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Mean-variance optimization problems for an accumulation phase in a defined benefit plan

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  • Delong, Lukasz
  • Gerrard, Russell
  • Haberman, Steven

Abstract

In this paper we deal with contribution rate and asset allocation strategies in a pre-retirement accumulation phase. We consider a single cohort of workers and investigate a retirement plan of a defined benefit type in which an accumulated fund is converted into a life annuity. Due to the random evolution of a mortality intensity, the future price of an annuity, and as a result, the liability of the fund, is uncertain. A manager has control over a contribution rate and an investment strategy and is concerned with covering the random claim. We consider two mean-variance optimization problems, which are quadratic control problems with an additional constraint on the expected value of the terminal surplus of the fund. This functional objectives can be related to the well-established financial theory of claim hedging. The financial market consists of a risk-free asset with a constant force of interest and a risky asset whose price is driven by a Lévy noise, whereas the evolution of a mortality intensity is described by a stochastic differential equation driven by a Brownian motion. Techniques from the stochastic control theory are applied in order to find optimal strategies.

Suggested Citation

  • Delong, Lukasz & Gerrard, Russell & Haberman, Steven, 2008. "Mean-variance optimization problems for an accumulation phase in a defined benefit plan," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 107-118, February.
    • Handle: RePEc:eee:insuma:v:42:y:2008:i:1:p:107-118
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    References listed on IDEAS

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    Cited by:

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    3. Xiaoyi Zhang, 2022. "Optimal DC Pension Management Under Inflation Risk With Jump Diffusion Price Index and Cost of Living Process," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 1253-1270, June.
    4. Yao, Haixiang & Yang, Zhou & Chen, Ping, 2013. "Markowitz’s mean–variance defined contribution pension fund management under inflation: A continuous-time model," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 851-863.
    5. Yao, Haixiang & Chen, Ping & Li, Xun, 2016. "Multi-period defined contribution pension funds investment management with regime-switching and mortality risk," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 103-113.
    6. Josa-Fombellida, Ricardo & Rincón-Zapatero, Juan Pablo, 2019. "Equilibrium strategies in a defined benefit pension plan game," European Journal of Operational Research, Elsevier, vol. 275(1), pages 374-386.
    7. Yao, Haixiang & Lai, Yongzeng & Ma, Qinghua & Jian, Minjie, 2014. "Asset allocation for a DC pension fund with stochastic income and mortality risk: A multi-period mean–variance framework," Insurance: Mathematics and Economics, Elsevier, vol. 54(C), pages 84-92.
    8. Luciano, Elisa & Regis, Luca, 2014. "Efficient versus inefficient hedging strategies in the presence of financial and longevity (value at) risk," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 68-77.
    9. Wujun Lv & Linlin Tian & Xiaoyi Zhang, 2023. "Optimal Defined Contribution Pension Management with Jump Diffusions and Common Shock Dependence," Mathematics, MDPI, vol. 11(13), pages 1-20, July.
    10. Schmeck, Maren Diane & Schmidli, Hanspeter, 2019. "Mortality Options: the Point of View of an Insurer," Center for Mathematical Economics Working Papers 616, Center for Mathematical Economics, Bielefeld University.
    11. Dang, D.M. & Forsyth, P.A., 2016. "Better than pre-commitment mean-variance portfolio allocation strategies: A semi-self-financing Hamilton–Jacobi–Bellman equation approach," European Journal of Operational Research, Elsevier, vol. 250(3), pages 827-841.
    12. Schmeck, Maren Diane & Schmidli, Hanspeter, 2021. "Mortality options: The point of view of an insurer," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 98-115.
    13. Josa-Fombellida, Ricardo & López-Casado, Paula & Rincón-Zapatero, Juan Pablo, 2018. "Portfolio optimization in a defined benefit pension plan where the risky assets are processes with constant elasticity of variance," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 73-86.
    14. Ai, Jing & Brockett, Patrick L. & Jacobson, Allen F., 2015. "A new defined benefit pension risk measurement methodology," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 40-51.
    15. Menoncin, Francesco & Regis, Luca, 2017. "Longevity-linked assets and pre-retirement consumption/portfolio decisions," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 75-86.
    16. Lin, Yijia & MacMinn, Richard D. & Tian, Ruilin, 2015. "De-risking defined benefit plans," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 52-65.
    17. Huang, Hong-Chih & Lee, Yung-Tsung, 2020. "A study of the differences among representative investment strategies," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 131-149.
    18. Francesco Menoncin & Luca Regis, 2015. "Longevity assets and pre-retirement consumption/portfolio decisions," Working Papers 2/2015, IMT School for Advanced Studies Lucca, revised May 2015.
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    20. Samuel H. Cox & Yijia Lin & Ruilin Tian & Jifeng Yu, 2013. "Managing Capital Market and Longevity Risks in a Defined Benefit Pension Plan," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(3), pages 585-620, September.

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