Factor-Based Conditional Diffusion Model for Portfolio Optimization

Xuefeng Gao, Mengying He and Xuedong He

Papers from arXiv.org

Abstract: We propose a novel conditional diffusion model for portfolio optimization that learns the cross-sectional distribution of next-day stock returns conditioned on asset-specific factors. The model builds on the Diffusion Transformer with token-wise conditioning, linking each asset's return to its own factor vector while capturing cross-asset dependencies. Generated return samples are used for daily mean-variance optimization under realistic constraints. Empirical results on the Chinese A-share market show that our approach consistently outperforms benchmark methods based on standard empirical and shrinkage-based estimators across multiple metrics.

Date: 2025-09
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