息披露系数减小,交易对手杠杆水平升高,交易对手风险平溢能力降低以及交易对手影响力增大,交易对手信用风险传染加剧。(3)双层耦合网络的违约交易对手规模在网络稳态时明显大于单层网络。而且,在传染过程中,单层网络的CRT市场交易对手信用风险传染更快到达网络稳态。(4)在双层耦合网络中,交易对手信用风险传染的三种层间连接模式中,同配连接具有“全局强化”效应,而易配连接具有“全局抑制”效应。(5)在双层耦合网络模型中,层内感染概率和层间感染概率促使潜伏违约状态交易对手朝着违约状态交易对手转化,具有全局强化信用风险传染的作用;层内免疫概率和层间免疫概率促使违约状态交易对手朝着其他状态交易对手转化,具有全局抑制信用风险传染的作用。
中图分类号:
陈庭强, 王杰朋, 杨晓光. 双层耦合网络下CRT市场交易对手信用风险传染演化模型研究[J]. 中国管理科学, 2023, 31(4): 260-274.
CHEN Ting-qiang, WANG Jie-peng, YANG Xiao-guang. Bilayer-Coupled Network Evolution Model of Counterparty Credit Risk Contagion in the CRT Market[J]. Chinese Journal of Management Science, 2023, 31(4): 260-274.
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