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The Bivariate Normal Copula

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  • Christian Meyer

Abstract

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.

Suggested Citation

  • Christian Meyer, 2009. "The Bivariate Normal Copula," Papers 0912.2816, arXiv.org.
    • Handle: RePEc:arx:papers:0912.2816
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    References listed on IDEAS

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    1. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
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    Cited by:

    1. Gijbels, Irène & Herrmann, Klaus, 2014. "On the distribution of sums of random variables with copula-induced dependence," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 27-44.
    2. Ernst, Philip & Pemantle, Robin & Satopää, Ville & Ungar, Lyle, 2016. "Bayesian aggregation of two forecasts in the partial information framework," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 170-180.
    3. Christoph Wunderer, 2017. "Asset correlation estimation for inhomogeneous exposure pools," Papers 1701.02028, arXiv.org, revised Sep 2019.
    4. Fabrizio Durante & Roberto Ghiselli-Ricci, 2012. "Supermigrative copulas and positive dependence," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 327-342, July.

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