Abstract
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.
Original language | English (US) |
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Pages (from-to) | 2069-2084 |
Number of pages | 16 |
Journal | Operations Research |
Volume | 70 |
Issue number | 4 |
DOIs | |
State | Published - Jul 1 2022 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Management Science and Operations Research