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ESTIMATION OF NATURAL CATASTROPHES REINSURANCE PREMIUM USING SOME PARETO TAILED COMPOSITE MODELS
Keywords:
PC model, PH reinsurance, ML estimator, Bayesian inference, goodness-of-fit, simulationsDOI:
https://doi.org/10.17654/0972361724067Abstract
In this paper, we investigate the use of a new kind of the so-called Pareto composite (PC) model, for estimating the proportional hazard reinsurance premium, when extreme natural disasters costs are considered. The PC models allow more flexibility over the thickness of the tail. The parameters estimation problem is considered in different points of views. We study the adequacy of these models, using a Monte-Carlo procedure first, and thereafter propose an application to natural catastrophes (Nat-CAT) reinsurance premium relating to a real dataset.
Received: March 19, 2024
Revised: May 3, 2024
Accepted: May 8, 2024
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