A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Repository Index
47,133 repositories indexed
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Python Backtesting library for trading strategies
- python
- trading
- backtesting
- metaclass
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
- c-sharp
- algorithmic-trading-engine
- quantconnect
- lean-engine
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
- machine-learning
- trading
- investment
- finance
Translated[🔥updating ...] AI automated quantitative trading robot (fully local deployment) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
- funds
- machine-learning
- pytrade
- quantitative-finance
Translatedstock. Get stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategies, stock verification and backtesting, automatic stock trading, supports PC and mobile devices.
- stock
- stocks
- backtest
- backtesting
Polly is a .NET resilience and transient-fault-handling library that allows developers to express policies such as Retry, Circuit Breaker, Timeout, Bulkhead Isolation, and Fallback in a fluent and thread-safe manner. From version 6.0.1, Polly targets .NET Standard 1.1 and 2.0+.
- circuit-breaker
- circuit-breaker-pattern
- resilience
- resiliency-patterns
Open-source feature management platform
- feature
- feature-toggle
- unleash
- feature-flags
Python toolkit for quantitative finance
- gs-quant
- goldman-sachs
- risk-management
- trading-strategies
Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
- trading-strategies
- quantitative-trading
- trading-bot
- quantitative-finance
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
- trading-strategies
- trading-robots
- trading-platform
- algorithmic-trading-engine
A curated list of practical financial machine learning tools and applications.
Free open source crypto trading bot to automate AI, Grid, DCA and TradingView strategies on Binance, Hyperliquid and 15+ exchanges, with a simple interface.
- trading-bot
- python
- bitcoin
- ai-trading
Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks
modular quant framework.
Quant/Algorithm trading resources with an emphasis on Machine Learning
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
- 3d-reconstruction
- depth-prediction
- feature-matching
- global-features
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
Strategies for cleaning databases in Ruby. Can be used to ensure a clean state for testing.
- testing
- ruby
- database-cleaner
- testing-tools
A Java library for technical analysis.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
- high-frequency-trading
- limit-order-book
- python
- machine-learning
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Strategies to Gekko trading bot with backtests results and some useful tools.
- gekko
- strategies
- gekko-strategies
- gekko-backtest
When Claude keeps giving you bad answers, make 100 versions of it fight to the death. Same task, 100 different strategies, a bracket, one answer left. Free Claude Code skill.