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Comparing and quantifying tail dependence

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  • Siburg, Karl Friedrich
  • Strothmann, Christopher
  • Weiß, Gregor

Abstract

We introduce a new stochastic order for the tail dependence between random variables. We then study different measures of tail dependence which are monotone in the proposed order, thereby extending various known tail dependence coefficients from the literature. We apply our concepts in an empirical study where we investigate the tail dependence for different pairs of S&P 500 stocks and indices, and illustrate the advantage of our measures of tail dependence over the classical tail dependence coefficient.

Suggested Citation

  • Siburg, Karl Friedrich & Strothmann, Christopher & Weiß, Gregor, 2024. "Comparing and quantifying tail dependence," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 95-103.
    • Handle: RePEc:eee:insuma:v:118:y:2024:i:c:p:95-103
    DOI: 10.1016/j.insmatheco.2024.06.006
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    References listed on IDEAS

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    More about this item

    Keywords

    Tail dependence; Measure of dependence; Dependence modelling;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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