68 lines
1.9 KiB
ReStructuredText
68 lines
1.9 KiB
ReStructuredText
OpenClaw Trading Documentation
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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.
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Key Features
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------------
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* **Multi-Agent Architecture**: Specialized agents for market analysis, sentiment analysis, fundamental analysis, risk management, and trading
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* **LangGraph Workflow**: State-driven workflow orchestration with parallel analysis and debate mechanisms
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* **Economic Tracking**: Each agent pays for decisions and trades, with survival status tracking
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* **Backtesting Engine**: Comprehensive backtesting with performance analytics
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* **Factor System**: Basic and advanced trading factors with unlocking mechanisms
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* **Learning System**: Course-based skill improvement for agents
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* **Web Dashboard**: Real-time monitoring and visualization
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* **Work-Trade Balance**: Agents can work to earn money when trading performance is poor
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Quick Links
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-----------
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* :doc:`quickstart` - Get started with OpenClaw Trading in 5 minutes
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* :doc:`architecture` - Understand the system architecture
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* :doc:`api` - API reference for all public classes and methods
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* :doc:`deployment` - Deploy OpenClaw Trading to production
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Table of Contents
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-----------------
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.. toctree::
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:maxdepth: 2
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:caption: Getting Started
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quickstart
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installation
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examples
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.. toctree::
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:maxdepth: 2
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:caption: User Guide
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architecture
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agents
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workflow
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factors
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learning
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backtesting
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.. toctree::
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:maxdepth: 2
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:caption: API Reference
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api
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.. toctree::
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:maxdepth: 2
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:caption: Operations
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deployment
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monitoring
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configuration
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Indices and Tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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