Search Results for author: Hongyang Yang

Found 5 papers, 4 papers with code

FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance

no code implementations7 Nov 2021 Xiao-Yang Liu, Hongyang Yang, Jiechao Gao, Christina Dan Wang

In this paper, we present the first open-source framework \textit{FinRL} as a full pipeline to help quantitative traders overcome the steep learning curve.


FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance

8 code implementations19 Nov 2020 Xiao-Yang Liu, Hongyang Yang, Qian Chen, Runjia Zhang, Liuqing Yang, Bowen Xiao, Christina Dan Wang

In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies.

reinforcement-learning Stock Market Prediction

DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News

4 code implementations20 Dec 2019 Xinyi Li, Yinchuan Li, Hongyang Yang, Liuqing Yang, Xiao-Yang Liu

In this paper, we propose a novel deep neural network DP-LSTM for stock price prediction, which incorporates the news articles as hidden information and integrates difference news sources through the differential privacy mechanism.

Stock Prediction Stock Price Prediction

Practical Deep Reinforcement Learning Approach for Stock Trading

5 code implementations19 Nov 2018 Xiao-Yang Liu, Zhuoran Xiong, Shan Zhong, Hongyang Yang, Anwar Walid

We explore the potential of deep reinforcement learning to optimize stock trading strategy and thus maximize investment return.


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