IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2609.39569.html

Spouse-Protected Tontines: Household Decumulation via Neural-Network Optimization

Author

Listed:
  • Duy-Minh Dang
  • Yukan Perumal

Abstract

We develop a spouse-protected tontine in which a first death changes the household state but generates no pool transfer. The same account remains attached to the household contract until extinction and funds a spouse-only continuation phase if the retiree dies first. We derive contract-level actuarial-fairness conditions and a finite-pool mortality-credit allocation rule with exact ex post budget balance. Under a homogeneous large-pool approximation, we formulate a multidimensional decumulation problem for a representative household, with withdrawal and rebalancing controls while the retiree is alive. The objective balances expected cumulative real household payments against the Conditional Value-at-Risk (CVaR) of terminal shortfalls relative to household reserve targets, without conditioning on survival to the horizon. We develop a numerical solution method for this problem based on a global-in-time neural-network parameterization of admissible control policies. We quantify policy-induced spouse-continuation costs using expected-cost and risk-loaded payment-scale loads at both representative-contract and book levels. We characterize the large-book limit of average per-contract continuation cost as the expected representative-contract cost conditional on common market information. Numerical experiments calibrated to Australia show that the spouse-only phase is a first-order and persistent household event. In these experiments, book-level diversification removes most of the representative-contract excess upper-tail cost of spouse continuation in the large-book limit, without changing expected per-contract continuation cost. A cross-country mortality comparison indicates that the prevalence and persistence of the spouse-only phase are not specific to Australia.

