Awesome AI4Finance
ChatGPT for FinTech
FinRL Blogs
A good survey paper:
Hambly, Ben, Renyuan Xu, and Huining Yang. "Recent advances in reinforcement learning in finance." arXiv preprint arXiv:2112.04553, 2021.
Selection Criteria
It is a byproduct from our weekly meetings, may be useful for newcomers.
The selection procedure is as follows: 1). recommendation from group members, 2). evaluation by core members after survey, 3). discussion and evalutation at our weekly meetings.
Financial Big Data
Giller, Graham L. Adventures in Financial Data Science: The empirical properties of financial data and some other things that interested me. Vol. 1. Giller Investments (New Jersey), LLC, 2020.
Data Source
Project |
Stars |
Recommendation |
Description |
FinRL-Meta |
550+ |
:star::star::star::star::star: |
A metaverse for financial deep reinforcement learning. Now providing dynamic market environments for stock, cryptocurrency, forex, paper/live trading, etc. |
CCXT |
26.9k |
:star::star::star::star::star: |
A JavaScript/Python/PHP crypto trading API |
StockSharp |
5.4k |
:star::star::star::star: |
Algorithmic trading for stock markets, forex, bitcoins and options |
TuShare |
11.9k |
:star::star::star: |
Crawling historical data of CN stocks |
yfinance |
8.5k |
:star::star::star: |
Provide market historical data, easy to connect and use |
Binance |
3.0k |
:star::star::star: |
A well developed crypto trading platform |
Alpaca |
1.7k |
:star::star::star: |
API for free stock trading, supporting paper/live trading |
WRDS |
96 |
:star::star: |
A python data access library for academic usage |
Features and Technical Indicators
Project |
Stars |
Recommendation |
Description |
TA-Lib |
7.3k |
:star::star::star::star::star: |
For trading software developers requiring to perform technical analysis of financial market data |
Clairvoyant |
2.3k |
:star::star::star: |
Identify and monitor social/historical cues for short term stock movement |
FinanceDatabase |
1.5k |
:star::star::star: |
Database of symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets |
Artificial Intelligence
Machine Learning
Project |
Stars |
Recommendation |
Description |
ML for Trading |
6.6k |
:star::star::star::star::star: |
A book shows how ML can add value to algorithmic trading strategies in a practical yet comprehensive way |
Qlib |
10.2k |
:star::star::star::star: |
An AI-oriented quantitative investment platform with full ML pipeline |
Stock-Prediction-Models |
5.8k |
:star::star::star::star: |
Machine learning and deep learning models for Stock forecasting |
TF Quant Finance |
3.6k |
:star::star::star: |
A TensorFlow library for quantitative finance by Google |
Adv_Fin_ML_Exercises |
1.4k |
:star::star::star: |
Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by Marcos Lopez De Prado |
AlphaPy |
840+ |
:star::star::star: |
A machine learning framework for both speculators and data scientists |
fin-ml |
400+ |
:star::star::star: |
Code to the case studies in the book Machine Learning and Data Science Blueprints for Finance |
stockpredictionai |
3.6k |
:star::star: |
A notebook of complete process for predicting stock price movements |
MLFinLab |
3.3k |
:star::star: |
Using ML to design strategies. Now close source, codes no longer available |
Reinforcement Learning
Project |
Stars |
Recommendation |
Description |
FinRL |
6.6k |
:star::star::star::star::star: |
The first open-source project for financial reinforcement learning, provide full pipeline of using DRL in financial tasks |
ElegantRL |
2.5k |
:star::star::star::star::star: |
Scalable and elastic deep reinforcement learning library using PyTorch |
tensortrade |
4.1k |
:star::star::star::star: |
An RL framework for training, evaluating, and deploying robust trading agents |
FinRL-Trading |
1.3k |
:star::star::star::star: |
Ensemble strategy and live trading using DRL |
gym-anytrading |
1.4k |
:star::star::star: |
OpenAI Gym trading environment |
Others
Project |
Stars |
Recommendation |
Description |
Finance
Stock Recommendation
Project |
Stars |
Recommendation |
Description |
ML_for_Stock_Recomm |
34 |
:star::star: |
A Practical Machine Learning Approach for Dynamic Stock Recommendation |
Trading
Project |
Stars |
Recommendation |
Description |
HFT-LOB-Trading-ML |
1.3k |
:star::star::star: |
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data. |
Portfolio Management
Project |
Stars |
Recommendation |
Description |
PyPortfolioOpt |
3.2k |
:star::star::star::star: |
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity |
OLPS |
300 |
:star::star: |
A toolbox for On-Line Portfolio Selection |
High Performance Computing
Project |
Stars |
Recommendation |
Description |
NumPy |
21.5k |
:star::star::star::star::star: |
The fundamental package for scientific computing with Python, used by many other python libraries |
Azure HPC |
:heavy_minus_sign: |
:star::star::star: |
Azure high-performance computing (HPC) for financial services, provided by Microsoft Azure |
Intepretation & Explainability
Trading Platform
Project |
Stars |
Recommendation |
Description |
QuantConnect |
7.0k |
:star::star::star::star: |
An algorithmic trading engine built for easy strategy research, backtesting and live trading |
HFT-LOB-Trading-ML |
1.3k |
:star::star::star: |
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data |
Rendering Tools
Project |
Stars |
Recommendation |
Description |
TradingGym |
1。1k |
:star::star::star: |
"A toolkit for training and backtesting the reinforcement learning algorithms". Has pretty good dynamic rendering. |
mplfinance |
2.5k |
:star::star::star: |
Using Matplotlib to visualize financial data and market data |
Rendering using Matplotlib and Gym |
- |
:star::star::star: |
A blog written by the main contributor of TensorTrading |
Feedback: If you have any ideas or you want any other content to be added to this list, feel free to recommend.