IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2609.39256.html

Stochastic Knothe-Rosenblatt: Light-speed Calibration of Stochastic Local Volatility Models

Author

Listed:
  • Mathias Beiglbock
  • Manuel Hasenbichler
  • Gudmund Pammer

Abstract

European option smiles determine the risk-neutral marginal laws of an asset, but not their intertemporal coupling, which is decisive for many applications. The Bass martingale construction selects, among all calibrated martingales, the one closest to Bachelier dynamics; it permits fast calibration at discrete maturities and recovers the Dupire local-volatility (LV) model as the maturity grid is refined. This article develops a modular calibration overlay for existing stochastic and path-dependent volatility models. We sequentially construct a martingale that matches all prescribed marginals exactly while remaining as close as possible, in an adapted Knothe-Rosenblatt sense, to the reference dynamics. As with the Bass LV model, each calibration step is amenable to an efficient Martingale Sinkhorn algorithm. We develop the theoretical foundations, numerical implementation and consider convergence to the SLV model. We also benchmark the method for Heston and Bergomi finite-factor path-dependent volatility dynamics and develop the multi-asset extension.

Suggested Citation

  • Mathias Beiglbock & Manuel Hasenbichler & Gudmund Pammer, 2026. "Stochastic Knothe-Rosenblatt: Light-speed Calibration of Stochastic Local Volatility Models," Papers 2609.39256, arXiv.org, revised Oct 2026.
  • Handle: RePEc:arx:papers:2609.39256
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2609.39256
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:spo:wpmain:info:hdl:2441/5rkqqmvrn4tl22s9mc4c7eg1p is not listed on IDEAS
    2. Benjamin Jourdain & Gudmund Pammer, 2024. "An extension of martingale transport and stability in robust finance," Post-Print hal-04075283, HAL.
    3. ShengQuan Zhou, 2024. "Markov-Functional Models with Local Drift," Papers 2411.15053, arXiv.org.
    4. Mathias Beiglböck & Gudmund Pammer & Walter Schachermayer, 2022. "From Bachelier to Dupire via optimal transport," Finance and Stochastics, Springer, vol. 26(1), pages 59-84, January.
    5. Benjamin Jourdain & Alexandre Zhou, 2020. "Existence of a calibrated regime switching local volatility model," Mathematical Finance, Wiley Blackwell, vol. 30(2), pages 501-546, April.
    6. Guillaume Carlier & Alfred Galichon & Filippo Santambrogio, 2010. "From Knothe's transport to Brenier's map and a continuation method for optimal transport," Post-Print hal-01023796, HAL.
    7. Beatrice Acciaio & Antonio Marini & Gudmund Pammer, 2023. "Calibration of the Bass Local Volatility model," Papers 2311.14567, arXiv.org, revised Jul 2025.
    8. Guillaume Carlier & Alfred Galichon & Filippo Santambrogio, 2010. "From Knothe's transport to Brenier's map and a continuation method for optimal transport," SciencePo Working papers hal-01023796, HAL.
    9. Walter Farkas & Francesco Ferrari & Urban Ulrych, 2022. "Pricing Autocallables under Local-Stochastic Volatility," Swiss Finance Institute Research Paper Series 22-71, Swiss Finance Institute.
    10. Beatrice Acciaio & Antonio Marini, 2026. "Fixed Points for the $q$-Bass Martingale: Existence, Stability, and Convergence," Papers 2609.07351, arXiv.org.
    11. Ivan Guo & Grégoire Loeper & Shiyi Wang, 2022. "Calibration of local‐stochastic volatility models by optimal transport," Mathematical Finance, Wiley Blackwell, vol. 32(1), pages 46-77, January.
    12. Guillaume Carlier & Alfred Galichon & Filippo Santambrogio, 2010. "From Knothe's transport to Brenier's map and a continuation method for optimal transport," Sciences Po Economics Publications (main) hal-01023796, HAL.
    13. Beatrice Acciaio & Antonio Marini, 2026. "Existence of $q$-Bass martingales in the semidiscrete setting," Papers 2607.15872, arXiv.org.
    14. repec:spo:wpecon:info:hdl:2441/5rkqqmvrn4tl22s9mc4c7eg1p is not listed on IDEAS
