FrontierStep-RL: Fixed-Dimensional Structured Actions for Transaction-Cost-Aware Portfolio Reinforcement Learning
Portfolio reinforcement learning (RL) commonly represents each action as a complete asset-weight vector, causing the action dimension and exploration difficulty to grow with the investment universe. This study proposes FrontierStep-RL, which replaces the direct N-dimensional action with two bounded variables: a frontie...