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Catalyst is an algorithmic trading library for crypto-assets written in Python, originally developed to let quants and developers design, backtest, and deploy trading strategies in a unified environment. It builds on top of Zipline, extending that ecosystem to support crypto exchanges and high-resolution historical data (daily and minute bars). Users can express strategies in Python, run backtests against historical price data, and analyze performance through built-in metrics and analytics to evaluate profitability, risk, and behavior under different market conditions. Beyond backtesting, Catalyst was designed to support live trading on multiple crypto exchanges such as Binance, Bitfinex, Bittrex, and Poloniex, bridging simulation and production within the same framework. The library includes a rich set of examples, Docker and conda configurations, and integration points for community resources like forums and Discord for sharing strategies and troubleshooting.
Features
- Python library for expressing, backtesting, and analyzing crypto trading strategies
- Built on top of Zipline to leverage an existing algorithmic trading ecosystem
- Historical data support with daily and minute resolution for realistic simulations
- Live trading integration with several major crypto exchanges
- Extensive examples, docs, and environment configs for Docker and conda setups
- Archived, read-only codebase that now serves as a reference for crypto algorithmic trading frameworks
Project Samples
