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Asymptotics of sums of lognormal random variables with Gaussian copula

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  • Asmussen, Søren
  • Rojas-Nandayapa, Leonardo

Abstract

Let (Y1,...,Yn) have a joint n-dimensional Gaussian distribution with a general mean vector and a general covariance matrix, and let , Sn=X1+...+Xn. The asymptotics of as n-->[infinity] are shown to be the same as for the independent case with the same lognormal marginals. In particular, for identical marginals it holds that no matter what the correlation structure is.

Suggested Citation

  • Asmussen, Søren & Rojas-Nandayapa, Leonardo, 2008. "Asymptotics of sums of lognormal random variables with Gaussian copula," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2709-2714, November.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:16:p:2709-2714
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    References listed on IDEAS

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    1. Denuit, M. & Genest, C. & Marceau, E., 1999. "Stochastic bounds on sums of dependent risks," Insurance: Mathematics and Economics, Elsevier, vol. 25(1), pages 85-104, September.
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