Analysis of an aggregate loss model in a Markov renewal regime
作者：
Highlights：
• An aggregate loss model with dependent losses is considered.
• The loss occurrence process is governed by a Markov renewal process.
• A maximum likelihood approach is examined for inference for the loss occurrence process.
• Novel descriptors to measure persistence in the loss occurrence process are obtained.
• The approach is illustrated using a real OpRisk database.
摘要
•An aggregate loss model with dependent losses is considered.•The loss occurrence process is governed by a Markov renewal process.•A maximum likelihood approach is examined for inference for the loss occurrence process.•Novel descriptors to measure persistence in the loss occurrence process are obtained.•The approach is illustrated using a real OpRisk database.
论文关键词：Loss modeling,Dependent loss times,Markov renewal theory,Overdispersion,Batch Markovian arrival process,PH distribution,Double-Pareto Lognormal distribution,MLE estimation,Operational risk,Value-at-Risk
论文评审过程：Received 3 September 2020, Revised 30 November 2020, Accepted 6 December 2020, Available online 22 December 2020, Version of Record 22 December 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125869
