Conditional tail moment and reinsurance premium estimation under random right censoring

• Yuri Goegebeur ^[1] ; Armelle Guillou ^[2] ; Jing Qin ^[1]
  1. [1] University of Southern Denmark

     University of Southern Denmark

     Dinamarca

     
  2. [2] Université de Strasbourg et CNRS
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 33, Nº. 1, 2024, págs. 230-250
• Idioma: inglés
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• Resumen

  • We propose an estimator of the conditional tail moment (CTM) when the data are subject to random censorship. The variable of main interest and the censoring variable both follow a Pareto-type distribution. We establish the asymptotic properties of our estimator and discuss bias-reduction. Then, the CTM is used to estimate, in case of censorship, the premium principle for excess-of-loss reinsurance. The finite sample properties of the proposed estimators are investigated with a simulation study and we illustrate their practical applicability on a dataset of motor third party liability insurance.