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NetVIX - A Network Volatility Index of Financial Markets

Author

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  • Daniel Felix Ahelegbey

    (University of Pavia)

  • Paolo Giudici

    (University of Pavia)

Abstract

We construct a network volatility index (NetVIX) via market interconnectedness and volatilities to measure global market turbulence. The NetVIX multiplicatively decomposes into an average volatility and a network amplifier index. It also additively decomposes into marginal volatility indices for measuring individual contribution to global turmoil. We apply our measure to study the relationship between the interconnectedness among 20 major stock markets and global market risks over the last two decades. The NetVIX is shown to be a novel approach to measuring global market risk, and an alternative to the VIX. The result shows that during crisis periods, particularly the tech-bubble, sub-prime, and COVID-19 pandemic, the interconnectedness of the markets amplifies average market risk more than 700 percent to cause a global meltdown. We find evidence that the highest risk-contributing markets to global meltdown are the US, Brazil, Hong Kong, France, and Germany.

Suggested Citation

  • Daniel Felix Ahelegbey & Paolo Giudici, 2020. "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series 192, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:demwp0192
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    References listed on IDEAS

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    Cited by:

    1. Palomba, Giulio & Tedeschi, Marco, 2024. "Contagion among European financial indices, evidence from a quantile VAR approach," Economic Systems, Elsevier, vol. 48(2).
    2. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    3. Celani, Alessandro & Cerchiello, Paola & Pagnottoni, Paolo, 2024. "The topological structure of panel variance decomposition networks," Journal of Financial Stability, Elsevier, vol. 71(C).
    4. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    5. Zheng, Yanting & Luan, Xin & Lu, Xin & Liu, Jiaming, 2023. "A new view of risk contagion by decomposition of dependence structure: Empirical analysis of Sino-US stock markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    6. Ahelegbey, Daniel Felix & Celani, Alessandro & Cerchiello, Paola, 2024. "Measuring the impact of the EU health emergency response authority on the economic sectors and the public sentiment," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    7. Lv, Jiamin & Ben, Shenglin & Huang, Wenli & Xu, Yueling, 2023. "How to reduce the default contagion risk of intercorporate credit guarantee networks? Evidence from China," Emerging Markets Review, Elsevier, vol. 55(C).

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    More about this item

    Keywords

    Centrality; COVID-19; Financial Crises; NetVIX; Turbulence; VAR; VIX;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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