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DYSANOS introduces a generative market model capable of simulating arbitrage-free option surfaces and spot price paths using machine learning techniques. By combining statistical arbitrage constraints with deep learning, it advances the field of quantitative finance where AI directly drives financial modeling rather than serving as an incidental tool. This work bridges the gap between theoretical mathematical finance and practical generative AI applications in high-frequency trading environments.
DYSANOS Generative Dynamic Smooth Arbitrage-free Non-parametric Option Surfaces
arXiv:2608.12587v2 Announce Type: replace-cross Abstract: This article presents with DYSANOS the first generative market model for smooth SANOS option surfaces for all strikes and expiries which are free of static arbitrage. Our model is designed to generate entire paths of daily spot and option prices for years in the future. We present a robust and useful if somewhat simplistic baseline in the form of an AR(1) model. We discuss model setup, data pipeline, and training and investigate market reconstruction, stability, and tail behavior. We illustrate model performance on 891 Option Metrics IvyDB S\&P Index surfaces from 2022-01-03 through to 2025-08-29. We also demonstrate how to construct numerically a risk-neutral density. As part of this we develop a new test for zero conditional means under a given measure. We show that for 100,000 simulated paths a trading universe of 48 options and spot is numerically free of dynamic arbitrage.
Abstract:This article presents with DYSANOS the first generative market model for smooth SANOS option surfaces for all strikes and expiries which are free of static arbitrage. Our model is designed to generate entire paths of daily spot and option prices for years in the future. We present a robust and useful if somewhat simplistic baseline in the form of an AR(1) model. We discuss model setup, data pipeline, and training and investigate market reconstruction, stability, and tail behavior. We illustrate model performance on 891 Option Metrics IvyDB S\&P Index surfaces from 2022-01-03 through to 2025-08-29. We also demonstrate how to construct numerically a risk-neutral density. As part of this we develop a new test for zero conditional means under a given measure. We show that for 100,000 simulated paths a trading universe of 48 options and spot is numerically free of dynamic arbitrage.
Mathematical Finance (q-fin.MF); Machine Learning (cs.LG)
arXiv:2608.12587 [q-fin.MF]
(or arXiv:2608.12587v2 [q-fin.MF] for this version)
https://doi.org/10.48550/arXiv.2608.12587 Focus to learn more arXiv-issued DOI via DataCite
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