Article2020

Multi-population mortality forecasting using tensor decomposition

Yumo Dong · Fei Huang · Honglin Yu · Steven Haberman

32 citations0/0 files storedScandinavian Actuarial Journal

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Insurance, Mortality, Demography, Risk Management Forecasting Techniques and Applications Tensor decomposition and applications

Abstract

In this paper, we formulate the multi-population mortality forecasting problem based on 3-way (age, year, and country/gender) decompositions. By applying the canonical polyadic decomposition (CPD) and the different forms of the Tucker decomposition to multi-population mortality data (10 European countries and 2 genders), we find that the out-of-sample forecasting performance is significantly improved both for individual populations and the aggregate population compared with using the single-population mortality model based on rank-1 singular value decomposition (SVD), or the Lee–Carter model. The results also shed lights on the similarity and difference of mortality among different countries. Additionally, we compare the variance-explained method and the out-of-sample validation method for rank (hyper-parameter) selection. Results show that the out-of-sample validation method is preferred for forecasting purposes.

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References

1966The Scree Test For The Number Of Factors 1825XXIV. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. In a letter to Francis Baily, Esq. F. R. S. &c 1986Comparison of five rules for determining the number of components to retain.2004Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis 1992Modeling and Forecasting U. S. Mortality 2006A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration 2006A cohort-based extension to the Lee–Carter model for mortality reduction factors 2009A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States

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