RT journal article
T1 Analysis of an aggregate loss model in a Markov renewal regime
A1 Ramírez Cobo, Josefa
A1 Carrizosa, Emilio
A1 Lillo, Rosa E.
A2 Estadística e Investigación Operativa
K1 Loss modeling
K1 Dependent losses times
K1 {Markov renewal theory; Overdispersion}
K1 Batch Markovian arrival process
K1 PH distribution
K1 double-Pareto Lognormal distribution
K1 MLE estimation
K1 Operational risk
K1 Value-at-Risk
AB In this article we consider an aggregate loss model with dependent losses. The losses occurrence process is governed by a two-state Markovian arrival process (MAP2), a Markov renewal process process that allows for (1) correlated inter-losses times,  (2) non-exponentially  distributed inter-losses times and, (3) overdisperse losses counts. Some quantities of interest to measure persistence in the loss occurrence process are obtained. Given a real operational risk database, the aggregate loss model is estimated by fitting separately the inter-losses times and severities. The MAP2 is estimated via direct maximization of the likelihood function, and severities are modeled by the heavy-tailed, double-Pareto Lognormal distribution. In comparison with the fit provided by the Poisson process, the results point out that taking into account the dependence and overdispersion in the inter-losses times distribution leads to higher capital charges.
PB Elsevier
SN 0096-3003
YR 2021
FD 2021
LK http://hdl.handle.net/10498/30386
UL http://hdl.handle.net/10498/30386
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 07-nov-2026