A Continuous Granular Model for Stochastic Reserving with Individual Information

نویسندگان

چکیده

This paper works on the claims data generated by individual policies which are randomly exposed to a period of continuous time. The main aim is model occurrence times claims, as well their developments given feature information and exposure periods policies, thus project outstanding liabilities. In this paper, we also propose method compute moments liabilities in an analytic form. It significant for general insurance company more accurately risk management. well-known that features have effects projection Neglecting can unquestionably decrease prediction accuracy stochastic reserving, where measured mean square error (MSEP), whose form computed according derived parameters concerned proposed estimated based likelihood quasi-likelihood properties further studied. asymptotic behavior reserving investigated. distribution parameter estimators multivariate normal symmetric deviation loss from theoretical reserve follows distribution. confidence intervals be easily obtained through symmetry Some simulations conducted order support results.

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ژورنال

عنوان ژورنال: Symmetry

سال: 2022

ISSN: ['0865-4824', '2226-1877']

DOI: https://doi.org/10.3390/sym14081582