Paper: Forecasting Implied Volatility Surfaces with Latent Diffusion Models
chaumian · x · 2026-08-25
A new paper titled 'Arbitrage-Aware Multi-Step Forecasting of Implied Volatility Surfaces' proposes a conditional latent diffusion framework. It generates joint 30-step trajectories of implied volatility surfaces and underlying returns. An arbitrage-aware autoencoder learns a low-dimensional surface representation, while the diffusion model captures conditional joint evolution. Evaluated on SPX data, the framework generates realistic probabilistic scenarios while outperforming the persistence benchmark in point forecasting.
More from Research
- LLM writing quality may require human-like Theory of Mind and embodiment — joshua_saxe · 2026-08-25
- LLMs Internal Competence Estimate Steers Answer Complexity — rohanpaul_ai · 2026-08-25
- Boston Dynamics demo sparks debate on robotics research — KyleMorgenstein · 2026-08-25
- Task-CoEvolve Cuts LLM Evaluation Costs by 80% via Adaptive Task Selection — hal-utokyo · 2026-08-25
- MIT proposes dynamic compression to fix info loss in long-context recurrent models — burkov · 2026-08-25
- AI in physical sciences shares the same bottleneck: missing data and feedback loops — AnneliesGamble · 2026-08-25