IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2609.33913.html

Magic strikes for variance and gamma contracts, and other attainable claims

Author

Listed:
  • Florian Bourgey
  • Jim Gatheral

Abstract

Building on the forest expansion of Al\`os, Gatheral and Radoi\v{c}i\'c and on the explicit Bergomi-Guyon smile expansion derived by Bourgey and Gatheral (2026), we derive fixed-point approximations, in terms of the implied total variance at a small number of magic strikes, for the fair values of power payoff contracts; the variance and gamma contracts arise as the endpoints of this one-parameter family, priced by a single set of formulae. We prove that such approximations exist at every order: at order $n$, $2\lceil n/2\rceil+1$ magic strikes suffice. Numerical tests under the Heston and rough Bergomi models demonstrate good accuracy even for strongly skewed smiles, and the method applies directly to interpolated market smiles without strike inversion. For the volatility contract, we show that the maturity-T smile does not determine the leading correction to the Rolloos-Arslan approximation.

Suggested Citation

  • Florian Bourgey & Jim Gatheral, 2026. "Magic strikes for variance and gamma contracts, and other attainable claims," Papers 2609.33913, arXiv.org.
  • Handle: RePEc:arx:papers:2609.33913
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2609.33913
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christian Bayer & Peter Friz & Jim Gatheral, 2016. "Pricing under rough volatility," Quantitative Finance, Taylor & Francis Journals, vol. 16(6), pages 887-904, June.
    2. Elisa Alòs & Jim Gatheral & Radoš Radoičić, 2020. "Exponentiation of conditional expectations under stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 20(1), pages 13-27, January.
    3. Stefano De Marco & Claude Martini, 2018. "Moment generating functions and normalized implied volatilities: unification and extension via Fukasawa’s pricing formula," Quantitative Finance, Taylor & Francis Journals, vol. 18(4), pages 609-622, April.
    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. Stefano De Marco, 2020. "On the harmonic mean representation of the implied volatility," Papers 2007.03585, arXiv.org.
    2. Paul P. Hager & Dorte Kreher, 2026. "Expanding the rough Heston model in $H$," Papers 2606.16619, arXiv.org.
    3. Alessandro Bondi & Sergio Pulido & Simone Scotti, 2022. "The rough Hawkes Heston stochastic volatility model," Papers 2210.12393, arXiv.org.
    4. Christa Cuchiero & Sara Svaluto-Ferro & Josef Teichmann, 2023. "Signature SDEs from an affine and polynomial perspective," Papers 2302.01362, arXiv.org, revised Jul 2026.
    5. Siow Woon Jeng & Adem Kiliçman, 2021. "SPX Calibration of Option Approximations under Rough Heston Model," Mathematics, MDPI, vol. 9(21), pages 1-11, October.
    6. repec:hal:wpaper:hal-03827332 is not listed on IDEAS
    7. Alessandro Bondi & Sergio Pulido & Simone Scotti, 2024. "The rough Hawkes Heston stochastic volatility model," Post-Print hal-03827332, HAL.
    8. Siow Woon Jeng & Adem Kilicman, 2020. "Series Expansion and Fourth-Order Global Padé Approximation for a Rough Heston Solution," Mathematics, MDPI, vol. 8(11), pages 1-26, November.
    9. Christian Bayer & Peter K. Friz & Paul Gassiat & Jorg Martin & Benjamin Stemper, 2020. "A regularity structure for rough volatility," Mathematical Finance, Wiley Blackwell, vol. 30(3), pages 782-832, July.
    10. Eduardo Abi Jaber, 2022. "The characteristic function of Gaussian stochastic volatility models: an analytic expression," Working Papers hal-02946146, HAL.
    11. Eduardo Abi Jaber & Donatien Hainaut & Edouard Motte, 2025. "The Volterra Stein-Stein model with stochastic interest rates," Papers 2503.01716, arXiv.org, revised Sep 2026.
    12. Eduardo Abi Jaber, 2022. "The characteristic function of Gaussian stochastic volatility models: an analytic expression," Finance and Stochastics, Springer, vol. 26(4), pages 733-769, October.
    13. Changqing Teng & Guanglian Li, 2025. "Efficient Simulation and Calibration of the Rough Bergomi Model via Wasserstein Distance," Papers 2512.00448, arXiv.org, revised Apr 2026.
    14. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    15. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    16. Friesen, Martin & Gerhold, Stefan & Wiedermann, Kristof, 2026. "Small-time central limit theorems for stochastic Volterra integral equations and their Markovian lifts," Stochastic Processes and their Applications, Elsevier, vol. 195(C).
    17. Florian Aichinger & Sascha Desmettre, 2025. "Pricing of geometric Asian options in the Volterra-Heston model," Review of Derivatives Research, Springer, vol. 28(1), pages 1-30, April.
    18. Calypso Herrera & Florian Krach & Pierre Ruyssen & Josef Teichmann, 2021. "Optimal Stopping via Randomized Neural Networks," Papers 2104.13669, arXiv.org, revised Dec 2023.
    19. Zhu, Qinwen & Diao, Xundi & Wu, Chongfeng, 2023. "Volatility forecast with the regularity modifications," Finance Research Letters, Elsevier, vol. 58(PA).
    20. Bastien Baldacci, 2020. "High-frequency dynamics of the implied volatility surface," Papers 2012.10875, arXiv.org.
    21. Saad Mouti, 2026. "Rough Volatility Across Assets," Papers 2608.16749, arXiv.org.

    More about this item

    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:arx:papers:2609.33913. 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.