Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets
International Review of Financial Analysis
; 86, 2023.
Article
in English
| Scopus | ID: covidwho-2179814
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. © 2023 Elsevier Inc.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
International Review of Financial Analysis
Year:
2023
Document Type:
Article
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