Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/60183
Title: Deriving robust bayesian premiums under bands of prior distributions with applications
Authors: Sánchez-Sánchez, M.
Sordo, M. A.
Suárez-Llorens, A.
Gómez Déniz, Emilio 
UNESCO Clasification: 1207 Investigación operativa
Keywords: Stochastic orders
Risk Measures
Reserves
Credibility
Class of priors, et al
Issue Date: 2019
Journal: ASTIN Bulletin 
Abstract: We study the propagation of uncertainty from a class of priors introduced by Arias-Nicolas et al. [(2016) Bayesian Analysis, 11(4), 1107-1136] to the premiums (both the collective and the Bayesian), for a wide family of premium principles (specifically, those that preserve the likelihood ratio order). The class under study reflects the prior uncertainty using distortion functions and fulfills some desirable requirements: elicitation is easy, the prior uncertainty can be measured by different metrics, and the range of quantities of interest is easily obtained from the extremal members of the class. We illustrate the methodology with several examples based on different claim counts models.
URI: http://hdl.handle.net/10553/60183
ISSN: 0515-0361
DOI: 10.1017/asb.2018.36
Source: Astin Bulletin [ISSN 0515-0361], v. 49 (1), p. 147-168
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