This paper presents and applies models for the valuation and management of mortality-contingent exposures. Such exposures include insurance and pension benefits, as well as novel mortality-linked securities traded in financial markets. Unlike conventional approaches to modeling mortality, we consider the stochastic evolution of mortality projections rather than realized mortality rates. Relying on a time series of age-specific mortality forecasts, we develop a set of stochastic models that-unlike conventional mortality models-capture the evolution of mortality forecasts over the past 50 years. In particular, the dynamics of our models reflect the substantial observed variability of long-term projections and are therefore particularly well-suited for financial applications where long-term demographic uncertainty is relevant.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Management Science and Operations Research