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Bregman superquantiles. Estimation methods and applications

Author

Listed:
  • Labopin-Richard T.

    (Institut de Mathématiques de Toulouse (CNRS UMR 5219). Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse, France)

  • Gamboa F.
  • Garivier A.
  • Iooss B.

    (FG AG and BI are with the Institut de Mathématiques de Toulouse (CNRS UMR 5219). Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse, France. BI is also with EDF R&D)

Abstract

In thiswork,we extend some parameters built on a probability distribution introduced before to the casewhere the proximity between real numbers is measured by using a Bregman divergence. This leads to the definition of the Bregman superquantile (thatwe can connect with severalworks in economy, see for example [18] or [9]). Axioms of a coherent measure of risk discussed previously (see [31] or [3]) are studied in the case of Bregman superquantile. Furthermore,we deal with asymptotic properties of aMonte Carlo estimator of the Bregman superquantile. Several numerical tests confirm the theoretical results and an application illustrates the potential interests of the Bregman superquantile.

Suggested Citation

  • Labopin-Richard T. & Gamboa F. & Garivier A. & Iooss B., 2016. "Bregman superquantiles. Estimation methods and applications," Dependence Modeling, De Gruyter, vol. 4(1), pages 1-33, March.
  • Handle: RePEc:vrs:demode:v:4:y:2016:i:1:p:33:n:4
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