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This work proposes an optimization-based stratification framework for stratified sampling using optimal multi-way decision trees, and introduces reduction procedures for redundant candidate paths and assignment constraints, substantially reducing the optimization problem size.
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 erro...
In portfolio optimization, a cardinality constraint, which limits the number of assets held, plays a key role in cutting down monitoring and transaction costs. However, the resulting problem is NP-hard and becomes computationally difficult to solve globally as the number of candidate assets grows. Safe screening addres...
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