Last modified date: 2025-03-04

🔗 GitHub Repository: Alchemist on GitHub

What is Alchemist?

Alchemist is a high-performance, distributed automated trading system designed to seamlessly transition quantitative research into fully automated algorithmic trading strategies.

Built on Ray, Alchemist provides a scalable infrastructure for strategy execution, real-time order management, and seamless integration with market data and broker connections. Whether you’re a quantitative researcher, algorithmic trader, or hedge fund, Alchemist helps you deploy, manage, and scale trading strategies efficiently.

Why Alchemist?

🚀 Fast and Scalable – Built with Ray to handle large-scale trading strategies across multiple processes and nodes.

🔌 Seamless Integration – Connects easily to market data providers, brokers, and exchanges.

📈 Backtesting & Live Trading – Develop strategies, backtest them, and switch to live trading without rewriting code.

⚡ Real-Time Order Management – Handles execution, risk management, and portfolio exposure dynamically.

🔧 Customizable Strategy Framework – A modular system that allows users to develop and optimize their own strategies.

Alchemist is part of a broader quantitative trading ecosystem, providing a structured way to move from strategy research to live trading with minimal friction.

Why Do You Need Alchemist?

Problem: Gap from Research to Execution

Quantitative traders often struggle with the transition from research to live deployment due to:

• Scalability Issues – Traditional execution frameworks cannot handle large-scale strategies efficiently.
• Infrastructure Complexity – Research environments are often disconnected from live market execution.
• Computational Bottlenecks – High-performance backtesting and execution require parallelized, distributed computing.