FinRL: Financial Reinforcement Learning

License

Financial reinforcement learning (FinRL®) is the first open-source framework for financial reinforcement learning.

| Dev Roadmap | Stage | Users | Project | Description | |----|----|----|----|----| | 0.0 (Preparation) | Entry | Practitioners | FinRL-Meta| gym-style market environments | | 1.0 (Proof-of-Concept)| End-to-End | Developers | this repo | automatic pipeline | | 2.0 (Professional) | Advanced | Researchers and Experts | ElegantRL | algorithms | | 3.0 (Production) | Production | Institutions and Hedge Funds | FinRL-X | An AI-Native deployment |

FinGPT: an open-source project for financial large language models, designed for research and real-world FinTech applications.

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Outline

Overview
File Structure
Supported Data Sources
Installation
Status Update
Tutorials
Publications
News
Citing FinRL
Join and Contribute
- Contributors
- Sponsorship
LICENSE

Project Contributors

FinRL® is an open-source financial reinforcement learning framework developed by contributors from the AI4Finance community and maintained by the AI4Finance Foundation.

Key contributors include:

Hongyang (Bruce) Yang – research and development on financial reinforcement learning frameworks, market environments, and quantitative trading applications
[other contributors…]

Overview

FinRL has three layers: market environments, agents, and applications. For a trading task (on the top), an agent (in the middle) interacts with a market environment (at the bottom), making sequential decisions.

Videos FinRL at AI4Finance Youtube Channel.

FinRL Stock Trading 2026 Tutorial

Step 1: Clone the Repository

git clone https://github.com/AI4Finance-Foundation/FinRL.git
cd FinRL

Step 2: Create and Activate Virtual Environment

python3 -m venv venv
source venv/bin/activate

Step 3: Install FinRL

pip install -e .

Step 4: Run the Scripts

1. Data Download & Preprocessing

python examples/FinRL_StockTrading_2026_1_data.py

This script downloads DOW 30 stock data from Yahoo Finance, adds technical indicators (MACD, RSI, etc.), VIX, and turbulence index, then splits the data into training set (2014–2025) and trading set (2026-01-01 to 2026-03-20), saving them as train_data.csv and trade_data.csv.

2. Train DRL Agents

python examples/FinRL_StockTrading_2026_2_train.py

This script trains 5 DRL agents (A2C, DDPG, PPO, TD3, SAC) using Stable Baselines 3 on the training data. Trained models are saved to the trained_models/ directory.

3. Backtest

python examples/FinRL_StockTrading_2026_3_Backtest.py

This script loads the trained agents, runs them on the trading data, and compares their performance against two baselines: Mean Variance Optimization (MVO) and the DJIA index. Results are printed to the console and a plot is saved as backtest_result.png.

File Structure

The main folder finrl has three subfolders applications, agents, meta. We employ a train-test-trade pipeline with three files: train.py, test.py, and trade.py.

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

Supported Data Sources

|Data Source |Type |Range and Frequency |Request Limits|Raw Data|Preprocessed Data| | ---- | ---- | ---- | ---- | ---- | ---- | |Akshare| CN Securities| 2015-now, 1day| Account-specific| OHLCV| Prices&Indicators| |Alpaca| US Stocks, ETFs| 2015-now, 1min| Account-specific| OHLCV| Prices&Indicators| |Baostock| CN Securities| 1990-12-19-now, 5min| Account-specific| OHLCV| Prices&Indicators| |Binance| Cryptocurrency| API-specific, 1s, 1min| API-specific| Tick-level daily aggregated trades, OHLCV| Prices&Indicators| |CCXT| Cryptocurrency| API-specific, 1min| API-specific| OHLCV| Prices&Indicators| |EODhistoricaldata| US Securities| Frequency-specific, 1min| API-specific | OHLCV | Prices&Indicators| |IEXCloud| NMS US securities|1970-now, 1 day|100 per second per IP|OHLCV| Prices&Indicators| |JoinQuant| CN Securities| 2005-now, 1min| 3 requests each time| OHLCV| Prices&Indicators| |QuantConnect| US Securities| 1998-now, 1s| NA| OHLCV| Prices&Indicators| |RiceQuant| CN Securities| 2005-now, 1ms| Account-specific| OHLCV| Prices&Indicators| Sinopac | Taiwan securities | 2023-04-13~now, 1min | Account-specific | OHLCV | Prices&Indicators| |Tushare| CN Securities, A-share| -now, 1 min| Account-specific| OHLCV| Prices&Indicators| |WRDS| US Securities| 2003-now, 1ms| 5 requests each time| Intraday Trades|Prices&Indicators| |YahooFinance| US Securities| Frequency-specific, 1min| 2,000/hour| OHLCV | Prices&Indicators|

<!-- |Data Source |Type |Max Frequency |Raw Data|Preprocessed Data| | ---- | ---- | ---- | ---- | ---- | | AkShare | CN Securities | 1 day | OHLCV | Prices, indicators | | Alpaca | US Stocks, ETFs | 1 min | OHLCV | Prices, indicators | | Alpha Vantage | Stock, ETF, forex, crypto, technical indicators | 1 min | OHLCV & Prices, indicators | | Baostock | CN Securities | 5 min | OHLCV | Prices, indicators | | Binance | Cryptocurrency | 1 s | OHLCV | Prices, indicators | | CCXT | Cryptocurrency | 1 min | OHLCV | Prices, indicators | | currencyapi | Exchange rate | 1 day | Exchange rate | Exchange rate, indicators | | currencylayer | Exchange rate | 1 day | Exchange rate | Exchange rate, indicators | | EOD Historical Data | US stocks, and ETFs | 1 day | OHLCV | Prices, indicators | | Exchangerates | Exchange rate | 1 day | Exchange rate | Exchange rate, indicators | | findatapy | CN Securities | 1 day | OHLCV | Prices, indicators | | Financial Modeling prep | US stocks, currencies, crypto | 1 min | OHLCV | Prices, indicators | |

FinRL

Install / Use

README