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Found 3 papers, 1 papers with code
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools
Specifically, the target stock pool of different investors varies dramatically due to their discrepancy on market states and individual investors may temporally adjust stocks they desire to trade (e. g., adding one popular stocks), which lead to customizable stock pools (CSPs).
Amortized Network Intervention to Steer the Excitatory Point Processes
Excitatory point processes (i. e., event flows) occurring over dynamic graphs (i. e., evolving topologies) provide a fine-grained model to capture how discrete events may spread over time and space.
Safe-FinRL: A Low Bias and Variance Deep Reinforcement Learning Implementation for High-Freq Stock Trading
In recent years, many practitioners in quantitative finance have attempted to use Deep Reinforcement Learning (DRL) to build better quantitative trading (QT) strategies.
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