Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets

Gang-Jin Wang, Li Wan, Yusen Feng, Chi Xie, Gazi Uddin and You Zhu

International Review of Financial Analysis, 2023, vol. 86, issue C

Abstract: This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion.

Keywords: Interconnected multilayer network; Connectedness; Stock markets; Forex markets; Volatility spillovers (search for similar items in EconPapers)
JEL-codes: C32 F31 G15 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000340

DOI: 10.1016/j.irfa.2023.102518

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