Symmetry (Jul 2023)

On a Measure of Tail Asymmetry for the Bivariate Skew-Normal Copula

  • Toshinao Yoshiba,
  • Takaaki Koike,
  • Shogo Kato

DOI
https://doi.org/10.3390/sym15071410
Journal volume & issue
Vol. 15, no. 7
p. 1410

Abstract

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Asymmetry in the upper and lower tails is an important feature in modeling bivariate distributions. This article focuses on the log ratio between the tail probabilities at upper and lower corners as a measure of tail asymmetry. Asymptotic behavior of this measure at extremely large and small thresholds is explored with particular emphasis on the skew-normal copula. Our numerical studies reveal that, when the correlation or skewness parameters are around at the boundary values, some asymptotic tail approximations of the skew-normal copulas proposed in the literature are not suitable to compute the measure of tail asymmetry with practically extremal thresholds.

Keywords