Interconnected networks: Measuring extreme risk connectedness between China’s financial sector and real estate sector

Zisheng Ouyang and Xuewei Zhou

International Review of Financial Analysis, 2023, vol. 90, issue C

Abstract: We propose interconnected networks through the network VAR model, which can simultaneously investigate the risk connectedness of intra- and inter-layer. Using the conditional autoregressive value at risk (CAViaR) tool to measure the extreme risk of financial firms and real estate firms, we apply the proposed approach to examine the extreme risk connectedness between China’s financial sector and real estate sector. We also identify the key drivers of extreme risk spillovers between sectors by constructing the inter-sector systemic importance indicator. Our results show that isolated networks underestimate extreme risk connectedness in the financial and real estate sectors, and there are significant differences between isolated networks and interconnected networks. There are lots of extreme risk spillovers between the financial sector and the real estate sector, where the extreme risk spillover from the real estate sector to the financial sector is stronger than the reverse extreme risk spillover. According to firm-level analysis, we observe that financial firms are the main risk receivers in interconnected networks, while real estate firms are the main risk transmitters. Also, we notice that financial firms are key nodes connecting inter-sector risk spillovers. Our conclusions provide new insights into preventing and defusing systemic risks.

Keywords: Interconnected networks; Extreme risk connectedness; Financial sector; Real estate sector (search for similar items in EconPapers)
JEL-codes: C58 G21 G32 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:90:y:2023:i:c:s1057521923004088

DOI: 10.1016/j.irfa.2023.102892

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