Academy notes
Articles and updates from SoloQuant Academy.
Tag: reinforcement-learning
Jiang, Xu & Liang (2017) map portfolio weights with EIIE nets, a Portfolio-Vector Memory for costs, and an explicit log-return reward on Poloniex 30-minute crypto. The FinRL-era template. Plain-language intro. Not investment advice.
Sen et al. (2023) compare mean–variance, López de Prado HRP, and deep Q-learning portfolios on NIFTY50 and Indian sector baskets. Plain-language intro. Not investment advice.
Sen et al. (2023) bake off mean–variance optimisation, hierarchical risk parity, and reinforcement-learning allocators on the same playground. Plain-language intro. Not investment advice.
Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.
Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.
Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.
Cheridito & Weiss (2025) use actor-critic RL to mix market and multi-level limit orders in impactful LOB simulations. Plain-language intro. Not investment advice.
Ning, Lin & Jaimungal (2018) apply Double Deep Q-Learning to optimal execution—RL as a study tool for how to finish a parent order under market impact. Plain-language intro. Not investment advice.
