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

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

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.

Suggested Citation

  • Wang, Gang-Jin & Wan, Li & Feng, Yusen & Xie, Chi & Uddin, Gazi Salah & Zhu, You, 2023. "Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:finana:v:86:y:2023:i:c:s1057521923000340
    DOI: 10.1016/j.irfa.2023.102518
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    More about this item

    Keywords

    Interconnected multilayer network; Connectedness; Stock markets; Forex markets; Volatility spillovers;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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