OpenClaw Trading Documentation
==============================

OpenClaw Trading is an AI-powered multi-agent trading system that uses LangGraph workflow orchestration to coordinate multiple specialized trading agents. The system implements a gamified economic model where agents must pay for their decisions and trades, creating a survival-of-the-fittest environment.

Key Features
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* **Multi-Agent Architecture**: Specialized agents for market analysis, sentiment analysis, fundamental analysis, risk management, and trading
* **LangGraph Workflow**: State-driven workflow orchestration with parallel analysis and debate mechanisms
* **Economic Tracking**: Each agent pays for decisions and trades, with survival status tracking
* **Backtesting Engine**: Comprehensive backtesting with performance analytics
* **Factor System**: Basic and advanced trading factors with unlocking mechanisms
* **Learning System**: Course-based skill improvement for agents
* **Web Dashboard**: Real-time monitoring and visualization
* **Work-Trade Balance**: Agents can work to earn money when trading performance is poor

Quick Links
-----------

* :doc:`quickstart` - Get started with OpenClaw Trading in 5 minutes
* :doc:`architecture` - Understand the system architecture
* :doc:`api` - API reference for all public classes and methods
* :doc:`deployment` - Deploy OpenClaw Trading to production

Table of Contents
-----------------

.. toctree::
   :maxdepth: 2
   :caption: Getting Started

   quickstart
   installation
   examples

.. toctree::
   :maxdepth: 2
   :caption: User Guide

   architecture
   agents
   workflow
   factors
   learning
   backtesting

.. toctree::
   :maxdepth: 2
   :caption: API Reference

   api

.. toctree::
   :maxdepth: 2
   :caption: Operations

   deployment
   monitoring
   configuration

Indices and Tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`