May 9, 2024
Abouzar Bazyari

Abouzar Bazyari

Academic Rank: Assistant professor
Address:
Degree: Ph.D in -
Phone: -
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title Analysis of a Dependent Perturbed Renewal Risk Model with Heavy-tailed Distributions
Type Article
Keywords
Boole’s inequality, Farlie–Gumbel–Morgenstern copula, heavy-tailed distribution, renewal risk model, ruin probability.
Journal Lobachevskii Journal of Mathematics
DOI https://doi.org/10.1134/S1995080223110057
Researchers Abouzar Bazyari (First researcher)

Abstract

This paper considers a delayed claim risk model with constant interest rate when there is a dependence structure between the delayed claim and claim amount. We will incorporate the heavy-tailed distributions into the perturbed renewal risk model and obtain the uniform asymptotic estimate for the probability that an insurance portfolio gets ruined within a finite time period using some probability inequalities and mathematical approaches. Moreover, two numerical examples via Monte carlo simulation methods are presented to illustrate the effectiveness of results when the claim amount and delayed claim are dependent according to the Farlie–Gumbel–Morgenstern copula for Pareto and Lognormal distributions.