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Learn to build an AI agent application that implements a trading strategy using Connor RSI, a sophisticated technical indicator that enhances traditional momentum analysis. Explore the three components that make Connor RSI superior to standard RSI and discover how each component provides unique insights into market momentum. Master the practical interpretation of buy and sell signals while developing an automated analysis system using LangGraph and OpenAI integration. Build custom tools for calculating indicators and implement real-time data integration with Yahoo Finance APIs. Combine Connor RSI with Z-Score analysis for statistical confirmation and create a unified scoring system ranging from -100 to +100. Analyze real-world case studies including Tesla's volatility patterns and compare performance across different market conditions. Develop an intelligent trading assistant that automatically analyzes any financial symbol, combines multiple indicators for enhanced accuracy, and provides detailed explanations of each component's contribution to trading decisions. Utilize Python for core calculations, LangGraph for AI orchestration, Claude/OpenAI for intelligent analysis, yfinance for market data, Plotly for interactive visualizations, and Jupyter for experimentation and development.
