A Monotonically Converging Algorithm for the Severity of Ruin in a Discrete Semi-Markov Risk Model

Abstract
This paper deals with the severity of ruin in a discrete semi-Markov risk model. It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is shown that the severity of ruin without initial surplus is solution of a system of equations. It can be obtained by a monotonically converging algorithm when the claims are bounded. Keywords: Probability Of Ruin, Severity Of Ruin, Recursive Calculation, Stable Algorithm, Monotonically Converging Algorithm
Volume
No. 5
Page
336-354
Year
2004
Categories
Actuarial Applications and Methodologies
Enterprise Risk Management
Processes
Analyzing/Quantifying Risks
Actuarial Applications and Methodologies
Enterprise Risk Management
Risk Categories
Financial Risks
Actuarial Applications and Methodologies
Capital Management
Capital Requirements
Financial and Statistical Methods
Aggregation Methods
Collective Risk Model
Actuarial Applications and Methodologies
Dynamic Risk Modeling
Solvency Analysis
Publications
Scandinavian Actuarial Journal
Authors
Jean-Marie Reinhard
M Snoussi