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Network topology and systemic risk: Evidence from the Euro Stoxx market

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  • Li, Wenwei
  • Hommel, Ulrich
  • Paterlini, Sandra

Abstract

This study investigates the network topology of equity volatilities. We propose a novel approach to model the interdependencies of the Euro Stoxx companies by constructing the minimum spanning tree with the upper tail dependence coefficient of the equity volatility. The empirical results demonstrate the usefulness of the network topology for the detection of systemic risk in high-volatility environments. More specifically, during crisis periods, the topology of the minimum spanning tree becomes more star-like and compact, accompanied by stronger rich-club effects. Such a network configuration is known to be less resilient to shock and more prone to systemic risk.

Suggested Citation

  • Li, Wenwei & Hommel, Ulrich & Paterlini, Sandra, 2018. "Network topology and systemic risk: Evidence from the Euro Stoxx market," Finance Research Letters, Elsevier, vol. 27(C), pages 105-112.
    • Handle: RePEc:eee:finlet:v:27:y:2018:i:c:p:105-112
    DOI: 10.1016/j.frl.2018.02.016
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    Citations

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    Cited by:

    1. Liu, Shaowen & Caporin, Massimiliano & Paterlini, Sandra, 2021. "Dynamic network analysis of North American financial institutions," Finance Research Letters, Elsevier, vol. 42(C).
    2. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    3. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    4. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    5. Yang, Xin & Wen, Shigang & Zhao, Xian & Huang, Chuangxia, 2020. "Systemic importance of financial institutions: A complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Νikolaos A. Kyriazis, 2021. "Investigating the nexus between European major and sectoral stock indices, gold and oil during the COVID-19 pandemic," SN Business & Economics, Springer, vol. 1(4), pages 1-12, April.
    7. Huang, Wei-Qiang & Wang, Dan, 2020. "Financial network linkages to predict economic output," Finance Research Letters, Elsevier, vol. 33(C).
    8. Wang, Dan & Huang, Wei-Qiang, 2021. "Centrality-based measures of financial institutions’ systemic importance: A tail dependence network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    9. Fang, Ming & Taylor, Stephen & Uddin, Ajim, 2022. "The network structure of overnight index swap rates," Finance Research Letters, Elsevier, vol. 46(PB).

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    More about this item

    Keywords

    Systemic risk; Copula; Tail dependence; Minimum spanning tree;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance

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