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A Comparative Study Of Two-Population Models For The Assessment Of Basis Risk In Longevity Hedges

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  • Villegas, Andrés M.
  • Haberman, Steven
  • Kaishev, Vladimir K.
  • Millossovich, Pietro

Abstract

Longevity swaps have been one of the major success stories of pension scheme de-risking in recent years. However, with some few exceptions, all of the transactions to date have been bespoke longevity swaps based upon the mortality experience of a portfolio of named lives. In order for this market to start to meet its true potential, solutions will ultimately be needed that provide protection for all types of members, are cost effective for large and smaller schemes, are tradable, and enable access to the wider capital markets. Index-based solutions have the potential to meet this need; however, concerns remain with these solutions. In particular, the basis risk emerging from the potential mismatch between the underlying forces of mortality for the index reference portfolio and the pension fund/annuity book being hedged is the principal issue that has, to date, prevented many schemes progressing their consideration of index-based solutions. Two-population stochastic mortality models offer an alternative to overcome this obstacle as they allow market participants to compare and project the mortality experience for the reference and target populations and thus assess the amount of demographic basis risk involved in an index-based longevity hedge. In this paper, we systematically assess the suitability of several multi-population stochastic mortality models for assessing basis risks and provide guidelines on how to use these models in practical situations paying particular attention to the data requirements for the appropriate calibration and forecasting of such models.

Suggested Citation

  • Villegas, Andrés M. & Haberman, Steven & Kaishev, Vladimir K. & Millossovich, Pietro, 2017. "A Comparative Study Of Two-Population Models For The Assessment Of Basis Risk In Longevity Hedges," ASTIN Bulletin, Cambridge University Press, vol. 47(3), pages 631-679, September.
  • Handle: RePEc:cup:astinb:v:47:y:2017:i:03:p:631-679_00
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    Cited by:

    1. Simon Schnürch & Torsten Kleinow & Ralf Korn, 2021. "Clustering-Based Extensions of the Common Age Effect Multi-Population Mortality Model," Risks, MDPI, vol. 9(3), pages 1-32, March.
    2. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    3. Bravo, Jorge M. & Ayuso, Mercedes & Holzmann, Robert & Palmer, Edward, 2021. "Addressing the life expectancy gap in pension policy," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 200-221.
    4. Selin Ozen & c{S}ule c{S}ahin, 2021. "A Two-Population Mortality Model to Assess Longevity Basis Risk," Papers 2101.06690, arXiv.org.
    5. Kallestrup-Lamb, Malene & Søgaard Laursen, Nicolai, 2024. "Longevity hedge effectiveness using socioeconomic indices," Insurance: Mathematics and Economics, Elsevier, vol. 114(C), pages 242-251.
    6. Zhou, Hongjuan & Zhou, Kenneth Q. & Li, Xianping, 2022. "Stochastic mortality dynamics driven by mixed fractional Brownian motion," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 218-238.
    7. Selin Özen & Şule Şahin, 2021. "A Two-Population Mortality Model to Assess Longevity Basis Risk," Risks, MDPI, vol. 9(2), pages 1-19, February.
    8. Massimiliano Menzietti & Maria Francesca Morabito & Manuela Stranges, 2019. "Mortality Projections for Small Populations: An Application to the Maltese Elderly," Risks, MDPI, vol. 7(2), pages 1-25, March.
    9. Zhou, Kenneth Q. & Li, Johnny Siu-Hang, 2019. "Delta-hedging longevity risk under the M7–M5 model: The impact of cohort effect uncertainty and population basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 84(C), pages 1-21.
    10. Rui Zhou & Guangyu Xing & Min Ji, 2019. "Changes of Relation in Multi-Population Mortality Dependence: An Application of Threshold VECM," Risks, MDPI, vol. 7(1), pages 1-18, February.
    11. Norkhairunnisa Redzwan & Rozita Ramli, 2022. "A Bibliometric Analysis of Research on Stochastic Mortality Modelling and Forecasting," Risks, MDPI, vol. 10(10), pages 1-17, October.
    12. Matteo Lizzi, 2024. "A Contrast-Tree-Based Approach to Two-Population Models," Risks, MDPI, vol. 12(10), pages 1-17, September.
    13. Zeddouk, Fadoua & Devolder, Pierre, 2022. "Pricing and hedging of longevity basis risk through securitization," LIDAM Discussion Papers ISBA 2022038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Giuseppe Giordano & Steven Haberman & Maria Russolillo, 2019. "Coherent modeling of mortality patterns for age-specific subgroups," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 189-204, June.
    15. Hanbali, Hamza & Dhaene, Jan & Linders, Daniël, 2022. "Dependence bounds for the difference of stop-loss payoffs on the difference of two random variables," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 22-37.
    16. Farid Flici & Frédéric Planchet, 2019. "Experience Prospective Life-Tables for the Algerian Retirees," Risks, MDPI, vol. 7(2), pages 1-21, April.
    17. Shang, Han Lin & Haberman, Steven & Xu, Ruofan, 2022. "Multi-population modelling and forecasting life-table death counts," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 239-253.
    18. Börger, Matthias & Freimann, Arne & Ruß, Jochen, 2021. "A combined analysis of hedge effectiveness and capital efficiency in longevity hedging," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 309-326.
    19. Mercedes Ayuso & Jorge M. Bravo & Robert Holzmann & Edward Palmer, 2021. "Automatic Indexation of the Pension Age to Life Expectancy: When Policy Design Matters," Risks, MDPI, vol. 9(5), pages 1-28, May.

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