Research on Evolution Process of Credit Risk Contagion Under Degree State Transition

DOI

10.2991/aebmr.k.210319.075How to use a DOI?

Keywords

State transition, open network system, credit risk infection

Abstract

This paper starts from the assumption that the credit relationship network will have a “degree transition”, that is, the underlying network is a limited dynamic, and the evolution process of credit risk contagion under the open network system with noise factors is studied. Firstly, under the assumption of dynamic network, the stochastic resonance adiabatic approximation theory is used to derive the probability of moderate change in social networks, and the non-Markov model of infection probability is constructed. Based on this, the factors such as noise intensity and evolution time are discussed. The impact and discovery of the non-linear characteristics of the credit risk contagion process under the open system, indicating that the evolution process of its contagion is the interaction of the strong interaction between the system movement process and finally through the simulation program to verify the validity of the conclusion. This paper emphasizes the significant adjustment of credit relationship in the occurrence of credit risk events. By controlling the evolution of time, the nonlinear evolution process of credit contagion is more realistic.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tianqi Wang
AU  - Yi Sun
PY  - 2021
DA  - 2021/03/22
TI  - Research on Evolution Process of Credit Risk Contagion Under Degree State Transition
BT  - Proceedings of the 6th International Conference on Financial Innovation and Economic Development (ICFIED 2021)
PB  - Atlantis Press
SP  - 402
EP  - 409
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210319.075
DO  - 10.2991/aebmr.k.210319.075
ID  - Wang2021
ER  -