Arbitrage-Free Option Price Surfaces via Chebyshev Tensor Bases and a Hamiltonian Fog Post-Fit
Robert Jenkinson Alvarez

TL;DR
This paper introduces a novel method for constructing arbitrage-free option price surfaces using Chebyshev tensor bases combined with a local risk-neutral density fog layer, ensuring high accuracy and stability even in stressed market conditions.
Contribution
The paper presents a new integrated approach that combines global Chebyshev representations with a local Hamiltonian fog layer to enforce no-arbitrage conditions and improve fit quality in noisy data environments.
Findings
Achieves 98-99% inside-spread coverage in stable markets.
Maintains static no-arbitrage violations below 1%.
Provides controlled out-of-band deviations during stressed periods.
Abstract
We study the construction of arbitrage-free option price surfaces from noisy bid-ask quotes across strike and maturity. Our starting point is a Chebyshev representation of the call price surface on a warped log-moneyness/maturity rectangle, together with linear sampling and no-arbitrage operators acting on a collocation grid. Static no-arbitrage requirements are enforced as linear inequalities, while the surface is fitted directly to prices via a coverage-seeking quadratic objective that trades off squared band misfit against spectral and transport-inspired regularisation of the Chebyshev coefficients. This yields a strictly convex quadratic program in the modal coefficients, solvable at practical scales with off-the-shelf solvers (OSQP). On top of the global backbone, we introduce a local post-fit layer based on a discrete fog of risk-neutral densities on a three-dimensional lattice…
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Taxonomy
TopicsStochastic processes and financial applications · Mathematical Approximation and Integration · Stochastic Gradient Optimization Techniques
