A Hybrid Fuzzy Regression Model for Optimal Loss Reserving in Insurance
Methodology
2018-06-20 v1
Abstract
In this article, a Hybrid Fuzzy Regression Model with Asymmetric Triangular Fuzzy Coefficients and optimized value in Generalized Linear Models (GLM) framework have been developed. The weighted functions of Fuzzy Numbers rather than the Expected value of Fuzzy Number is used as a defuzzification procedure. We perform the new model on a numerical data (Taylor and Ashe, 1983) to predict incremental payments in loss reserving. We prove that the new Hybrid Model with the optimized value produce better results than the classical GLM according to the Reserve Prediction Error and Reserve Standard Deviation.
Keywords
Cite
@article{arxiv.1806.06853,
title = {A Hybrid Fuzzy Regression Model for Optimal Loss Reserving in Insurance},
author = {Woundjiagué Apollinaire and Mbele Bidima Martin Le Doux and Waweru Mwangi Ronald},
journal= {arXiv preprint arXiv:1806.06853},
year = {2018}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1806.04530