IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v45y2025i9p1154-1181.html

Understanding the Factors Driving the Demand of Structured Investment Products

Author

Listed:
  • Massimo Guidolin
  • Giacomo Leonetti
  • Manuela Pedio

Abstract

Structured products have gained increasing popularity among retail investors over the last decade, both in Europe and in the United States. However, based on data on the ex post realized gains of retail clients investing in certificates, the literature has concluded that the high demand of these products may be hard to rationalize within a portfolio optimization framework. In this paper, we investigate whether a rational, perfectly informed investor with constant relative risk aversion (CRRA) preferences who optimally allocates her wealth among risky and riskless assets can ex ante expect to benefit from adding structured products to her portfolio. We show that the utility gains from investment certificates vary dramatically across alternative structures, investment horizons, and levels of risk aversion. We also find that the optimal demand for investment certificates and their benefits depend heavily on the pricing models informing the portfolio assessment and the size of the risk premia associated with them.

Suggested Citation

  • Massimo Guidolin & Giacomo Leonetti & Manuela Pedio, 2025. "Understanding the Factors Driving the Demand of Structured Investment Products," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(9), pages 1154-1181, September.
    • Handle: RePEc:wly:jfutmk:v:45:y:2025:i:9:p:1154-1181
    DOI: 10.1002/fut.22612
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22612
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.22612?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
    ---><---

