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Global stock markets risk contagion: Evidence from multilayer connectedness networks in the frequency domain

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  • Ouyang, Zisheng
  • Zhou, Xuewei
  • Lai, Yongzeng

Abstract

Multilayer connectedness networks are a promising tool for unveiling the contagion mechanism of financial risk. This paper constructs multilayer connectedness networks in the frequency domain to examine the risk contagion among global stock markets from January 4, 2006, to June 30, 2022. We analyze the global efficiency, average connectedness strength, and network density of single-layer connectedness network, and investigate the average overlap degree, network correlation coefficient and network participation coefficients of inter-layer connectedness networks. We observe that (i) the risk contagion among global stock markets shows different behaviors in the short-, medium-, and long-term, (ii) during the period of financial stress, the medium- and long-term connectedness increase significantly, while the short-term connectedness decrease significantly, and (iii) the Asian stock markets are main risk receivers, but the risks they receive are heterogeneous in frequency. Our work provides a new perspective for studying global risk contagion and supply valuable knowledge for investor and regulators.

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  • Ouyang, Zisheng & Zhou, Xuewei & Lai, Yongzeng, 2023. "Global stock markets risk contagion: Evidence from multilayer connectedness networks in the frequency domain," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823000967
    DOI: 10.1016/j.najef.2023.101973
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    Cited by:

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    3. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    4. Kaihao Liang & Shuliang Li & Wenfeng Zhang & Chaolong Zhang, 2024. "Research on Stock Market Risk Contagion of Major Debt Crises Based on Complex Network Models—The Case of Evergrande in China," Mathematics, MDPI, vol. 12(11), pages 1-13, May.
    5. U, Tony Sio-Chong & Lin, Yongjia & Wang, Yizhi, 2024. "The impact of the Russia–Ukraine war on volatility spillovers," International Review of Financial Analysis, Elsevier, vol. 93(C).
    6. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    7. Abdou, Hussein A. & Elamer, Ahmed A. & Abedin, Mohammad Zoynul & Ibrahim, Bassam A., 2024. "The impact of oil and global markets on Saudi stock market predictability: A machine learning approach," Energy Economics, Elsevier, vol. 132(C).
    8. Guo, Xiaoping & Fan, Ningyuan & Liu, Zhenchun & Wang, Jianwei, 2024. "Macro topology structure and evolution of Chinese Public Funds’ Co-holding Network," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
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    More about this item

    Keywords

    Financial risk; Frequency domain; Multilayer connectedness networks; Global stock markets;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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