Dynamics Evolution of Credit Risk Contagion in the CRT Market

This work introduces a nonlinear dynamics model of credit risk contagion in the credit risk transfer (CRT) market, which contains time delay, the contagion rate of credit risk, and nonlinear resistance. The model depicts the dynamics behavior characteristics of evolution of credit risk contagion thr...

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Main Authors: Tingqiang Chen, Jianmin He, Qunyao Yin
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2013/206201
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spelling doaj-352f58edb7784967af329795c3fe54e92020-11-24T23:01:35ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2013-01-01201310.1155/2013/206201206201Dynamics Evolution of Credit Risk Contagion in the CRT MarketTingqiang Chen0Jianmin He1Qunyao Yin2School of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, ChinaSchool of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, ChinaSchool of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, ChinaThis work introduces a nonlinear dynamics model of credit risk contagion in the credit risk transfer (CRT) market, which contains time delay, the contagion rate of credit risk, and nonlinear resistance. The model depicts the dynamics behavior characteristics of evolution of credit risk contagion through numerical simulation. Meanwhile, numerical simulations show that, in the CRT market, the contagion rate of credit risk and the nonlinear resistance among CRT activities participants have some significant effects on the dynamics behaviors of evolution of credit risk contagion. Specifically, on the one hand, we find that the status curve of credit risk contagion that causes some significant changes with the increase in the contagion rate of credit risk, moreover, emerges a series of Hopf bifurcation and chaotic phenomena in the process of credit risk contagion. On the other hand, Hopf bifurcation and chaotic phenomena appear in advance with the increase in the nonlinear resistance coefficient and time-delay. In addition, there are a series of periodic windows in the chaotic interval inside, including Hopf bifurcation, inverse bifurcation, and chaos.http://dx.doi.org/10.1155/2013/206201
collection DOAJ
language English
format Article
sources DOAJ
author Tingqiang Chen
Jianmin He
Qunyao Yin
spellingShingle Tingqiang Chen
Jianmin He
Qunyao Yin
Dynamics Evolution of Credit Risk Contagion in the CRT Market
Discrete Dynamics in Nature and Society
author_facet Tingqiang Chen
Jianmin He
Qunyao Yin
author_sort Tingqiang Chen
title Dynamics Evolution of Credit Risk Contagion in the CRT Market
title_short Dynamics Evolution of Credit Risk Contagion in the CRT Market
title_full Dynamics Evolution of Credit Risk Contagion in the CRT Market
title_fullStr Dynamics Evolution of Credit Risk Contagion in the CRT Market
title_full_unstemmed Dynamics Evolution of Credit Risk Contagion in the CRT Market
title_sort dynamics evolution of credit risk contagion in the crt market
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2013-01-01
description This work introduces a nonlinear dynamics model of credit risk contagion in the credit risk transfer (CRT) market, which contains time delay, the contagion rate of credit risk, and nonlinear resistance. The model depicts the dynamics behavior characteristics of evolution of credit risk contagion through numerical simulation. Meanwhile, numerical simulations show that, in the CRT market, the contagion rate of credit risk and the nonlinear resistance among CRT activities participants have some significant effects on the dynamics behaviors of evolution of credit risk contagion. Specifically, on the one hand, we find that the status curve of credit risk contagion that causes some significant changes with the increase in the contagion rate of credit risk, moreover, emerges a series of Hopf bifurcation and chaotic phenomena in the process of credit risk contagion. On the other hand, Hopf bifurcation and chaotic phenomena appear in advance with the increase in the nonlinear resistance coefficient and time-delay. In addition, there are a series of periodic windows in the chaotic interval inside, including Hopf bifurcation, inverse bifurcation, and chaos.
url http://dx.doi.org/10.1155/2013/206201
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AT jianminhe dynamicsevolutionofcreditriskcontagioninthecrtmarket
AT qunyaoyin dynamicsevolutionofcreditriskcontagioninthecrtmarket
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