    References listed on IDEAS

    as
    1. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
    2. A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
    3. Stoimenov, Pavel A. & Wilkens, Sascha, 2005. "Are structured products 'fairly' priced? An analysis of the German market for equity-linked instruments," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 2971-2993, December.
    4. Mark Broadie & Özgür Kaya, 2006. "Exact Simulation of Stochastic Volatility and Other Affine Jump Diffusion Processes," Operations Research, INFORMS, vol. 54(2), pages 217-231, April.
    5. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    6. Joost Driessen & Pascal Maenhout, 2007. "An Empirical Portfolio Perspective on Option Pricing Anomalies," Review of Finance, European Finance Association, vol. 11(4), pages 561-603.
    7. Liu, Jun & Pan, Jun, 2003. "Dynamic derivative strategies," Journal of Financial Economics, Elsevier, vol. 69(3), pages 401-430, September.
    8. Yuan-Hung Hsuku, 2007. "Dynamic consumption and asset allocation with derivative securities," Quantitative Finance, Taylor & Francis Journals, vol. 7(2), pages 137-149.
    9. John Quiggin & Robert G Chambers, 2009. "Bargaining Power and Efficiency in Insurance Contracts," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 34(1), pages 47-73, June.
    10. Henderson, Brian J. & Pearson, Neil D., 2011. "The dark side of financial innovation: A case study of the pricing of a retail financial product," Journal of Financial Economics, Elsevier, vol. 100(2), pages 227-247, May.
    11. Faias, José Afonso & Santa-Clara, Pedro, 2017. "Optimal Option Portfolio Strategies: Deepening the Puzzle of Index Option Mispricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(1), pages 277-303, February.
    12. repec:bla:jfinan:v:59:y:2004:i:3:p:1367-1404 is not listed on IDEAS
    13. Vladimir Anic & Martin Wallmeier, 2020. "Perceived Attractiveness of Structured Financial Products: The Role of Presentation Format and Reference Instruments," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(1), pages 78-102, January.
    14. Entrop, Oliver & Fischer, Georg & McKenzie, Michael & Wilkens, Marco & Winkler, Christoph, 2016. "How does pricing affect investors’ product choice? Evidence from the market for discount certificates," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 195-215.
    15. Darrell Duffie & Jun Pan & Kenneth Singleton, 2000. "Transform Analysis and Asset Pricing for Affine Jump-Diffusions," Econometrica, Econometric Society, vol. 68(6), pages 1343-1376, November.
    16. Benet, Bruce A. & Giannetti, Antoine & Pissaris, Seema, 2006. "Gains from structured product markets: The case of reverse-exchangeable securities (RES)," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 111-132, January.
    17. Mark Broadie & Mikhail Chernov & Michael Johannes, 2007. "Model Specification and Risk Premia: Evidence from Futures Options," Journal of Finance, American Finance Association, vol. 62(3), pages 1453-1490, June.
    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. Massimo Guidolin & Giacomo Leonetti & Manuela Pedio, 2024. "Who should buy structured investment products and why?," BAFFI CAREFIN Working Papers 24222, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. Shuonan Yuan & Marc Oliver Rieger, 2021. "Diversification with options and structured products," Review of Derivatives Research, Springer, vol. 24(1), pages 55-77, April.
    3. Branger, Nicole & Hansis, Alexandra, 2012. "Asset allocation: How much does model choice matter?," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1865-1882.
    4. Bas Peeters, 2012. "Risk premiums in a simple market model for implied volatility," Quantitative Finance, Taylor & Francis Journals, vol. 13(5), pages 739-748, January.
    5. Hamed Ghanbari & Michael Oancea & Stylianos Perrakis, 2021. "Shedding light on a dark matter: Jump diffusion and option‐implied investor preferences," European Financial Management, European Financial Management Association, vol. 27(2), pages 244-286, March.
    6. Benzoni, Luca & Collin-Dufresne, Pierre & Goldstein, Robert S., 2011. "Explaining asset pricing puzzles associated with the 1987 market crash," Journal of Financial Economics, Elsevier, vol. 101(3), pages 552-573, September.
    7. Branger, Nicole & Schlag, Christian & Schneider, Eva, 2008. "Optimal portfolios when volatility can jump," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1087-1097, June.
    8. Bégin, Jean-François & Gómez, Fabio & Ignatieva, Katja & Li, Han, 2025. "The stochastic behavior of electricity prices under scrutiny: Evidence from spot and futures markets," Energy Economics, Elsevier, vol. 144(C).
    9. Yan Qu & Angelos Dassios & Hongbiao Zhao, 2023. "Shot-noise cojumps: Exact simulation and option pricing," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 647-665, March.
    10. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    11. Yoontae Jeon & Raymond Kan & Gang Li, 2025. "Stock Return Autocorrelations and Expected Option Returns," Management Science, INFORMS, vol. 71(6), pages 4895-4914, June.
    12. Qu, Yan & Dassios, Angelos & Zhao, Hongbiao, 2023. "Shot-noise cojumps: exact simulation and option pricing," LSE Research Online Documents on Economics 111537, London School of Economics and Political Science, LSE Library.
    13. Papantonis, Ioannis, 2016. "Volatility risk premium implications of GARCH option pricing models," Economic Modelling, Elsevier, vol. 58(C), pages 104-115.
    14. Santa-Clara, Pedro & Yan, Shu, 2004. "Jump and Volatility Risk and Risk Premia: A New Model and Lessons from S&P 500 Options," University of California at Los Angeles, Anderson Graduate School of Management qt5dv8v999, Anderson Graduate School of Management, UCLA.
    15. Branger, Nicole & Hansis, Alexandra, 2015. "Earning the right premium on the right factor in portfolio planning," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 367-383.
    16. Boswijk, H. Peter & Laeven, Roger J.A. & Vladimirov, Evgenii, 2024. "Estimating option pricing models using a characteristic function-based linear state space representation," Journal of Econometrics, Elsevier, vol. 244(1).
    17. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    18. Dario Alitab & Giacomo Bormetti & Fulvio Corsi & Adam A. Majewski, 2019. "A realized volatility approach to option pricing with continuous and jump variance components," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 639-664, December.
    19. Henri Bertholon & Alain Monfort & Fulvio Pegoraro, 2006. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working Papers 2006-28, Center for Research in Economics and Statistics.
    20. Glasserman, Paul & Kim, Kyoung-Kuk, 2009. "Saddlepoint approximations for affine jump-diffusion models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 15-36, January.

    More about this item

    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:wly:jfutmk:v:45:y:2025:i:9:p:1154-1181. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    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.