In the renewal risk model, several strong hypotheses may be found too restrictive to model accurately the complex evolution of the reserves of an insurance company. In the case where claim sizes are heavy-tailed, we relax the independence and stationarity assumptions and extend some asymptotic...

The present paper aims to point out how the stationary-excess operator and its iterates transform s-convex stochastic orders and the associated moment spaces. This allows us to propose a new unified method on constructing s-convex extrema for distributions that are known to be t-monotone. Both...

This note discusses a simple quasi-Monte Carlo method to evaluate numerically the ultimate ruin probability in the classical compound Poisson risk model. The key point is the Pollaczek-Khintchine representation of the non-ruin probability as a series of convolutions. Our suggestion is to...

The present paper aims to revisit the homogeneous risk model investigated by De Vylder and Goovaerts (1999, 2000). First, a claim arrival process is defined on a fixed time interval by assuming that the arrival times satisfy an order statistic property. Then, the variability and the covariance...

The Panjer (Katz) family of distributions is defined by a particular first-order recursion which is built on the basis of two parameters. It is known to characterize the Poisson, negative binomial and binomial distributions. In insurance, its main usefulness is to yield a simple recursive...

The purpose of this note is two-fold. First we derive a simple condition under which two s-convex ordered random variables must be stochastically equal, and we indicate the potential usefulness of this result in statistics. Then we highlight the relationship between the canonical moments and the...

This paper considers a Markovian epidemic process for the spread of an infectious disease with fatal risk. The model includes as extreme cases two classical models, the general epidemic (for those diseases that confer immunity after infection) and the fatal epidemic (for those diseases that lead...