Latent-Space No-Arbitrage Geometry of Generative Models for Implied Volatility Surfaces

arXiv:2609.00332 · q-fin.CP, cs.AI, cs.LG, cs.NA, math.NA · Submitted 2026-08-31 · Read on arXiv

q-fin.CP, cs.AI, cs.LG, cs.NA, math.NA

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Admissibility — 14× in this paper · explained in 2 episodes
• Latent Space — 12× in this paper · explained in 7 episodes
• Generative Model — 10× in this paper · explained in 2 episodes
• Generative Models — 9× in this paper · explained in 2 episodes
• Reconstruction Error — 6× in this paper · explained in 2 episodes
• Initial Data — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Degeneracy — 2× in this paper · explained in 3 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Approximation Bound — 1× in this paper · explained in 1 episode
• Decode — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Latent Flow Matching for Arbitrage-Aware Implied Volatility Surface Generation
• Forecasting implied volatility surface with generative diffusion models
• Auto-Encoding Variational Bayes
• Computing Volatility Surfaces using Generative Adversarial Networks with Minimal Arbitrage Violations
• Controllable Generation of Implied Volatility Surfaces with Variational Autoencoders

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