IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v11y2023i6p107-d1164262.html
   My bibliography  Save this article

A Guaranteed-Return Structured Product as an Investment Risk-Hedging Instrument in Pension Savings Plans

Author

Listed:
  • Zvika Afik

    (Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, Beer-Sheva 8443944, Israel
    Israel and Hadassah Academic College, Jerusalem 9101001, Israel)

  • Elroi Hadad

    (Department of Industrial Engineering and Management, Sami Shamoon College of Engineering, Beer-Sheva 8410802, Israel)

  • Rami Yosef

    (Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev, Beer-Sheva 8443944, Israel)

Abstract

This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital market risk. Using Monte Carlo simulations on three different guaranteed returns to test the investment strategy of the SP against a balanced investment portfolio, we measure their performance across a wide variety of capital market returns and risk scenarios. The results show that the SP guarantees a minimal return on the pension savings portfolio and offers a higher portfolio return at a lower investment risk, compared with the balanced investment portfolio. We conclude that the SP may become popular among pension fund members, potentially leading to improved risk management, greater competition, and investment strategy innovations for defined contribution pension schemes.

Suggested Citation

  • Zvika Afik & Elroi Hadad & Rami Yosef, 2023. "A Guaranteed-Return Structured Product as an Investment Risk-Hedging Instrument in Pension Savings Plans," Risks, MDPI, vol. 11(6), pages 1-16, June.
    • Handle: RePEc:gam:jrisks:v:11:y:2023:i:6:p:107-:d:1164262
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/11/6/107/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/11/6/107/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Thorsten Hens & Marc Oliver Rieger, 2014. "Can utility optimization explain the demand for structured investment products?," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 673-681, April.
    2. Randle, Tony & Rudolph, Heinz P., 2014. "Pension risk and risk-based supervision in defined contribution pension funds," Policy Research Working Paper Series 6813, The World Bank.
    3. Marie‐Eve Lachance & Olivia S. Mitchell & Kent Smetters, 2003. "Guaranteeing Defined Contribution Pensions: The Option to Buy Back a Defined Benefit Promise," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(1), pages 1-16, March.
    4. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Scholarly Articles 2624460, Harvard University Department of Economics.
    5. Fang, H., 2016. "Insurance Markets for the Elderly," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 237-309, Elsevier.
    6. James P. Quirk & Rubin Saposnik, 1962. "Admissibility and Measurable Utility Functions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 29(2), pages 140-146.
    7. Ibragimov, Rustam & Walden, Johan, 2007. "The limits of diversification when losses may be large," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2551-2569, August.
    8. Christian Knoller, 2016. "MULTIPLE REFERENCE POINTS AND THE DEMAND FOR PRINCIPAL-PROTECTED LIFE ANNUITIES: An EXPERIMENTAL ANALYSIS," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 163-179, January.
    9. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    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. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    2. Steven Kou & Xianhua Peng & Chris C. Heyde, 2013. "External Risk Measures and Basel Accords," Mathematics of Operations Research, INFORMS, vol. 38(3), pages 393-417, August.
    3. Daniel R. Jiang & Warren B. Powell, 2018. "Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures," Mathematics of Operations Research, INFORMS, vol. 43(2), pages 554-579, May.
    4. Steven Kou & Xianhua Peng, 2014. "On the Measurement of Economic Tail Risk," Papers 1401.4787, arXiv.org, revised Aug 2015.
    5. Byers, J.W. & Popova, I. & Simkins, B.J., 2021. "Robust estimation of conditional risk measures using machine learning algorithm for commodity futures prices in the presence of outliers," Journal of Commodity Markets, Elsevier, vol. 24(C).
    6. Rama Cont & Romain Deguest & Giacomo Scandolo, 2010. "Robustness and sensitivity analysis of risk measurement procedures," Quantitative Finance, Taylor & Francis Journals, vol. 10(6), pages 593-606.
    7. Andreas Muhlbacher & Thomas Guhr, 2018. "Credit Risk Meets Random Matrices: Coping with Non-Stationary Asset Correlations," Papers 1803.00261, arXiv.org.
    8. Chirok Han & Jin Seo Cho & Peter C. B. Phillips, 2011. "Infinite Density at the Median and the Typical Shape of Stock Return Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 282-294, April.
    9. DiTraglia, Francis J. & Gerlach, Jeffrey R., 2013. "Portfolio selection: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 305-323.
    10. Leili Javanmardi & Yuri Lawryshyn, 2016. "A new rank dependent utility approach to model risk averse preferences in portfolio optimization," Annals of Operations Research, Springer, vol. 237(1), pages 161-176, February.
    11. Thomas Holzheu & Ginger Turner, 2018. "The Natural Catastrophe Protection Gap: Measurement, Root Causes and Ways of Addressing Underinsurance for Extreme Events†," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 43(1), pages 37-71, January.
    12. Chollete, Lorán, 2008. "The Propagation of Financial Extremes: An Application to Subprime Market Spillovers," Discussion Papers 2008/2, Norwegian School of Economics, Department of Business and Management Science.
    13. Adabi Firouzjaee , Bagher & Mehrara , Mohsen & Mohammadi , Shapour, 2014. "Optimal Portfolio Selection for Tehran Stock Exchange Using Conditional, Partitioned and Worst-case Value at Risk Measures," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 9(1), pages 1-30, October.
    14. Ankudinov, Andrei & Ibragimov, Rustam & Lebedev, Oleg, 2017. "Sanctions and the Russian stock market," Research in International Business and Finance, Elsevier, vol. 40(C), pages 150-162.
    15. Mainik Georg & Rüschendorf Ludger, 2012. "Ordering of multivariate risk models with respect to extreme portfolio losses," Statistics & Risk Modeling, De Gruyter, vol. 29(1), pages 73-106, March.
    16. Matthias Degen & Dominik D. Lambrigger & Johan Segers, 2009. "Risk Concentration and Diversification: Second-Order Properties," Papers 0910.2367, arXiv.org, revised Dec 2009.
    17. Andreas Muhlbacher & Thomas Guhr, 2017. "Extreme portfolio loss correlations in credit risk," Papers 1706.09809, arXiv.org.
    18. Daniel Gottlieb & Olivia S. Mitchell, 2020. "Narrow Framing and Long‐Term Care Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 861-893, December.
    19. Rustam Ibragimov & Johan Walden, 2011. "Value at risk and efficiency under dependence and heavy-tailedness: models with common shocks," Annals of Finance, Springer, vol. 7(3), pages 285-318, August.
    20. Ibragimov, Rustam, 2008. "Heavy-tailedness and threshold sex determination," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2804-2810, November.

    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:jrisks:v:11:y:2023:i:6:p:107-:d:1164262. 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.