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Portfolio insurance under a risk-measure constraint

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  • De Franco, Carmine
  • Tankov, Peter

Abstract

We study the problem of portfolio insurance from the point of view of a fund manager, who guarantees to the investor that the portfolio value at maturity will be above a fixed threshold. If, at maturity, the portfolio value is below the guaranteed level, a third party will refund the investor up to the guarantee. In exchange for this protection, the third party imposes a limit on the risk exposure of the fund manager, in the form of a convex monetary risk measure. The fund manager therefore tries to maximize the investor’s utility function subject to the risk-measure constraint. We give a full solution to this non-convex optimization problem in the complete market setting and show in particular that the choice of the risk measure is crucial for the optimal portfolio to exist. Explicit results are provided for the entropic risk measure (for which the optimal portfolio always exists) and for the class of spectral risk measures (for which the optimal portfolio may fail to exist in some cases).

Suggested Citation

  • De Franco, Carmine & Tankov, Peter, 2011. "Portfolio insurance under a risk-measure constraint," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 361-370.
    • Handle: RePEc:eee:insuma:v:49:y:2011:i:3:p:361-370
    DOI: 10.1016/j.insmatheco.2011.05.009
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    Cited by:

    1. Fangyuan Zhang, 2023. "Non-concave portfolio optimization with average value-at-risk," Mathematics and Financial Economics, Springer, volume 17, number 3, December.
    2. Géraldine Bouveret, 2018. "Portfolio Optimization Under A Quantile Hedging Constraint," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-36, November.
    3. Chen, An & Stadje, Mitja & Zhang, Fangyuan, 2024. "On the equivalence between Value-at-Risk- and Expected Shortfall-based risk measures in non-concave optimization," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 114-129.
    4. Goovaerts, Marc & Linders, Daniël & Van Weert, Koen & Tank, Fatih, 2012. "On the interplay between distortion, mean value and Haezendonck–Goovaerts risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 51(1), pages 10-18.
    5. Pézier, Jacques & Scheller, Johanna, 2013. "Best portfolio insurance for long-term investment strategies in realistic conditions," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 263-274.
    6. Donnelly, Catherine & Gerrard, Russell & Guillén, Montserrat & Nielsen, Jens Perch, 2015. "Less is more: Increasing retirement gains by using an upside terminal wealth constraint," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 259-267.
    7. Catherine Donnelly & Russell Gerrard & Montserrat Guillén & Jens Perch Nielsen, 2015. "Less is more: increasing retirement gains by using an upside terminal wealth constraint," Working Papers 2015-02, Universitat de Barcelona, UB Riskcenter.

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