Preprint
SANOS: smooth strictly arbitrage-free non-parametric option surfaces
- Abstract:
- We present a simple, numerically efficient but highly flexible non-parametric method to construct representations of option price surfaces which are both smooth and strictly arbitrage-free across time and strike. The method can be viewed as a smooth generalization of the widely-known linear interpolation scheme, and retains the simplicity and transparency of that baseline. Calibration of the model to observed market quotes is formulated as a linear program, allowing bid-ask spreads to be incorporated directly via linear penalties or inequalities, and delivering materially lower computational cost than most of the currently available implied-volatility surface fitting routines. As a further contribution, we derive an equivalent parameterization of the proposed surface in terms of strictly positive "discrete local volatility" variables. This yields, to our knowledge, the first construction of smooth, strictly arbitrage-free option price surfaces while requiring only trivial parameter constraints (positivity). We illustrate the approach using S&P 500 index options.
- Publication status:
- Published
- Peer review status:
- Not peer reviewed
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(Preview, Pre-print, pdf, 1.4MB, Terms of use)
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- Preprint server copy:
- 10.48550/arXiv.2601.11209
Authors
+ Natural Sciences and Engineering Research Council of Canada
More from this funder
- Funder identifier:
- https://ror.org/01h531d29
- Funding agency for:
- Kratsios, A
- Grant:
- DGECR-2023-00230
- RGPIN-2023-04482
+ European Commission
More from this funder
- Funder identifier:
- https://ror.org/00k4n6c32
- Funding agency for:
- Kratsios, A
- Programme:
- Bando PRIN 2022
+ Vector Institute
More from this funder
- Funder identifier:
- https://ror.org/03kqdja62
- Funding agency for:
- Kratsios, A
- Saqur, R
- Preprint server:
- arXiv
- Publication date:
- 2026-01-16
- DOI:
- Language:
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English
- Pubs id:
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2363634
- Local pid:
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pubs:2363634
- Deposit date:
-
2026-01-23
- ARK identifier:
Terms of use
- Copyright holder:
- Buehler et al.
- Copyright date:
- 2026
- Rights statement:
- © The Author(s) 2026. This work is made available under the Creative Commons Attribution 4.0 License.
- Licence:
- CC Attribution (CC BY)
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