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Mortality Surface by Means of Continuous Time Cohort Models

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  • Petar Jevtic
  • Elisa Luciano
  • Elena Vigna

Abstract

We study and calibrate a cohort-based model which captures the characteristics of a mortality surface with a parsimonious, continuous-time fac- tor approach. The model allows for imperfect correlation of mortality intensity across generations. It is implemented on UK data for the period 1900-2008. Calibration by means of stochastic search and the Differential Evolution opti- mization algorithm proves to yield robust and stable parameters. We provide in-sample and out-of-sample, deterministic as well as stochastic forecasts. Cal- ibration confirms that correlation across generations is smaller than one.

Suggested Citation

  • Petar Jevtic & Elisa Luciano & Elena Vigna, 2012. "Mortality Surface by Means of Continuous Time Cohort Models," Carlo Alberto Notebooks 264, Collegio Carlo Alberto, revised 2013.
    • Handle: RePEc:cca:wpaper:264
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    References listed on IDEAS

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    Cited by:

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    2. Petar Jevtić & Luca Regis, 2021. "A Square-Root Factor-Based Multi-Population Extension of the Mortality Laws," Mathematics, MDPI, vol. 9(19), pages 1-17, September.
    3. Anastasia Novokreshchenova, 2016. "Predicting Human Mortality: Quantitative Evaluation of Four Stochastic Models," Risks, MDPI, vol. 4(4), pages 1-28, December.
    4. Yang Chang & Michael Sherris, 2018. "Longevity Risk Management and the Development of a Value-Based Longevity Index," Risks, MDPI, vol. 6(1), pages 1-20, February.
    5. Wang, Ling & Chiu, Mei Choi & Wong, Hoi Ying, 2021. "Volterra mortality model: Actuarial valuation and risk management with long-range dependence," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 1-14.
    6. Hainaut, Donatien, 2022. "A calendar year mortality model in continuous time," LIDAM Discussion Papers ISBA 2022019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Milevsky, Moshe A., 2020. "Calibrating Gompertz in reverse: What is your longevity-risk-adjusted global age?," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 147-161.
    8. Paul Doukhan & Joseph Rynkiewicz & Yahia Salhi, 2021. "Optimal Neighborhood Selection for AR-ARCH Random Fields with Application to Mortality," Stats, MDPI, vol. 5(1), pages 1-26, December.
    9. Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "Mortality and Longevity Risks in the United Kingdom: Dynamic Factor Models and Copula-Functions," Working Papers 2015-03, Universitat de Barcelona, UB Riskcenter.
    10. Ling Wang & Mei Choi Chiu & Hoi Ying Wong, 2020. "Volterra mortality model: Actuarial valuation and risk management with long-range dependence," Papers 2009.09572, arXiv.org.
    11. Zhiping Huang & Michael Sherris & Andrés M. Villegas & Jonathan Ziveyi, 2022. "Modelling USA Age-Cohort Mortality: A Comparison of Multi-Factor Affine Mortality Models," Risks, MDPI, vol. 10(9), pages 1-28, September.
    12. Elisa Luciano & Luca Regis, 2012. "Demographic risk transfer: is it worth for annuity providers?," ICER Working Papers 11-2012, ICER - International Centre for Economic Research.
    13. Luca Regis, 2014. "Demographic uncertainty, the financing mix and the sustainability of welfare systems," Working Papers SWITCH 02-2014, Competitività, Regole, Mercati (CERM).
    14. 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.
    15. Man Chung Fung & Katja Ignatieva & Michael Sherris, 2015. "Managing Systematic Mortality Risk in Life Annuities: An Application of Longevity Derivatives," Papers 1508.00090, arXiv.org.
    16. Cupido, Kyran & Jevtić, Petar & Paez, Antonio, 2020. "Spatial patterns of mortality in the United States: A spatial filtering approach," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 28-38.
    17. Jevtić, Petar & Regis, Luca, 2019. "A continuous-time stochastic model for the mortality surface of multiple populations," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 181-195.
    18. Daniel H. Alai & Katja Ignatieva & Michael Sherris, 2019. "The Investigation of a Forward-Rate Mortality Framework," Risks, MDPI, vol. 7(2), pages 1-22, June.
    19. De Rosa, Clemente & Luciano, Elisa & Regis, Luca, 2021. "Geographical Diversification And Longevity Risk Mitigation In Annuity Portfolios," ASTIN Bulletin, Cambridge University Press, vol. 51(2), pages 375-410, May.
    20. Doukhan, P. & Pommeret, D. & Rynkiewicz, J. & Salhi, Y., 2017. "A class of random field memory models for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 97-110.
    21. Fadoua Zeddouk & Pierre Devolder, 2020. "Longevity Modelling and Pricing under a Dependent Multi-Cohort Framework," Risks, MDPI, vol. 8(4), pages 1-23, November.

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    More about this item

    Keywords

    stochastic mortality; age effect; cohort effect; differential evolution algorithm; mortality forecasting.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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