Studies from Department of Statistics and Actuarial Sciences Yield New Data on Markov Processes and Related Fields (On the Moments of the Aggregate Discounted Claims With Dependence Between Inter-arrival Times)

2019 JUN 14 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Fresh data on Markov Processes and Related Fields are presented in a new report. According to news reporting out of Rabat, Morocco, by NewsRx editors, research stated, “In the classical collective insurance risk model, the independence among inter-arrival times is one of the crucial assumptions. However, in reality, one could easily identify exceptions to this assumption.”

Our news journalists obtained a quote from the research from the Department of Statistics and Actuarial Sciences, “For instance, in car insurance, if there has been a long waiting time before a claim, the next inter-arrival time can also be long, either, because the policyholders are potentially good drivers; or policyholders only start to use their cars a long time after purchasing them, then claims, would suddenly arrive more frequently after a long silence. Hence, a shorter interval before the next claim can be expected.”

According to the news editors, the research concluded: “Therefore, a natural way to relax this assumption is to introduce a dependence structure in-between inter-arrival times, and derive a recursive formula for the higher moments of the discounted aggregate renewal claims under these relaxed conditions.”

For more information on this research see: On the Moments of the Aggregate Discounted Claims With Dependence Between Inter-arrival Times. MARKOV PROCESSES AND RELATED FIELDS, 2019;25(1):149-169. MARKOV PROCESSES AND RELATED FIELDS can be contacted at: Polymat, C, O Elena Petrova, PO Box 207, Moscow, 125190, Russia.

Our news journalists report that additional information may be obtained by contacting F. Marri, Insea, Dept. of Statistics and Actuarial Sciences, Rabat, Morocco.

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