May 8, 2024
Abouzar Bazyari

Abouzar Bazyari

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

Research

Title Ruin probabilities in a discrete-time risk process with homogeneous markov chain
Type Article
Keywords
Discrete-time risk model; Homogeneous Markov chain; Ruin probability; Stationary distribution; Transition probability matrix
Journal Journal of Statistical Modelling: Theory and Applications
DOI 10.22034/jsmta.2023.19435.1080
Researchers Abouzar Bazyari (First researcher)

Abstract

The present paper considers a discrete-time risk model with a homogeneous, irreducible, and aperiodic Markov chain. The general distribution of total claim amounts is influenced by the environmental Markov chain and in the i-th period the individual claim sizes are conditionally independent. We obtain the recursive formulae for infinite time ruin probability using the technique of ordinary generating functions. In addition, we give some restrictions which under those the ruin will not happen. In the last part, we present some numerical illustrations for the results and give the prac- tical problem through a fully developed case study in the domain of social insurance.