Research

The academic foundations of Convex Volatility Interpolation.

Working Paper, May 2026

The Maximum-Skew Constraint

In the wings of an implied-vol smile, no-butterfly-arbitrage is more than a floor on the implied PDF (or on the convexity): it is a cap on the skew. Concretely, the no-butterfly-arbitrage condition at any point reduces to a quadratic in the skew . Where this quadratic admits two real roots in the regime , the cap reads at any right-wing point, with mirror at the left; we call this the maximum-skew constraint. Under strict Lee [Lee 2004], this regime holds asymptotically in either wing. This note studies that quadratic, first in the linear-in-variance edge-knot case introduced by the CVI paper [Deschâtres 2026], then in full generality.

Abstract

In the wings of an implied-vol smile, no-butterfly-arbitrage is more than a floor on the implied PDF (or on the convexity): it is a cap on the skew. Concretely, the no-butterfly-arbitrage condition at any point reduces to a quadratic in the skew . Where this quadratic admits two real roots in the regime , the cap reads at any right-wing point, with mirror at the left; we call this the maximum-skew constraint. Under strict Lee [Lee 2004], this regime holds asymptotically in either wing. This note studies that quadratic, first in the linear-in-variance edge-knot case introduced by the CVI paper [Deschâtres 2026], then in full generality.

At the edge knot of CVI's cubic spline, linear-in-variance wing extrapolation forces . The CVI paper selected the smaller-magnitude root on practical grounds, leaving open whether any strike-arbitrage-free smile could lie on the larger-magnitude root. We close that gap via Lucic's pointwise strike-arbitrage slope bound [Lucic 2021], which sits strictly between and : the larger-magnitude root carries a vertical-spread arbitrage incompatible with strike-arbitrage-freeness. We further identify the constraint as the finite-strike form of Lee's asymptotic large-strike bound [Lee 2004]: strictly tighter than Lee at any finite knot, approaching Lee only as the knot moves deep into the tail, and propagating along the linear-extrapolated wing to give necessary-and-sufficient strike-arbitrage-freeness at and beyond the knot. Furthermore, an equivalent form free of the pathology at is given. The argument applies to any implied-volatility parametrization with linear-in-variance wing extrapolation.

Beyond CVI, the assumption is relaxed. Strict Lee gives the wing regime asymptotically; for asymptotically linear smooth tails with , including SVI/SSVI, the remaining real-root condition also holds asymptotically in either wing. The larger-magnitude root is excluded wherever such roots exist. Under Black-Scholes pricing, alone is pointwise (i.e., at each finite strike of the slice) necessary and sufficient for strike-arbitrage-freeness (mirror at the left); the name maximum-skew constraint thus becomes literal: in either wing, wherever the smaller-magnitude root exists, it is the maximum admissible skew. Without Black-Scholes, the combined form takes over, with butterfly binding for and the call-spread Mills threshold for , where is the convexity at which and coincide. Moving out along an asymptotic linear-in-variance wing, ; under the further assumption of eventually monotone convexity, , so the Mills-ratio bound is asymptotically non-binding. For parametrizations with positive fast-decaying convexity ( eventually and ; covering SVI and SSVI with ), the pointwise picture above extends asymptotically to a sufficient (not necessary) at-and-beyond form: a single-strike check against the CVI bound (sufficient since implies ) propagates strike arbitrage-freeness along the entire wing past the strike, with the closed form worked out for raw SVI.

Across the smile, the picture extends into the interior as a band on the skew when butterfly roots are real (automatic for any , since the interior is negative). At very marked W shapes near the money, the butterfly quadratic has no real roots and the constraint becomes a convexity floor . In short, butterfly arbitrage is best read as a cap or floor on the skew across the smile when real roots exist.

Risk Cutting Edge, February 2026

Convex Volatility Interpolation

Fast, accurate and arbitrage-free volatility surface fitting remains a core challenge for options desks. This paper presents convex volatility interpolation (CVI), a framework that casts the problem as quadratic programming in variance space, with intuitive parameters, bid-ask-aware penalties and rigorous treatment of the tails. CVI calibrates volatility surfaces in a fraction of a second.

Abstract

CVI (Convex Volatility Interpolation) is a novel approach to constructing and fitting implied volatility surfaces from observed market option prices. Its key innovation lies in reformulating the problem of fitting arbitrage-free volatility surfaces as an approximately convex optimization task. This allows the fitting process to leverage efficient convex solvers, offering both speed and robustness, and bridging the gap between flow and exotics fitters. Specifically, CVI uses a parameterization of the volatility surface in variance space, calibrated using quadratic programming (QP) with linear constraints. Its dual parameterization in cubic spline and B-spline spaces maps a set of intuitive parameters to the weights of basis functions. As CVI has no restrictions on the number of parameters, it can fit any volatility surface. The method works consistently across all underlyings without the need for hyperparameter tuning, relying on dimensionless numbers for the parameterization and fitting logic.

Risk Views, March 2026

A smooth fit for complex volatility surfaces

Mauro Cesa profiles the CVI methodology and its industry reception, with commentary from Vladimir Lucic (Marex Solutions) on CVI's applicability to flow and exotics desks.

SSRN Preprint, 2024

Convex Volatility Interpolation

Earlier preprint version of the paper.

Conferences

WBS 22nd Quantitative Finance Conference · Valletta, Malta · October 2026

Convex Volatility Interpolation (CVI), an arbitrage-free volatility surface fitting methodology