We present a new model of loss processes in insurance. The process is a couple (N,L) where N is a univariate Markov-modulated Poisson process (MMPP) and L is a multivariate loss process whose behavior is driven by N. We prove the strong consistency of the maximum likelihood estimator of the...

For a risk variable X and a normalized Young function φ(⋅), the Haezendonck–Goovaerts risk measure for X at level q∈(0,1) is defined as Hq[X]=infx∈R(x+h), where h solves the equation E[φ((X−x)+/h)]=1−q if Pr(Xx)0 or is 0 otherwise. In a recent work, we implemented an asymptotic...

In this paper, we are interested in the calculation of the Haezendonck–Goovaerts risk measure, which is defined via a convex Young function and a parameter q∈(0,1) representing the confidence level. We mainly focus on the case in which the risk variable follows a distribution function from a...

In this paper, we show a characterization of upper comonotonicity via tail convex order. For any given marginal distributions, a maximal random vector with respect to tail convex order is proved to be upper comonotonic under suitable conditions. As an application, we consider the computation of...