19 citations · 31 across the 3 of their papers we have counts for
3 papers
q-fin.TR2021★ 4 cited
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…
q-fin.TR2020★ 8 cited
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…
q-fin.ST2019★ 19 cited
DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
Xinyi Li, Yinchuan Li, Hongyang Yang +2
Stock price prediction is important for value investments in the stock market. In particular, short-term prediction that exploits financial news articles is promising in recent yea…