Project CEMAPRE internal
Title | Optimal reinsurance with dependencies |
Participants | João Andrade e Silva, Alfredo Egídio dos Reis, Manuel Guerra, Alexandra Moura (Principal Investigator), Carlos Oliveira |
Summary | The project focuses on the optimal reinsurance of dependence risks, continuing the 2021 project with the title "Optimal reinsurance of dependent risks with applications". There are still many open questions regarding the optimal reinsurance problem with dependencies. Indeed, in spite being a classical field of research in Actuarial Science, only recently dependence has been considered and it is an active field of research. The interest in studying reinsurance under dependencies is still increasing, driven by the need for real, robust and reliable quantitative risk models, even though data is frequently very hard to obtain. We aim continuing studying the reinsurance problem in the presence of dependencies of the underlying risks and under general optimality criteria and general premium calculation principles. Dependencies are considered both between risks and in time. One interesting aspect of optimal reinsurance design is that in practice the insurer transfers part of each risk, independently of other risks, even if there is awareness that there may be dependences. So, the first insurer could somehow play with this fact. On the other hand, there are usually several constraints in practice that are not commonly accounted in analytical works on optimal reinsurance. One of such constraints is for instance the fact that no reinsurer will indemnify an unlimited amount of the losses. Also, real reinsurance contracts usually include type of contracts that may not be considered in fundamental works. We intend to study the optimal reinsurance problem in the presence of dependence of the underlying risks, from both an analytical fundamental point of view and an application perspective. Here, the main challenge is to obtain insurance data, namely loss data. For that reason, simulated data will be also investigated. |