Agentic Trading Systems explores the emerging field of LLM-powered multi-agent architectures for algorithmic trading.

This practical guide teaches you how to design, build, and deploy multi-agent systems that integrate large language models with real-time market data. Using Python and LangGraph, you'll learn to construct intelligent agents capable of strategy development, debate, risk oversight, and live execution workflows.

What You'll Learn:
- How to architect multi-agent systems using LangGraph and LLM APIs
- Techniques for connecting agents to live market data feeds
- Methods for implementing strategy generation, evaluation, and risk management workflows
- Best practices for building robust, modular trading architectures
>Whether you are a quantitative developer, Python programmer, or AI engineer interested in applying large language models to financial markets, this book provides clear, step-by-step guidance and working code examples.

Focus is placed on practical implementation, system design principles, and responsible development rather than trading performance claims.

Ideal for readers with intermediate Python knowledge and an interest in AI, multi-agent systems, and algorithmic trading infrastructure.