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Continuous-time multi-cohort mortality modelling with affine processes

Author

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  • Yajing Xu
  • Michael Sherris
  • Jonathan Ziveyi

Abstract

Continuous-time mortality models, based on affine processes, provide many advantages over discrete-time models, especially for financial applications, where such processes are commonly used for interest rate and credit risks. This paper presents a multi-cohort mortality model for age-cohort mortality rates with common factors across cohorts as well as cohort-specific factors. The mortality model is based on well-developed and used techniques from interest rate theory and has many applications including the valuation of longevity-linked products. The model has many appealing features. It is a multi-cohort model that describes the whole mortality surface, it captures cohort effects, it allows for observed imperfect correlation between different cohorts, it is shown to fit historical data at pension-related ages very well, it has closed-form expressions for survival curves and we show that it outperforms a number of other commonly used discrete-time mortality models in forecasting future survival curves.

Suggested Citation

  • Yajing Xu & Michael Sherris & Jonathan Ziveyi, 2020. "Continuous-time multi-cohort mortality modelling with affine processes," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2020(6), pages 526-552, July.
    • Handle: RePEc:taf:sactxx:v:2020:y:2020:i:6:p:526-552
    DOI: 10.1080/03461238.2019.1696223
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    Cited by:

    1. Da Fonseca, José, 2024. "Pricing guaranteed annuity options in a linear-rational Wishart mortality model," Insurance: Mathematics and Economics, Elsevier, vol. 115(C), pages 122-131.
    2. Hung-Tsung Hsiao & Chou-Wen Wang & I.-Chien Liu & Ko-Lun Kung, 2024. "Mortality improvement neural-network models with autoregressive effects," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 363-383, April.

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