Topics / #trading-strategies

Trading-strategies projects on GitHub

Systematic trading strategies and quantitative finance research.

As of , the most-starred Trading-strategies projects on GitHub are awesome-quant (30.2K stars), backtrader (23.5K stars) and Lean (22.1K stars). GitHub.Locker tracks 12 Trading-strategies repositories with 177.1K stars combined. The fastest-growing on October 18 was machine-learning-for-trading, with +40 stars in a day.

12Projects
177.1KStars in total
+172Stars in a day
Browse in the catalog →github.com/topics/trading-strategies ↗

Hot right now

Most stars gained in a day · Oct 18

+40

machine-learning-for-trading

stefan-jansen/machine-learning-for-trading · ★ 21.5K

The code repository for Machine Learning for Trading, 3rd Edition by Stefan Jansen: an end-to-end workflow for building, testing, and deploying ML-driven trading strategies, from data sourcing to live execution.

+26

awesome-systematic-trading

paperswithbacktest/awesome-systematic-trading · ★ 14.8K

A curated list of resources for systematic (quantitative) trading: papers, libraries, packages, books, articles, videos, blogs and courses for finding, developing and running trading strategies.

+23

awesome-quant

wilsonfreitas/awesome-quant · ★ 30.2K

A curated list of libraries, packages and resources for quants - people doing quantitative finance: pricing, trading, backtesting, risk and market data.

+17

Lean

QuantConnect/Lean · ★ 22.1K

LEAN is QuantConnect's open-source, event-driven algorithmic trading engine, written in C# with Python support. You use it to build, backtest and live-trade strategies, with alternative data support out of the box.

The all-time top

12 projects · by stars

  1. #1 · wilsonfreitas/awesome-quant

    awesome-quant

    A curated list of libraries, packages and resources for quants - people doing quantitative finance: pricing, trading, backtesting, risk and market data.

    30.2K
  2. #2 · mementum/backtrader

    backtrader

    backtrader is a Python library for backtesting trading strategies: you write a strategy as code, run it against historical market data and measure how it would have performed before risking real money.

    23.5K
  3. #3 · QuantConnect/Lean

    Lean

    LEAN is QuantConnect's open-source, event-driven algorithmic trading engine, written in C# with Python support. You use it to build, backtest and live-trade strategies, with alternative data support out of the box.

    22.1K
  1. 4

    machine-learning-for-trading

    21.5Kstefan-jansen/machine-learning-for-trading · Jupyter Notebook

    The code repository for Machine Learning for Trading, 3rd Edition by Stefan Jansen: an end-to-end workflow for building, testing, and deploying ML-driven trading strategies, from data sourcing to live execution.

  2. 5

    abu

    19Kbbfamily/abu · Python

    This is 'abu' (阿布量化), an open-source Python framework for building, backtesting and running quantitative trading strategies across US/A-share/HK stocks, futures, options and cryptocurrencies like Bitcoin, using machine learning to optimize the strategies.

  3. 6

    awesome-systematic-trading

    14.8Kpaperswithbacktest/awesome-systematic-trading · Python

    A curated list of resources for systematic (quantitative) trading: papers, libraries, packages, books, articles, videos, blogs and courses for finding, developing and running trading strategies.

  4. 7

    gs-quant

    13.2Kgoldmansachs/gs-quant · Python

    GS Quant is a Python toolkit for quantitative finance built by Goldman Sachs quants on top of their risk transfer platform, used for derivative structuring, trading strategy development, and risk management.

  5. 8

    quant-trading

    11.1Kje-suis-tm/quant-trading · Python

    This is a Python repository of quantitative trading strategies — a collection of standalone scripts implementing technical indicators, pattern recognition, options strategies and statistical arbitrage for backtesting on historical market data.

  6. 9

    StockSharp

    10.9KStockSharp/StockSharp · C#

    StockSharp (S#) is a free, open-source platform for trading on any market worldwide - crypto exchanges, stocks, futures, options, forex, and Bitcoin - supporting both manual and algorithmic trading, including high-frequency strategies.

  7. 10

    gekko

    10.2Kaskmike/gekko · JavaScript

    Gekko is a Bitcoin trading and backtesting platform that connects to popular Bitcoin exchanges — a trading bot written in JavaScript that runs on Node.js.

  8. 11

    ict-trading-model

    323carreypro/ict-trading-model · Python

    ICT Trading Model is a Codex skill that combines multi-timeframe bias, liquidity mapping, premium/discount location, session context, displacement, market structure, and PD arrays into a strict ICT/SMC (Inner Circle Trader / Smart Money Concepts) setup-validation framework.

  9. 12

    bytex

    250BYTEX-TRADE/bytex · C#

    BYTEX is an open-source, event-driven algorithmic trading engine for .NET written in C#. You write a trading strategy once and run the exact same code unchanged against historical data (backtest), live data with simulated fills (sandbox/paper), or real exchange accounts (live), with fixed-point money and adapters for major crypto exchanges.

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