IDEAS home Printed from https://ideas.repec.org/p/yor/yorken/16-11.html
   My bibliography  Save this paper

Reducing sequence risk using trend following investment strategies and the CAPE

Author

Listed:
  • Andrew Clare
  • James Seaton
  • Peter N. Smith
  • Stephen Thomas

Abstract

Sequence risk is a poorly understood, but crucial aspect of the risk faced by many investors. Using US equity data from 1872-2015 we apply the concept of Perfect Withdrawal Rates to show how this risk can be significantly reduced by applying simple, trend following investment strategies. We also show that knowing the CAPE ratio at the beginning of a decumulation period is useful for predicting and enhancing the sustainable withdrawal rate.

Suggested Citation

  • Andrew Clare & James Seaton & Peter N. Smith & Stephen Thomas, 2016. "Reducing sequence risk using trend following investment strategies and the CAPE," Discussion Papers 16/11, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:16/11
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/discussionpapers/2016/1611.pdf
    File Function: Main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clare, Andrew & Seaton, James & Smith, Peter N. & Thomas, Stephen, 2016. "The trend is our friend: Risk parity, momentum and trend following in global asset allocation," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 63-80.
    2. Gerrard, Russell & Haberman, Steven & Vigna, Elena, 2004. "Optimal investment choices post-retirement in a defined contribution pension scheme," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 321-342, October.
    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. Di Giacinto, Marina & Federico, Salvatore & Gozzi, Fausto & Vigna, Elena, 2014. "Income drawdown option with minimum guarantee," European Journal of Operational Research, Elsevier, vol. 234(3), pages 610-624.
    2. Yang Wang & Xiao Xu & Jizhou Zhang, 2021. "Optimal Investment Strategy for DC Pension Plan with Stochastic Income and Inflation Risk under the Ornstein–Uhlenbeck Model," Mathematics, MDPI, vol. 9(15), pages 1-15, July.
    3. Horneff, Wolfram J. & Maurer, Raimond H. & Mitchell, Olivia S. & Stamos, Michael Z., 2009. "Asset allocation and location over the life cycle with investment-linked survival-contingent payouts," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1688-1699, September.
    4. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, March.
    5. Alessandra Milazzo & Elena Vigna, 2018. "The Italian Pension Gap: a Stochastic Optimal Control Approach," Carlo Alberto Notebooks 553, Collegio Carlo Alberto.
    6. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    7. Marina Di Giacinto & Bjarne Højgaard & Elena Vigna, 2010. "Optimal time of annuitization in the decumulation phase of a defined contribution pension scheme," Working Papers 2010-08, Universita' di Cassino, Dipartimento di Economia e Giurisprudenza.
    8. Wang, J. & Forsyth, P.A., 2010. "Numerical solution of the Hamilton-Jacobi-Bellman formulation for continuous time mean variance asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 207-230, February.
    9. Denis S. Grebenkov & Jeremy Serror, 2014. "Optimal Allocation of Trend Following Strategies," Papers 1410.8409, arXiv.org.
    10. Blake, David & Wright, Douglas & Zhang, Yumeng, 2013. "Target-driven investing: Optimal investment strategies in defined contribution pension plans under loss aversion," Journal of Economic Dynamics and Control, Elsevier, vol. 37(1), pages 195-209.
    11. Andrew Clare & James Seaton & Peter N. Smith & Stephen Thomas, 2014. "European Equity Investing through the Financial Crisis: Can Risk Parity, Momentum or Trend Following Help to Reduce Tail Risk?," Discussion Papers 14/02, Department of Economics, University of York.
    12. Cong, F. & Oosterlee, C.W., 2016. "Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 23-38.
    13. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
    14. Paul Emms & Steven Haberman, 2008. "Income Drawdown Schemes for a Defined‐Contribution Pension Plan," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 739-761, September.
    15. Alessandro Milazzo & Elena Vigna, 2018. "The Italian Pension Gap: A Stochastic Optimal Control Approach," Risks, MDPI, vol. 6(2), pages 1-20, April.
    16. Grebenkov, Denis S. & Serror, Jeremy, 2015. "Optimal allocation of trend following strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 107-125.
    17. Andrew Clare & James Seaton & Peter N. Smith & Stephen Thomas, 2014. "When Growth Beats Value: Removing Tail Risk From Global Equity Momentum Strategies," Discussion Papers 14/09, Department of Economics, University of York.
    18. F. Cong & C. W. Oosterlee, 2017. "On Robust Multi-Period Pre-Commitment And Time-Consistent Mean-Variance Portfolio Optimization," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(07), pages 1-26, November.
    19. Wolfram Horneff & Raimond Maurer & Olivia Mitchell & Michael Stamos, 2007. "Money in Motion: Dynamic Portfolio Choice in Retirement," Working Papers wp152, University of Michigan, Michigan Retirement Research Center.
    20. Salvatore Federico & Paul Gassiat & Fausto Gozzi, 2015. "Utility maximization with current utility on the wealth: regularity of solutions to the HJB equation," Finance and Stochastics, Springer, vol. 19(2), pages 415-448, April.

    More about this item

    Keywords

    Sequence Risk; Perfect Withdrawal Rate; Decumulation; Trend-Following; CAPE;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    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:yor:yorken:16/11. 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: Paul Hodgson (email available below). General contact details of provider: https://edirc.repec.org/data/deyoruk.html .

    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.