Dynamic credit contagion and aggregate loss in networks |
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| Institution: | 2. University of Rome Tor Vergata, Dipartimento di Economia e Finanza, Via Columbia 2, 00133 Roma, Italy;4. Università Politecnica delle Marche, School of Business Giorgio Fuà, Money and Finance Research Group (MoFiR), Piazza Martelli 8, Ancona, Italy;1. School of Finance, Nanjing Audit University, Nanjing, China;2. School of Public Administration, Hunan University, China;3. Research Institute of Digital Society and Blockchain, Hunan University, China;4. Centre for Resource and Environmental Management, Hunan University, China;5. The Energy Centre, University of Auckland, New Zealand;6. Independent Researcher, Melbourne, Australia;7. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;8. Research Center of Peaking Carbon Emissions and Carbon Neutrality, Hunan University, China;9. Business School, Hunan University, China;1. Mashang Consumer Finance Co., Ltd., Chongqing, China;2. College of Economics and Management, Southwest University, Chongqing, China;3. School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China;1. Zhejiang Normal University;2. Guangdong University of Foreign Studies, China |
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| Abstract: | We develop a dynamic model to illustrate the credit risk contagion mechanism caused by interaction between firms. Specifically, we formulate the sources of risk into idiosyncratic risk and contagion risk, and introduce recovery ability to model the scenario of a firm changing from default into normal status. Our result shows that there always exists a steady state in a network under some trivial conditions. For quasi-regular networks and bipartite networks, the expected aggregate loss remains unchanged as long as the product of the contagion probability and the partner number is fixed. |
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| Keywords: | Credit risk Networks Expected aggregate loss Dynamic contagion |
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