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Topological properties of reconstructed credit networks and banking systemic risk |
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| Institution: | 1. School of Finance, Nanjing Agricultural University, Weigang 1#, Nanjing 210095, PR China;2. School of Economics and Management, Southeast University, Sipailou 2#, Nanjing 210096, PR China;1. Department of Finance and Accounting, University of Tunis El Manar and IFGT, Tunis, Tunisia;2. Department of Economics and Finance, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman;3. ISEG – Lisbon School of Economics and Management, SOCIUS/CSG – Research in Social Sciences and Management, Universidade de Lisboa, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal;4. HSE University, Pokrovsky Blv. 11, 109028 Moscow, Russian Federation;5. PNU Business School, Pusan National University, Busan, South Korea;1. School of Economics, Jinan University, Guangzhou 510630, China;2. School of Business Administration, South China University of Technology, Guangzhou 510640, China;1. Research Institute on Sustainable Economic Growth (IRCrES), National Research Council of Italy (CNR), Moncalieri, TO, Italy;2. Faculty of Business Administration and Economics, Bielefeld University, Bielefeld, NRW, Germany |
| Abstract: | Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure. |
| Keywords: | Network reconstruction Systemic risk Bipartite credit network Fire sales |
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