Learning from historical and recent evolutions in mortality rates and life expectancy is key to produce realistic scenarios for future mortality rates, which are necessary for the valuation of the liabilities of life insurance companies and pension funds. This workshop will focus on actuarial and statistical tools to model mortality data, and the use of the constructed models for the valuation and management of life contingent risks.
We will discuss the construction and calibration of stochastic single and multi-population mortality models from annual, all-cause, population-level death counts and exposures. We cover the state-of-the-art literature and discuss the essentials of the stochastic multi-population mortality model developed (and maintained) by the Royal Dutch Actuarial Association. This model was developed via a unique partnership between industry and academia and combines insights from the evolution in mortality rates in a set of European countries on the one hand and the mortality statistics of the country of interest (e.g., the Netherlands) on the other hand. The use of the constructed model as a generator of scenarios for future mortality rates will be demonstrated. Relying on our first-hand experience, we will discuss related topics such as the biennial updates of the model, and the response to modeling challenges such as the COVID-19 shock. We will also explore mortality data in the presence of covariates or risk factors which allow us to go beyond the initial set-up of population-level mortality data.
Throughout the course, the following topics will be considered:
- basics of mortality modelling and demographics, including useful data visuals,
- single and multi-population stochastic mortality models: set-up, calibration, scenario generation; this includes the essentials of (e.g.) Lee-Carter, Li-Lee, Cairns-Blake-Dowd models and the use of time series models to project mortality rates, with special emphasis on modifications that were needed in the wake of the COVID-19 pandemic,
- the valuation of life contingent risks, reflections on longevity and mortality risk, the design of shock scenarios and the quantification of their impact
- estimating methods for mortality data collected at different levels of granularity.
Upon completion of the course the participants will:
- understand the essentials of stochastic mortality models, and have acquired insights into basic time series models and modern statistical methods for count and survival data,
- be able to apply these for the valuation of life contingent risks and the quantification of longevity risk, and
- be able to reflect on modelling challenges associated with longevity, the pros and cons of the use of different modelling strategies in this context.
Required prerequisites are an intermediate-level knowledge of probability and statistics, and/or actuarial mathematics.
This is an updated version of a workshop developed together with professor Katrien Antonio of the KU Leuven and University of Amsterdam.
Presenter
Michel Vellekoop is full professor in the Actuarial Sciences and Mathematical Finance group at the University of Amsterdam (Faculty of Economics and Business). He studied Applied Mathematics at the University of Twente and obtained his PhD. degree in 1998 at Imperial College in London for research on nonlinear filtering problems for stochastic processes. Since then, he has focused on applications in finance and insurance, both as an academic and as director of research for the Derivatives Technology Foundation. His main interests are valuation and risk management problems for contingent claims in complete as well as incomplete markets. He is the former vice-chair and current scientific advisor for the committee of the Dutch Actuarial Association which is responsible for the Dutch stochastic mortality model and projections that are published in even years. In 2022 he was one of the authors of the report for the Dutch government which defines the new model to generate economic scenarios that will be used by supervising authorities in the new Dutch pension system.
Website: https://www.uva.nl/profiel/v/e/m.h.vellekoop/m.h.vellekoop.html
More detailed information can be found in the invitation.