83 citations · 159 across the 12 of their papers we have counts for
4 papers · 1 filter
FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning
Xiao-Yang Liu, Ziyi Xia, Jingyang Rui +6
Finance is a particularly difficult playground for deep reinforcement learning. However, establishing high-quality market environments and benchmarks for financial reinforcement le…
FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance
Xiao-Yang Liu, Jingyang Rui, Jiechao Gao +5
Deep reinforcement learning (DRL) has shown huge potentials in building financial market simulators recently. However, due to the highly complex and dynamic nature of real-world ma…
FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance
Xiao-Yang Liu, Hongyang Yang, Jiechao Gao +1
Deep reinforcement learning (DRL) has been envisioned to have a competitive edge in quantitative finance. However, there is a steep development curve for quantitative traders to ob…
FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
Xiao-Yang Liu, Hongyang Yang, Qian Chen +4
As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners. However, to trai…