IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v92y2020icp90-103.html
   My bibliography  Save this article

Long-term real dynamic investment planning

Author

Listed:
  • Gerrard, Russell
  • Hiabu, Munir
  • Nielsen, Jens Perch
  • Vodička, Peter

Abstract

When long-term savers plan for retirement they need to know their investment prospects in terms of real income (Merton, 2014). While inflation has traditionally been considered as a complication in financial analysis and financial practise, we obtain enhanced predictability and model fit if the real returns are targeted in conjunction with earnings-by-price minus inflation as predictor. For this latter case, we propose an investment strategy of updating the simple classical Merton proportion as we go along. This simple strategy is very close to the complicated theoretically optimal solution but has comparably much lower parameter uncertainty.

Suggested Citation

  • Gerrard, Russell & Hiabu, Munir & Nielsen, Jens Perch & Vodička, Peter, 2020. "Long-term real dynamic investment planning," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 90-103.
    • Handle: RePEc:eee:insuma:v:92:y:2020:i:c:p:90-103
    DOI: 10.1016/j.insmatheco.2020.03.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167668720300299
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.insmatheco.2020.03.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bergmeir, Christoph & Hyndman, Rob J. & Koo, Bonsoo, 2018. "A note on the validity of cross-validation for evaluating autoregressive time series prediction," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 70-83.
    2. Gerrard, Russell & Hiabu, Munir & Kyriakou, Ioannis & Nielsen, Jens Perch, 2019. "Communication and personal selection of pension saver’s financial risk," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1102-1111.
    3. Jørgensen, Peter Løchte & Linnemann, Per, 2012. "A comparison of three different pension savings products with special emphasis on the payout phase," Annals of Actuarial Science, Cambridge University Press, vol. 6(1), pages 137-152, March.
    4. Nielsen, Jens Perch & Sperlich, Stefan, 2003. "Prediction of Stock Returns: A New Way to Look at It," ASTIN Bulletin, Cambridge University Press, vol. 33(2), pages 399-417, November.
    5. Duffie, Darrell & Skiadas, Costis, 1994. "Continuous-time security pricing : A utility gradient approach," Journal of Mathematical Economics, Elsevier, vol. 23(2), pages 107-131, March.
    6. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    7. 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.
    8. Kim, Tong Suk & Omberg, Edward, 1996. "Dynamic Nonmyopic Portfolio Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 141-161.
    9. Guillen, Montserrat & Jorgensen, Peter Lochte & Nielsen, Jens Perch, 2006. "Return smoothing mechanisms in life and pension insurance: Path-dependent contingent claims," Insurance: Mathematics and Economics, Elsevier, vol. 38(2), pages 229-252, April.
    10. Scholz, Michael & Nielsen, Jens Perch & Sperlich, Stefan, 2015. "Nonparametric prediction of stock returns based on yearly data: The long-term view," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 143-155.
    11. Mei, Zhaoxun, 2019. "The design of pension contracts: on the perspective of customers," Annals of Actuarial Science, Cambridge University Press, vol. 13(2), pages 219-240, September.
    12. Paul Harrison & Harold H. Zhang, 1999. "An Investigation Of The Risk And Return Relation At Long Horizons," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 399-408, August.
    13. Kim, Sangbae & In, Francis, 2005. "The relationship between stock returns and inflation: new evidence from wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 435-444, June.
    14. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional variance forecasts for long-term stock returns," Graz Economics Papers 2019-08, University of Graz, Department of Economics.
    15. van Bilsen, Servaas & Linders, Daniël, 2019. "Affordable and adequate annuities with stable payouts: Fantasy or reality?," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 19-42.
    16. Engsted, Tom & Tanggaard, Carsten, 2002. "The relation between asset returns and inflation at short and long horizons," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(2), pages 101-118, April.
    17. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 433-495.
    18. Thomas Bernhardt & Catherine Donnelly, 2019. "Modern tontine with bequest: innovation in pooled annuity products," Papers 1903.05990, arXiv.org.
    19. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    20. Donnelly, Catherine & Guillen, Montserrat & Nielsen, Jens Perch & Pérez-Marín, Ana Maria, 2018. "Implementing Individual Savings Decisions For Retirement With Bounds On Wealth," ASTIN Bulletin, Cambridge University Press, vol. 48(1), pages 111-137, January.
