IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v12y2019i2p70-d225342.html
   My bibliography  Save this article

Defined Contribution Pension Plans: Who Has Seen the Risk?

Author

Listed:
  • Peter A. Forsyth

    (David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
    This work was supported by the Natural Sciences and Engineering Research Council of Canada.)

  • Kenneth R. Vetzal

    (School of Accounting and Finance, University of Waterloo, Waterloo, ON N2L 3G1, Canada)

Abstract

The trend towards eliminating defined benefit (DB) pension plans in favour of defined contribution (DC) plans implies that increasing numbers of pension plan participants will bear the risk that final realized portfolio values may be insufficient to fund desired retirement cash flows. We compare the outcomes of various asset allocation strategies for a typical DC plan investor. The strategies considered include constant proportion, linear glide path, and optimal dynamic (multi-period) time consistent quadratic shortfall approaches. The last of these is based on a double exponential jump diffusion model. We determine the parameters of the model using monthly US data over a 90-year sample period. We carry out tests in a synthetic market which is based on the same jump diffusion model and also using bootstrap resampling of historical data. The probability that portfolio values at retirement will be insufficient to provide adequate retirement incomes is relatively high, unless DC investors adopt optimal allocation strategies and raise typical contribution rates. This suggests there is a looming crisis in DC plans, which requires educating DC plan holders in terms of realistic expectations, required contributions, and optimal asset allocation strategies.

Suggested Citation

  • Peter A. Forsyth & Kenneth R. Vetzal, 2019. "Defined Contribution Pension Plans: Who Has Seen the Risk?," JRFM, MDPI, vol. 12(2), pages 1-27, April.
    • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:2:p:70-:d:225342
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/12/2/70/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/12/2/70/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cui, Xiangyu & Gao, Jianjun & Li, Xun & Li, Duan, 2014. "Optimal multi-period mean–variance policy under no-shorting constraint," European Journal of Operational Research, Elsevier, vol. 234(2), pages 459-468.
    2. Brigitte C. Madrian & Dennis F. Shea, 2001. "The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(4), pages 1149-1187.
    3. Rupert, Peter & Zanella, Giulio, 2015. "Revisiting wage, earnings, and hours profiles," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 114-130.
    4. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2013. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, volume 2, number 2-b.
    5. G.M. Constantinides & M. Harris & R. M. Stulz (ed.), 2013. "Handbook of the Economics of Finance," Handbook of the Economics of Finance, Elsevier, volume 2, number 2-a.
    6. James J. Choi & David Laibson & Brigitte C. Madrian & Andrew Metrick, 2002. "Defined Contribution Pensions: Plan Rules, Participant Choices, and the Path of Least Resistance," NBER Chapters, in: Tax Policy and the Economy, Volume 16, pages 67-114, National Bureau of Economic Research, Inc.
    7. Menoncin, Francesco & Vigna, Elena, 2017. "Mean–variance target-based optimisation for defined contribution pension schemes in a stochastic framework," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 172-184.
    8. Wang, J. & Forsyth, P.A., 2011. "Continuous time mean variance asset allocation: A time-consistent strategy," European Journal of Operational Research, Elsevier, vol. 209(2), pages 184-201, March.
    9. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    10. Suleyman Basak & Georgy Chabakauri, 2010. "Dynamic Mean-Variance Asset Allocation," The Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 2970-3016, August.
    11. Elena Vigna, 2014. "On efficiency of mean--variance based portfolio selection in defined contribution pension schemes," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 237-258, February.
    12. 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.
    13. 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.
    14. Loretti Isabella Dobrescu & Xiaodong Fan & Hazel Bateman & Ben Rhodri Newell & A. Ortmann & Susan Thorp, 2018. "Retirement Savings: A Tale of Decisions and Defaults," Economic Journal, Royal Economic Society, vol. 128(610), pages 1047-1094, May.
    15. Michael E. Drew & Anup Basu & Alistair Byrnes, 2009. "Dynamic Lifecycle Strategies for Target Date Retirement Funds," Discussion Papers in Finance finance:200902, Griffith University, Department of Accounting, Finance and Economics.
    16. S. G. Kou & Hui Wang, 2004. "Option Pricing Under a Double Exponential Jump Diffusion Model," Management Science, INFORMS, vol. 50(9), pages 1178-1192, September.
    17. Duy-Minh Dang & P. A. Forsyth & K. R. Vetzal, 2017. "The 4% strategy revisited: a pre-commitment mean-variance optimal approach to wealth management," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 335-351, March.
    18. James J. Choi & David Laibson & Brigitte C. Madrian & Andrew Metrick, 2001. "Defined Contribution Pensions: Plan Rules, Participant Decisions, and the Path of Least Resistance," NBER Working Papers 8655, National Bureau of Economic Research, Inc.
    19. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    20. David E. Bloom & David Canning & Michael Moore, 2014. "Optimal Retirement with Increasing Longevity," Scandinavian Journal of Economics, Wiley Blackwell, vol. 116(3), pages 838-858, July.
    21. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1533-1570, Elsevier.
    22. Bonnie-Jeanne MacDonald & Bruce Jones & Richard Morrison & Robert Brown & Mary Hardy, 2013. "Research and Reality: A Literature Review on Drawing Down Retirement Financial Savings," North American Actuarial Journal, Taylor & Francis Journals, vol. 17(3), pages 181-215.
    23. Joao F. Cocco, 2005. "Consumption and Portfolio Choice over the Life Cycle," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 491-533.
    24. Peter A. Forsyth & Kenneth R. Vetzal, 2019. "Optimal Asset Allocation for Retirement Saving: Deterministic Vs. Time Consistent Adaptive Strategies," Applied Mathematical Finance, Taylor & Francis Journals, vol. 26(1), pages 1-37, January.
    25. Philippe Cogneau & Valeri Zakamouline, 2013. "Block bootstrap methods and the choice of stocks for the long run," Quantitative Finance, Taylor & Francis Journals, vol. 13(9), pages 1443-1457, September.
    26. Lioui, Abraham & Poncet, Patrice, 2016. "Understanding dynamic mean variance asset allocation," European Journal of Operational Research, Elsevier, vol. 254(1), pages 320-337.
    27. Giulio Zanella & Peter Rupert, 2010. "Revisiting Wage, Earnings, and Hours Profiles," 2010 Meeting Papers 1158, Society for Economic Dynamics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lars Stentoft, 2020. "Computational Finance," JRFM, MDPI, vol. 13(7), pages 1-4, July.

