Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective
Associated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dyn...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5642730 |
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| _version_ | 1832567329456652288 |
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| author | Kai Xu Jianming Mo Qian Qian Fengying Zhang Xiaofeng Xie Zongfang Zhou |
| author_facet | Kai Xu Jianming Mo Qian Qian Fengying Zhang Xiaofeng Xie Zongfang Zhou |
| author_sort | Kai Xu |
| collection | DOAJ |
| description | Associated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dynamic model to describe the associated credit risk contagion of associated credit entities based on the mean-field theory of complex networks. Firstly, this paper analyzes the stable state of the associated credit risk contagion in the associated entity network, considering the latent entities and their incubatory period. Secondly, from the perspective of complex network and considering the incubatory period, a SHIS model is built to reveal how the incubatory period influences associated credit risk contagion. Finally, the sensitivity of some parameters is analyzed in the Barabási–Albert (BA) scale-free network. The results show the following: (i) the contagion threshold of associated credit risk is related to the incubatory period of latent entities, the recovery rate and infectivity of infected entities, and the newborn rate of credit entities; (ii) the infectious rate of infected entities, the mortality rate of credit entities, and the important factors stated in (i) are all significantly correlated with the density of infected entities. |
| format | Article |
| id | doaj-art-b01755c43ed848e094ddd8e31291aeb5 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-b01755c43ed848e094ddd8e31291aeb52025-02-03T01:01:52ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/56427305642730Associated Credit Risk Contagion with Incubatory Period: A Network-Based PerspectiveKai Xu0Jianming Mo1Qian Qian2Fengying Zhang3Xiaofeng Xie4Zongfang Zhou5Business School, Chengdu University, No. 2025, Chengluo Avenue, Longquanyi District, Chengdu 610106, ChinaChinese Finance Research Institute, Southwestern University of Finance and Economics, No. 55, Guanghua Village Road, Wenjiang District, Chengdu 610074, ChinaSchool of Business, Sichuan Normal University, No. 5, Jinan Road, Jinjiang District, Chengdu 610101, ChinaWest China School of Nursing, Sichuan University, No. 37, Guoxuexiang, Wuhou District, Chengdu 610041, ChinaWest China School of Nursing/West China Hospital, Sichuan University, No. 37, Guoxuexiang, Wuhou District, Chengdu 610041, ChinaSchool of Management and Economics, University of Electronic Science and Technology of China, No. 2006, Xiyuan Avenue, High-Tech District, Chengdu 611731, ChinaAssociated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dynamic model to describe the associated credit risk contagion of associated credit entities based on the mean-field theory of complex networks. Firstly, this paper analyzes the stable state of the associated credit risk contagion in the associated entity network, considering the latent entities and their incubatory period. Secondly, from the perspective of complex network and considering the incubatory period, a SHIS model is built to reveal how the incubatory period influences associated credit risk contagion. Finally, the sensitivity of some parameters is analyzed in the Barabási–Albert (BA) scale-free network. The results show the following: (i) the contagion threshold of associated credit risk is related to the incubatory period of latent entities, the recovery rate and infectivity of infected entities, and the newborn rate of credit entities; (ii) the infectious rate of infected entities, the mortality rate of credit entities, and the important factors stated in (i) are all significantly correlated with the density of infected entities.http://dx.doi.org/10.1155/2020/5642730 |
| spellingShingle | Kai Xu Jianming Mo Qian Qian Fengying Zhang Xiaofeng Xie Zongfang Zhou Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective Complexity |
| title | Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective |
| title_full | Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective |
| title_fullStr | Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective |
| title_full_unstemmed | Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective |
| title_short | Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective |
| title_sort | associated credit risk contagion with incubatory period a network based perspective |
| url | http://dx.doi.org/10.1155/2020/5642730 |
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