IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2608.22620.html

WSVI: A Dimensionless Shape Family for Implied Volatility and Its Static No-Arbitrage Structure

Author

Listed:
  • Charles Clevenger
  • Xiang Wan

Abstract

W-shaped smiles appear in near-expiry options around binary events such as earnings, and have been associated with bimodal risk-neutral densities. The three-parameter eSSVI slice cannot produce them. This paper defines WSVI, a parametric family for implied volatility that admits negative at-the-forward curvature and bimodal implied densities, and develops its static no-arbitrage structure. The construction factorizes total variance into a level and a dimensionless shape of normalized log-moneyness. The shape extends the per-slice eSSVI form with bounded one-sided basis terms, which add flexibility in the interior while leaving the leading-order wing behavior controlled by the affine and quadratic components. We characterize the family's exact domain and write the butterfly, vertical spread, and calendar conditions directly in shape coordinates.

Suggested Citation

  • Charles Clevenger & Xiang Wan, 2026. "WSVI: A Dimensionless Shape Family for Implied Volatility and Its Static No-Arbitrage Structure," Papers 2608.22620, arXiv.org.
  • Handle: RePEc:arx:papers:2608.22620
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2608.22620
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul Glasserman & Dan Pirjol, 2023. "W-shaped implied volatility curves and the Gaussian mixture model," Quantitative Finance, Taylor & Francis Journals, vol. 23(4), pages 557-577, April.
    2. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    3. Jim Gatheral & Antoine Jacquier, 2014. "Arbitrage-free SVI volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 59-71, January.
    4. Arianna Mingone, 2022. "No arbitrage global parametrization for the eSSVI volatility surface," Papers 2204.00312, arXiv.org.
    5. Roger W. Lee, 2004. "The Moment Formula For Implied Volatility At Extreme Strikes," Mathematical Finance, Wiley Blackwell, vol. 14(3), pages 469-480, July.
    6. A. Mingone, 2022. "No arbitrage global parametrization for the eSSVI volatility surface," Quantitative Finance, Taylor & Francis Journals, vol. 22(12), pages 2205-2217, December.
    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. Nicola F. Zaugg & Leonardo Perotti & Lech A. Grzelak, 2024. "Volatility Parametrizations with Random Coefficients: Analytic Flexibility for Implied Volatility Surfaces," Papers 2411.04041, arXiv.org, revised Jan 2026.
    2. Vimal Raval & Antoine Jacquier, 2023. "The log‐moment formula for implied volatility," Mathematical Finance, Wiley Blackwell, vol. 33(4), pages 1146-1165, October.
    3. Shuzhen Yang & Wenqing Zhang, 2023. "Fixed-point iterative algorithm for SVI model," Papers 2301.07830, arXiv.org.
    4. Jimin Lin, 2026. "Shallow Representation of Option Implied Information," Papers 2603.17151, arXiv.org.
    5. Yang, Shuzhen & Zhang, Wenqing, 2025. "Fixed-point iterative algorithm for SVI model," Finance Research Letters, Elsevier, vol. 80(C).
    6. Sergey Badikov & Mark H. A. Davis & Antoine Jacquier, 2018. "Perturbation analysis of sub/super hedging problems," Papers 1806.03543, arXiv.org, revised May 2021.
    7. Bastien Baldacci, 2020. "High-frequency dynamics of the implied volatility surface," Papers 2012.10875, arXiv.org.
    8. Martin Keller-Ressel & Hannes Nikulski, 2026. "Discovering parametrizations of implied volatility with symbolic regression," Papers 2603.21892, arXiv.org.
    9. Jian'an Zhang, 2025. "Tail-Safe Stochastic-Control SPX-VIX Hedging: A White-Box Bridge Between AI Sensitivities and Arbitrage-Free Market Dynamics," Papers 2510.15937, arXiv.org.
    10. Michael R. Tehranchi, 2020. "A Black–Scholes inequality: applications and generalisations," Finance and Stochastics, Springer, vol. 24(1), pages 1-38, January.
    11. Jian'an Zhang, 2025. "Risk-Sensitive Option Market Making with Arbitrage-Free eSSVI Surfaces: A Constrained RL and Stochastic Control Bridge," Papers 2510.04569, arXiv.org.
    12. Hao Qin & Ruozhong Yang & Charlie Che & Liming Feng, 2026. "Arbitrage-Free Multi-Maturity Risk-Neutral Marginals," Papers 2607.06204, arXiv.org.
    13. Ruben Wiedemann & Antoine Jacquier & Lukas Gonon, 2024. "Operator Deep Smoothing for Implied Volatility," Papers 2406.11520, arXiv.org, revised Jun 2025.
    14. Aaron Wizman & Gabriel Turinici & Gregory Merran, 2026. "From Arbitrage Removal to Density Extraction: A Model-Free Framework for Short-Dated Options," Papers 2605.22792, arXiv.org, revised Jun 2026.
    15. Jian Sun, 2026. "Monotonicity of Normalized Implied-Volatility Coordinates under No-Arbitrage," Papers 2606.23883, arXiv.org.
    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. Philip Stahl, 2022. "Asymptotic extrapolation of model-free implied variance: exploring structural underestimation in the VIX Index," Review of Derivatives Research, Springer, vol. 25(3), pages 315-339, October.
    18. Dillschneider, Yannick & Maurer, Raimond, 2019. "Functional Ross recovery: Theoretical results and empirical tests," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    19. Florence Guillaume & Wim Schoutens, 2014. "Heston Model: The Variance Swap Calibration," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 76-89, April.
    20. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.

    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:arx:papers:2608.22620. 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.