Forecasting implied volatility surface with generative diffusion models

We introduce a conditional Denoising Diffusion Probabilistic Model (DDPM) for generating one-day-ahead approximately arbitrage-free implied volatility surfaces. To capture the path-dependent nature of volatility dynamics, we condition our model on a set of market variables, including exponentially w