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Tail asymptotics for the bivariate skew normal

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  • Fung, Thomas
  • Seneta, Eugene

Abstract

We derive the asymptotic rate of decay to zero of the tail dependence of the bivariate skew normal distribution under the equal-skewness condition α1=α2,=α, say. The rate depends on whether α>0 or α<0. For the lower tail, the latter case has rate asymptotically identical with the bivariate normal (α=0), but has a different multiplicative constant. The case α>0 gives a rate dependent on α. The detailed asymptotic behaviour of the quantile function for the univariate skew normal is a key. This study is partly a sequel to our earlier one on the analogous situation for bivariate skew t.

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  • Fung, Thomas & Seneta, Eugene, 2016. "Tail asymptotics for the bivariate skew normal," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 129-138.
  • Handle: RePEc:eee:jmvana:v:144:y:2016:i:c:p:129-138
    DOI: 10.1016/j.jmva.2015.11.002
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    References listed on IDEAS

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    1. Loperfido, Nicola, 2002. "Statistical implications of selectively reported inferential results," Statistics & Probability Letters, Elsevier, vol. 56(1), pages 13-22, January.
    2. Fung, Thomas & Seneta, Eugene, 2010. "Tail dependence for two skew t distributions," Statistics & Probability Letters, Elsevier, vol. 80(9-10), pages 784-791, May.
    3. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," LIDAM Reprints ISBA 2011002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Fung, Thomas & Seneta, Eugene, 2014. "Convergence rate to a lower tail dependence coefficient of a skew-t distribution," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 62-72.
    5. Padoan, Simone A., 2011. "Multivariate extreme models based on underlying skew-t and skew-normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 977-991, May.
    6. Rémy Chicheportiche & Jean-Philippe Bouchaud, 2012. "The Joint Distribution Of Stock Returns Is Not Elliptical," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-23.
    7. Lysenko, Natalia & Roy, Parthanil & Waeber, Rolf, 2009. "Multivariate extremes of generalized skew-normal distributions," Statistics & Probability Letters, Elsevier, vol. 79(4), pages 525-533, February.
    8. R'emy Chicheportiche & Jean-Philippe Bouchaud, 2010. "The joint distribution of stock returns is not elliptical," Papers 1009.1100, arXiv.org, revised Jun 2012.
    9. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    10. Alexandra Ramos & Anthony Ledford, 2009. "A new class of models for bivariate joint tails," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 219-241, January.
    11. Hashorva, Enkelejd, 2010. "On the residual dependence index of elliptical distributions," Statistics & Probability Letters, Elsevier, vol. 80(13-14), pages 1070-1078, July.
    12. Antonella Capitanio, 2010. "On the approximation of the tail probability of the scalar skew-normal distribution," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 299-308.
    13. Thomas Fung & Eugene Seneta, 2010. "Tail dependence and skew distributions," Quantitative Finance, Taylor & Francis Journals, vol. 11(3), pages 327-333.
    14. Fung, Thomas & Seneta, Eugene, 2011. "The bivariate normal copula function is regularly varying," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1670-1676, November.
    15. Rémy Chicheportiche & Jean-Philippe Bouchaud, 2012. "The joint distribution of stock returns is not elliptical," Post-Print hal-00703720, HAL.
    16. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
    17. Hua, Lei & Joe, Harry, 2011. "Tail order and intermediate tail dependence of multivariate copulas," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1454-1471, November.
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    Cited by:

    1. Andréas Heinen & Alfonso Valdesogo, 2022. "The Kendall and Spearman rank correlations of the bivariate skew normal distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1669-1698, December.
    2. Fung, Thomas & Seneta, Eugene, 2021. "Tail asymptotics for the bivariate equi-skew generalized hyperbolic distribution and its Variance-Gamma special case," Statistics & Probability Letters, Elsevier, vol. 178(C).
    3. Xin Lao & Zuoxiang Peng & Saralees Nadarajah, 2023. "Tail Dependence Functions of Two Classes of Bivariate Skew Distributions," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-24, March.
    4. Hu, Shuang & Peng, Zuoxiang & Nadarajah, Saralees, 2022. "Tail dependence functions of the bivariate Hüsler–Reiss model," Statistics & Probability Letters, Elsevier, vol. 180(C).
    5. Thomas Fung & Eugene Seneta, 2018. "Quantile Function Expansion Using Regularly Varying Functions," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1091-1103, December.

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