    21. Golez, Benjamin & Koudijs, Peter, 2018. "Four centuries of return predictability," Journal of Financial Economics, Elsevier, vol. 127(2), pages 248-263.
    22. Linnemann, Per & Bruhn, Kenneth & Steffensen, Mogens, 2015. "A comparison of modern investment-linked pension savings products," Annals of Actuarial Science, Cambridge University Press, vol. 9(1), pages 72-84, March.
    23. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
    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. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    2. Gerrard, Russell & Kyriakou, Ioannis & Nielsen, Jens Perch & Vodička, Peter, 2023. "On optimal constrained investment strategies for long-term savers in stochastic environments and probability hedging," European Journal of Operational Research, Elsevier, vol. 307(2), pages 948-962.
    3. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    4. Parastoo Mousavi, 2021. "Debt-by-Price Ratio, End-of-Year Economic Growth, and Long-Term Prediction of Stock Returns," Mathematics, MDPI, vol. 9(13), pages 1-18, 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. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    2. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    3. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    4. John Y. Campbell & Luis M. Viceira & Joshua S. White, 2003. "Foreign Currency for Long-Term Investors," Economic Journal, Royal Economic Society, vol. 113(486), pages 1-25, March.
    5. John Y. Campbell & Yeung Lewis Chanb & M. Viceira, 2013. "A multivariate model of strategic asset allocation," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part II, chapter 39, pages 809-848, World Scientific Publishing Co. Pte. Ltd..
    6. Weidong Tian & Murray Carlson & David A. Chapman & Ron Kaniel & Hong Yan, 2017. "Specification Error, Estimation Risk, and Conditional Portfolio Rules," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 263-288, June.
    7. Mark E. Wohar & David E. Rapach, 2005. "Return Predictability and the Implied Intertemporal Hedging Demands for Stocks and Bonds: International Evidence," Computing in Economics and Finance 2005 329, Society for Computational Economics.
    8. Michael W. Brandt & Amit Goyal & Pedro Santa-Clara & Jonathan R. Stroud, 2005. "A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 831-873.
    9. Ferstl, Robert & Weissensteiner, Alex, 2011. "Asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 182-192, January.
    10. Hui Chen & Nengjiu Ju & Jianjun Miao, 2014. "Dynamic Asset Allocation with Ambiguous Return Predictability," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(4), pages 799-823, October.
    11. Suresh M. Sundaresan, 2000. "Continuous‐Time Methods in Finance: A Review and an Assessment," Journal of Finance, American Finance Association, vol. 55(4), pages 1569-1622, August.
    12. Klos, Alexander & Langer, Thomas & Weber, Martin, 2002. "Über kurz oder lang : welche Rolle spielt der Anlagehorizont bei Investitionsentscheidungen?," Papers 02-49, Sonderforschungsbreich 504.
    13. Parastoo Mousavi, 2021. "Debt-by-Price Ratio, End-of-Year Economic Growth, and Long-Term Prediction of Stock Returns," Mathematics, MDPI, vol. 9(13), pages 1-18, July.
    14. Jakub W. Jurek & Luis M. Viceira, 2011. "Optimal Value and Growth Tilts in Long-Horizon Portfolios," Review of Finance, European Finance Association, vol. 15(1), pages 29-74.
    15. John H. Cochrane, 2014. "A Mean-Variance Benchmark for Intertemporal Portfolio Theory," Journal of Finance, American Finance Association, vol. 69(1), pages 1-49, February.
    16. Luca Benzoni & Pierre Collin‐Dufresne & Robert S. Goldstein, 2007. "Portfolio Choice over the Life‐Cycle when the Stock and Labor Markets Are Cointegrated," Journal of Finance, American Finance Association, vol. 62(5), pages 2123-2167, October.
    17. Sørensen, Carsten & Trolle, Anders Bjerre, 2006. "Dynamic asset allocation and latent variables," Working Papers 2004-8, Copenhagen Business School, Department of Finance.
    18. José María Sarabia & Faustino Prieto & Vanesa Jordá & Stefan Sperlich, 2020. "A Note on Combining Machine Learning with Statistical Modeling for Financial Data Analysis," Risks, MDPI, vol. 8(2), pages 1-14, April.
    19. Gollier Christian, 2004. "Optimal Dynamic Portfolio Risk with First-Order and Second-Order Predictability," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 4(1), pages 1-35, September.
    20. George Chacko & Luis M. Viceira, 2005. "Dynamic Consumption and Portfolio Choice with Stochastic Volatility in Incomplete Markets," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1369-1402.

    More about this item

    Keywords

    Long-term Investment; Forecasting Returns; Nonmyopic Strategy; Optimal Investment; Strategy; Econometrics;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:eee:insuma:v:92:y:2020:i:c:p:90-103. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    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.