Factor-Based Conditional Diffusion Model for Contextual Portfolio Optimization

ArXi:2509.22088v3 Announce Type: replace-cross We propose a novel conditional diffusion model for contextual portfolio optimization that learns the cross-sectional distribution of next-day stock returns conditioned on high-dimensional asset-specific factors. Our model leverages a Diffusion Transformer architecture with token-wise conditioning, which enables linking each asset's return to its own factor vector while capturing complex cross-asset dependencies.