A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities

🔎 📈 🐍 💰 Backtest trading strategies in Python.

🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.

fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

LLM-powered trading agents that turn plain natural language into a five-pillar strategy: Trend, Mean-Reversion, Momentum, Volume, and Risk. Each strategy is hosted, self-evolving, configurable through 30+ tunable parameters, and bit-exact between backtest and live execution. Built for simulated Hyperliquid perpetuals.

Open agent skills and tool schemas for Superior Trade — build, backtest, and deploy trading strategies on Hyperliquid

Deterministic PineScript v6 backtest runtime. Validated trade-for-trade against TradingView.

BackTest and Run CryptoCurrency Trading Strategies

A reusable AI agent skill for quantitative analysis of A-share, HK, and US stocks, including market data, fundamentals, screening, factor calculation, and backtesting.

The fastest way from backtest to live trading.

Backtest and live trading in Python