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Stochastic representation of FGM copulas using multivariate Bernoulli random variables

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  • Blier-Wong, Christopher
  • Cossette, Hélène
  • Marceau, Etienne

Abstract

A one-to-one correspondence between Fréchet's class of multivariate Bernoulli distribution with symmetric marginals and the well-known family of Farlie-Gumbel-Morgenstern (FGM) copulas is established. A new stochastic representation of the family of d-variate FGM copulas is introduced. The representation is bijective: from any d-variate Bernoulli distribution, one may define a corresponding d-variate FGM copula; and for any d-variate FGM copula, one finds the corresponding d-variate Bernoulli distribution. The proposed stochastic representation has many advantages, notably establishing stochastic orders, constructing subclasses of FGM copulas and sampling. In particular, one may use the stochastic representation to develop computational methods to perform sampling from subclasses of FGM copulas, which scale well to large dimensions.

Suggested Citation

  • Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2022. "Stochastic representation of FGM copulas using multivariate Bernoulli random variables," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:csdana:v:173:y:2022:i:c:s016794732200086x
    DOI: 10.1016/j.csda.2022.107506
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    References listed on IDEAS

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    Cited by:

    1. H'el`ene Cossette & Etienne Marceau & Alessandro Mutti & Patrizia Semeraro, 2024. "Generalized FGM dependence: Geometrical representation and convex bounds on sums," Papers 2406.10648, arXiv.org, revised Oct 2024.
    2. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2023. "Risk aggregation with FGM copulas," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 102-120.

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