FinRL®: Financial Reinforcement Learning

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FinRL├── finrl (main folder)│   ├── applications│   ├── Stock_NeurIPS2018│   ├── imitation_learning│   ├── cryptocurrency_trading│   ├── high_frequency_trading│   ├── portfolio_allocation│   └── stock_trading│   ├── agents│   ├── elegantrl│   ├── rllib│   └── stablebaseline3│   ├── meta│   ├── data_processors│   ├── env_cryptocurrency_trading│   ├── env_portfolio_allocation│   ├── env_stock_trading│   ├── preprocessor│   ├── data_processor.py│       ├── meta_config_tickers.py│   └── meta_config.py│   ├── config.py│   ├── config_tickers.py│   ├── main.py│   ├── plot.py│   ├── train.py│   ├── test.py│   └── trade.py│├── examples├── unit_tests (unit tests to verify codes on env & data)│   ├── environments│   └── test_env_cashpenalty.py│   └── downloaders│   ├── test_yahoodownload.py│   └── test_alpaca_downloader.py├── setup.py├── requirements.txt└── README.md

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Citing FinRL

@article{dynamic_datasets,    author = {Liu, Xiao-Yang and Xia, Ziyi and Yang, Hongyang and Gao, Jiechao and Zha, Daochen and Zhu, Ming and Wang, Christina Dan and Wang, Zhaoran and Guo, Jian},    title = {Dynamic Datasets and Market Environments for Financial Reinforcement Learning},    journal = {Machine Learning - Springer Nature},    year = {2024}}

@article{liu2022finrl_meta,  title={FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning},  author={Liu, Xiao-Yang and Xia, Ziyi and Rui, Jingyang and Gao, Jiechao and Yang, Hongyang and Zhu, Ming and Wang, Christina Dan and Wang, Zhaoran and Guo, Jian},  journal={NeurIPS},  year={2022}}

@article{liu2021finrl,    author  = {Liu, Xiao-Yang and Yang, Hongyang and Gao, Jiechao and Wang, Christina Dan},    title   = {{FinRL}: Deep reinforcement learning framework to automate trading in quantitative finance},    journal = {ACM International Conference on AI in Finance (ICAIF)},    year    = {2021}}

@article{finrl2020,    author  = {Liu, Xiao-Yang and Yang, Hongyang and Chen, Qian and Zhang, Runjia and Yang, Liuqing and Xiao, Bowen and Wang, Christina Dan},    title   = {{FinRL}: A deep reinforcement learning library for automated stock trading in quantitative finance},    journal = {Deep RL Workshop, NeurIPS 2020},    year    = {2020}}

@article{liu2018practical,  title={Practical deep reinforcement learning approach for stock trading},  author={Liu, Xiao-Yang and Xiong, Zhuoran and Zhong, Shan and Yang, Hongyang and Walid, Anwar},  journal={NeurIPS Workshop on Deep Reinforcement Learning},  year={2018}}

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