Hou-Yu Zou

FrontierStep-RL: Fixed-Dimensional Structured Actions for Transaction-Cost-Aware Portfolio Reinforcement Learning

This study proposes FrontierStep-RL, which replaces the direct N-dimensional action with two bounded variables: a frontier coordinate and a rebalancing step, which supports fixed-dimensional target selection and controlled execution for scalable, transaction-cost-aware portfolio RL.