    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. Max Cytrynbaum & Fredrik Savje, 2026. "Coupling Designs for Randomized Experiments with Complex Treatments," Papers 2604.09858, arXiv.org, revised Jul 2026.
    2. Mathias Beiglböck & George Lowther & Gudmund Pammer & Walter Schachermayer, 2024. "Faking Brownian motion with continuous Markov martingales," Finance and Stochastics, Springer, vol. 28(1), pages 259-284, January.
    3. Christoph Reisinger & Maria Olympia Tsianni, 2023. "Convergence of the Euler--Maruyama particle scheme for a regularised McKean--Vlasov equation arising from the calibration of local-stochastic volatility models," Papers 2302.00434, arXiv.org, revised Aug 2023.
    4. Samuel Daudin, 2022. "Optimal Control of Diffusion Processes with Terminal Constraint in Law," Journal of Optimization Theory and Applications, Springer, vol. 195(1), pages 1-41, October.
    5. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    6. Martin Larsson & Shukun Long, 2024. "Markovian projections for It\^o semimartingales with jumps," Papers 2403.15980, arXiv.org.
    7. Martin Larsson & Shukun Long, 2024. "Inverting the Markovian projection for pure jump processes," Papers 2412.04589, arXiv.org, revised Nov 2025.
    8. Mathias Beiglbock & George Lowther & Gudmund Pammer & Walter Schachermayer, 2021. "Faking Brownian motion with continuous Markov martingales," Papers 2109.12927, arXiv.org.
    9. Christoph Reisinger & Maria Olympia Tsianni, 2025. "Numerical analysis of a particle system for the calibrated Heston-type local stochastic volatility model," Papers 2504.14343, arXiv.org.
    10. Ludovic Goudenege & Andrea Molent & Xiao Wei & Antonino Zanette, 2026. "Market-Informed Valuation of GMMB Riders with Surrender Options under a Heston Stochastic-Local Volatility Model," Papers 2608.28397, arXiv.org.
    11. Manuel Hasenbichler & Benjamin Joseph & Gregoire Loeper & Jan Obloj & Gudmund Pammer, 2023. "The Martingale Sinkhorn Algorithm," Papers 2310.13797, arXiv.org, revised Mar 2026.
    12. Beiglböck, Mathias & Pammer, Gudmund & Riess, Lorenz, 2026. "Change of numeraire for weak martingale transport," Stochastic Processes and their Applications, Elsevier, vol. 192(C).
    13. Alexandre Alouadi & Gr'egoire Loeper & C'elian Marsala & Othmane Mazhar & Huy^en Pham, 2026. "SBBTS: A Unified Schr\"odinger-Bass Framework for Synthetic Financial Time Series," Papers 2604.07159, arXiv.org.
    14. Shaosai Huang, 2026. "Stability of Change-of-Num\'eraire Reweighting: An Exact Wasserstein Boundary," Papers 2609.30329, arXiv.org.
    15. Zejun Sun & Guang-Hui Zheng, 2023. "Solving linear Bayesian inverse problems using a fractional total variation-Gaussian (FTG) prior and transport map," Computational Statistics, Springer, vol. 38(4), pages 1811-1849, December.
    16. Christian Bayer & Denis Belomestny & Oleg Butkovsky & John Schoenmakers, 2024. "A reproducing kernel Hilbert space approach to singular local stochastic volatility McKean–Vlasov models," Finance and Stochastics, Springer, vol. 28(4), pages 1147-1178, October.
    17. Scander Mustapha, 2024. "Strong existence and uniqueness of a calibrated local stochastic volatility model," Papers 2406.14074, arXiv.org.
    18. Hao Qin & Ruozhong Yang & Charlie Che & Liming Feng, 2026. "Arbitrage-Free Multi-Maturity Risk-Neutral Marginals," Papers 2607.06204, arXiv.org.
    19. Mathias Beiglböck & Gudmund Pammer & Walter Schachermayer, 2022. "From Bachelier to Dupire via optimal transport," Finance and Stochastics, Springer, vol. 26(1), pages 59-84, January.
    20. Christa Cuchiero & Guido Gazzani & Janka Möller & Sara Svaluto‐Ferro, 2025. "Joint calibration to SPX and VIX options with signature‐based models," Mathematical Finance, Wiley Blackwell, vol. 35(1), pages 161-213, January.

    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:2609.39256. 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.