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Assessing tail risk for nonlinear dependence of MSCI sector indices: A copula three-stage approach

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  • Luca, Giovanni De
  • Guégan, Dominique
  • Rivieccio, Giorgia

Abstract

The author propose a copula-based three-stage estimation technique in order to describe the serial and cross-sectional nonlinear dependence among financial multiple time series, exploring the existence of tail risk. We find out on MSCI World Sector Indices the higher performance of the approach against the classical Vector AutoRegressive models, giving the implications of misspecified assumptions for margins and/or joint distribution and providing tail dependence measures of financial variables involved in the analysis.

Suggested Citation

  • Luca, Giovanni De & Guégan, Dominique & Rivieccio, Giorgia, 2019. "Assessing tail risk for nonlinear dependence of MSCI sector indices: A copula three-stage approach," Finance Research Letters, Elsevier, vol. 30(C), pages 327-333.
    • Handle: RePEc:eee:finlet:v:30:y:2019:i:c:p:327-333
    DOI: 10.1016/j.frl.2018.10.018
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    References listed on IDEAS

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    Cited by:

    1. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    2. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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