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Decision-Focused Learning for Mean-Variance Portfolio Optimization via KKT-Based Reformulation

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Mean-variance portfolio optimization (MVO) is a central framework in data-driven asset management. A widely adopted approach is a two-stage framework that first predicts expected returns and then solves the optimization problem based on these predictions, with the predictive models trained by minimizing prediction errors. However, this objective of prediction is not aligned with the quality of the downstream portfolio decision. Decision-focused learning (DFL), which directly minimizes the downstream decision loss within the learning process, has thus emerged as a promising direction. However,

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