Suggested Citation

  • Duy-Minh Dang & Yukan Perumal, 2026. "Spouse-Protected Tontines: Household Decumulation via Neural-Network Optimization," Papers 2609.39569, arXiv.org.
  • Handle: RePEc:arx:papers:2609.39569
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2609.39569
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andreas Hubener & Raimond Maurer & Ralph Rogalla, 2014. "Optimal Portfolio Choice with Annuities and Life Insurance for Retired Couples," Review of Finance, European Finance Association, vol. 18(1), pages 147-188.
    2. Strub, Moris S. & Li, Duan & Cui, Xiangyu & Gao, Jianjun, 2019. "Discrete-time mean-CVaR portfolio selection and time-consistency induced term structure of the CVaR," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    3. Li, Yuying & Forsyth, Peter A., 2019. "A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 189-204.
    4. Donnelly, Catherine, 2015. "Actuarial Fairness And Solidarity In Pooled Annuity Funds," ASTIN Bulletin, Cambridge University Press, vol. 45(1), pages 49-74, January.
    5. Bernhardt, Thomas & Donnelly, Catherine, 2019. "Modern tontine with bequest: Innovation in pooled annuity products," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 168-188.
    6. Hubert Dichtl & Wolfgang Drobetz & Martin Wambach, 2016. "Testing rebalancing strategies for stock-bond portfolios across different asset allocations," Applied Economics, Taylor & Francis Journals, vol. 48(9), pages 772-788, February.
    7. Donnelly, Catherine & Guillén, Montserrat & Nielsen, Jens Perch, 2014. "Bringing cost transparency to the life annuity market," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 14-27.
    8. Thomas Mathews, 2019. "A History of Australian Equities," RBA Research Discussion Papers rdp2019-04, Reserve Bank of Australia.
    9. Andrew Patton & Dimitris Politis & Halbert White, 2009. "Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White," Econometric Reviews, Taylor & Francis Journals, vol. 28(4), pages 372-375.
    10. Duy-Minh Dang & Chang Chen, 2025. "Multi-period Mean-Buffered Probability of Exceedance in Defined Contribution Portfolio Optimization," Papers 2505.22121, arXiv.org, revised Feb 2026.
    11. Sanders, Lisanne & Melenberg, Bertrand, 2016. "Estimating the joint survival probabilities of married individuals," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 88-106.
    12. Pieter M. van Staden & Peter A. Forsyth & Yuying Li, 2024. "A Global-in-Time Neural Network Approach to Dynamic Portfolio Optimization," Applied Mathematical Finance, Taylor & Francis Journals, vol. 31(3), pages 131-163, May.
    13. Forsyth, Peter A. & Vetzal, Kenneth R. & Westmacott, Graham, 2024. "Optimal performance of a tontine overlay subject to withdrawal constraints," ASTIN Bulletin, Cambridge University Press, vol. 54(1), pages 94-128, January.
    14. Thomas Bernhardt & Catherine Donnelly, 2019. "Modern tontine with bequest: innovation in pooled annuity products," Papers 1903.05990, arXiv.org.
    15. A. Max Reppen & H. Mete Soner & Valentin Tissot-Daguette, 2023. "Deep stochastic optimization in finance," Digital Finance, Springer, vol. 5(1), pages 91-111, March.
    16. German Nova Orozco & Duy-Minh Dang & Peter A. Forsyth, 2026. "Money-Back Tontines for Retirement Decumulation: Neural-Network Optimization under Systematic Longevity Risk," Papers 2602.16212, arXiv.org, revised Sep 2026.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. German Nova Orozco & Duy-Minh Dang & Peter A. Forsyth, 2026. "Money-Back Tontines for Retirement Decumulation: Neural-Network Optimization under Systematic Longevity Risk," Papers 2602.16212, arXiv.org, revised Sep 2026.
    2. Peter A. Forsyth & Kenneth R. Vetzal & G. Westmacott, 2022. "Optimal performance of a tontine overlay subject to withdrawal constraints," Papers 2211.10509, arXiv.org.
    3. Moshe A. Milevsky & Thomas S. Salisbury & Robyn Allen, 2025. "Equitable Longevity Risk Sharing or, the raison d'\^etre for a First Nations Pension Plan," Papers 2512.00122, arXiv.org.
    4. Pieter van Staden & Peter Forsyth & Yuying Li, 2024. "Smart leverage? Rethinking the role of Leveraged Exchange Traded Funds in constructing portfolios to beat a benchmark," Papers 2412.05431, arXiv.org, revised Mar 2025.
    5. Chen, An & Hieber, Peter & Rach, Manuel, 2021. "Optimal retirement products under subjective mortality beliefs," Insurance: Mathematics and Economics, Elsevier, vol. 101(PA), pages 55-69.
    6. Bégin, Jean-François & Sanders, Barbara, 2024. "Benefit volatility-targeting strategies in lifetime pension pools," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 72-94.
    7. Chang Chen & Duy-Minh Dang, 2026. "Convergence of Neural Network Policies for Risk--Reward Optimization," Papers 2603.06563, arXiv.org.
    8. Moshe A. Milevsky & Thomas S. Salisbury, 2025. "The Riccati tontine: how to satisfy regulators on average," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 50(1), pages 72-102, March.
    9. Dagpunar, John, 2021. "Closed-form solutions for an explicit modern ideal tontine with bequest motive," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 261-273.
    10. Peter A. Forsyth & Yuying Li, 2025. "Risk Measures for DC Pension Plan Decumulation," Papers 2502.16364, arXiv.org.
    11. Xie, Lin & Chen, Lv & Qian, Linyi & Li, Danping & Yang, Zhixin, 2023. "Optimal investment and consumption strategies for pooled annuity with partial information," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 129-155.
    12. Ng, Tak Wa & Nguyen, Thai, 2025. "Individual survivor fund account: The impact of bequest motives on tontine participation," Insurance: Mathematics and Economics, Elsevier, vol. 125(C).
    13. An Chen & Thai Nguyen & Thorsten Sehner, 2022. "Unit-Linked Tontine: Utility-Based Design, Pricing and Performance," Risks, MDPI, vol. 10(4), pages 1-27, April.
    14. Chendi Ni & Yuying Li & Peter A. Forsyth, 2023. "Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment," Papers 2304.05297, arXiv.org, revised May 2023.
    15. Doreen Kabuche & Michael Sherris & Andrés M. Villegas & Jonathan Ziveyi, 2025. "Return smoothing in pooled annuity products," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 48(2), pages 933-970, December.
    16. Dhaene, Jan & Milevsky, Moshe A., 2024. "Egalitarian pooling and sharing of longevity risk a.k.a. can an administrator help skin the tontine cat?," Insurance: Mathematics and Economics, Elsevier, vol. 119(C), pages 238-250.
    17. Chen, An & Guillen, Montserrat & Rach, Manuel, 2021. "Fees in tontines," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 89-106.
    18. Hieber, Peter & Lucas, Nathalie, 2020. "Life-Care Tontines," LIDAM Discussion Papers ISBA 2020026, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Forsyth, Peter A., 2020. "Optimal dynamic asset allocation for DC plan accumulation/decumulation: Ambition-CVAR," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 230-245.
    20. Ni, Chendi & Li, Yuying & Forsyth, Peter, 2025. "Optimal multi-period leverage-constrained portfolios: A neural network approach," Journal of Economic Dynamics and Control, Elsevier, vol. 177(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2609.39569. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.