    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. 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.
    2. 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.
    3. Marc Chen & Mohammad Shirazi & Peter A. Forsyth & Yuying Li, 2023. "Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study," Papers 2306.10582, arXiv.org.
    4. Peter A. Forsyth, 2020. "A Stochastic Control Approach to Defined Contribution Plan Decumulation: "The Nastiest, Hardest Problem in Finance"," Papers 2008.06598, arXiv.org.
    5. 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.
    6. Peter A. Forsyth & Kenneth R. Vetzal & G. Westmacott, 2022. "Optimal performance of a tontine overlay subject to withdrawal constraints," Papers 2211.10509, arXiv.org.
    7. van Staden, Pieter M. & Dang, Duy-Minh & Forsyth, Peter A., 2021. "The surprising robustness of dynamic Mean-Variance portfolio optimization to model misspecification errors," European Journal of Operational Research, Elsevier, vol. 289(2), pages 774-792.
    8. Forsyth, Peter A., 2022. "Short term decumulation strategies for underspending retirees," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 56-74.
    9. Peter A. Forsyth & Kenneth R. Vetzal & Graham Westmacott, 2021. "Optimal control of the decumulation of a retirement portfolio with variable spending and dynamic asset allocation," Papers 2101.02760, arXiv.org.
    10. Peter A. Forsyth & Yuying Li & Kenneth R. Vetzal, 2017. "Are target date funds dinosaurs? Failure to adapt can lead to extinction," Papers 1705.00543, arXiv.org.
    11. P. A. Forsyth & K. R. Vetzal, 2017. "Robust Asset Allocation For Long-Term Target-Based Investing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    12. Peter A. Forsyth & Kenneth R. Vetzal, 2017. "Dynamic mean variance asset allocation: Tests for robustness," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 1-37, June.
    13. Pieter M. van Staden & Peter A. Forsyth & Yuying Li, 2023. "A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming," Papers 2303.08968, arXiv.org.
    14. Peter A. Forsyth & George Labahn, 2017. "$\epsilon$-Monotone Fourier Methods for Optimal Stochastic Control in Finance," Papers 1710.08450, arXiv.org, revised Apr 2018.
    15. Cong, F. & Oosterlee, C.W., 2016. "On pre-commitment aspects of a time-consistent strategy for a mean-variance investor," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 178-193.
    16. De Gennaro Aquino, Luca & Sornette, Didier & Strub, Moris S., 2023. "Portfolio selection with exploration of new investment assets," European Journal of Operational Research, Elsevier, vol. 310(2), pages 773-792.
    17. Van Staden, Pieter M. & Dang, Duy-Minh & Forsyth, Peter A., 2018. "Time-consistent mean–variance portfolio optimization: A numerical impulse control approach," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 9-28.
    18. Xiangyu Cui & Xun Li & Duan Li & Yun Shi, 2014. "Time Consistent Behavior Portfolio Policy for Dynamic Mean-Variance Formulation," Papers 1408.6070, arXiv.org, revised Aug 2015.
    19. Xiangyu Cui & Duan Li & Xun Li, 2014. "Mean-Variance Policy for Discrete-time Cone Constrained Markets: The Consistency in Efficiency and Minimum-Variance Signed Supermartingale Measure," Papers 1403.0718, arXiv.org.
    20. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.

    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:gam:jjrfmx:v:12:y:2019:i:2:p:70-:d:225342. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.