Application of Relational Models in Mortality Immunization

The prediction of future mortality rates by any existing mortality projection models is hardly tobe exact, which causes an exposure to mortality and longevity risks for life insurance companies.Since a change in mortality rates has opposite impacts on the surpluses of life insurance andannuity products, hedging strategies of mortality and longevity risks can be implemented bycreating an insurance portfolio of both life insurance and annuity products. In this project, wedevelop a framework of implementing non-size free matching strategies to hedge against mortalityand longevity risks. We apply relational models to capture the mortality movements byassuming that the simulated mortality sequence is a proportional and/or a constant change ofthe expected one, and the amount of the changes varies in the length of the sequence. Withthe magnitude of the proportional and/or constant changes, we determine the optimal weightsof allocating the life insurance and annuity products in a portfolio for mortality immunizationaccording to each of the proposed matching strategies. Comparing the hedging performanceof non-size free matching strategies with size free ones proposed by Lin and Tsai (2014), wedemonstrate that non-size free matching strategies can hedge against mortality and longevityrisks more effectively than the corresponding size free ones.