Deep reinforcement learning for optimal trading with partial information

By Andrea Macrì, Sebastian Jaimungal, Fabrizio Lillo

Published 2025-11-04

Everscope rating

1831.9

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: DDPG with GRU for Optimal Trading under Partial Information. Problem types: Reinforcement Learning, Pairs Trading, Optimization, Time Series Forecasting, Classification, Algorithmic Execution.

arXiv:2511.00190 · Paper rankings

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