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Tweedie dominance for autocalibrated predictors and Laplace transform order

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  • Denuit, Michel

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Huyghe, Julie

    (Université Libre de Bruxelles)

  • Simon, Pierre-Alexandre

    (Université Libre de Bruxelles)

  • Trufin, Julien

    (Université Libre de Bruxelles)

Abstract

While Krüger and Ziegel [(2021). Generic conditions for forecast dominance. Journal of Business & Economic Statistics, 39(4), 972–983.] defined forecast dominance, or Bregman dominance as dominance for every Bregman loss function, this paper explores Tweedie dominance proposed by Denuit et al. [(2021). Autocalibration and Tweedie dominance for insurance pricing with machine learning. Insurance: Mathematics and Economics, 101, 485–497.] to compare competing candidate premiums. A necessary and sufficient condition is established under autocalibration. Moreover, Laplace transform order turns out to be a sufficient condition for Tweedie dominance between autocalibrated predictors. This shows that Tweedie dominance is a rather weak concept compared to Bregman dominance that reduces to the well-known convex order among autocalibrated predictors.

Suggested Citation

  • Denuit, Michel & Huyghe, Julie & Simon, Pierre-Alexandre & Trufin, Julien, 2026. "Tweedie dominance for autocalibrated predictors and Laplace transform order," LIDAM Reprints ISBA 2026025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2026025
    DOI: https://doi.org/10.1080/03461238.2025.2557295
    Note: In: Scandinavian Actuarial Journal, 2026, vol. 2026(6), p. 569-583
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