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Awesome List
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
GitHub stars and default-branch commits for wilsonfreitas/awesome-quant.
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Financial data platform for analysts, quants and AI agents.
Free, open source crypto trading bot
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
A cryptocurrency trading API with more than 100 exchanges in JavaScript / TypeScript / Python / C# / PHP / Go / Java
Extremely fast Query Engine for DataFrames, written in Rust
The fundamental package for scientific computing with Python.
Download market data from Yahoo! Finance's API
Python Backtesting library for trading strategies
AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Zipline, a Pythonic Algorithmic Trading Library
FinRL®: Financial Reinforcement Learning. 🔥
SciPy library main repository
A computer algebra system written in pure Python
Python training for business analysts and traders
"Vibe-Trading: Your Personal Trading Agent"
Python wrapper for TA-Lib (http://ta-lib.org/).
Statsmodels: statistical modeling and econometrics in Python
Python toolkit for quantitative finance
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
Bayesian Modeling and Probabilistic Programming in Python
Automatic extraction of relevant features from time series:
An advanced crypto trading bot written in Python
The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
Portfolio analytics for quants, written in Python
A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities
Portfolio and risk analytics in Python
Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
High-performance TensorFlow library for quantitative finance.
Probabilistic time series modeling in Python
Visualizer for pandas data structures
Technical Analysis Library using Pandas and Numpy
A python wrapper for Alpha Vantage API for financial data.
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Python Algorithmic Trading Library
Financial Markets Data Visualization using Matplotlib
Performance analysis of predictive (alpha) stock factors
Portfolio Optimization in Python
Free, open source, a high frequency trading and market making backtesting and trading bot, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books(Level-2 and Level-3), with real-world crypto trading examples for Binance and Bybit
modular quant framework.
150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data
A Python module for creating Excel XLSX files.
Algorithmic Trading in Python with Machine Learning
QuantStart.com - QSTrader backtesting simulation engine.
xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.
Systematic Trading in python
Hikyuu Quant Framework 基于C++/Python的超高速开源量化交易研究框架,同时可基于策略部件进行资产重用,快速累积策略资产。
Statistical and Algorithmic Investing Strategies for Everyone