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Trading Analysis Tools

This directory contains tools for analyzing trading performance, debugging AI decisions, and monitoring system behavior.

Tools Overview

Performance Analysis

  • trading_performance_analyzer.py - Comprehensive trading performance analysis
  • decision_quality_analyzer.py - AI decision quality scoring and pattern analysis
  • risk_metrics_calculator.py - Risk-adjusted performance metrics calculation

AI Decision Analysis

  • ai_reasoning_analyzer.py - Analyze AI decision-making patterns and reasoning quality
  • prompt_performance_tester.py - Test and compare different prompt strategies
  • decision_feedback_analyzer.py - Correlation between AI confidence and actual outcomes

Market Pattern Analysis

  • market_regime_detector.py - Identify market conditions and regime changes
  • symbol_performance_analyzer.py - Symbol-specific trading performance analysis
  • timing_pattern_analyzer.py - Analysis of trading timing and market hours impact

System Monitoring

  • order_execution_analyzer.py - Order execution quality and failure analysis
  • system_health_monitor.py - Trading system health and performance monitoring
  • real_time_dashboard.py - Real-time trading performance dashboard

Usage

Quick Performance Check

# Overall trading performance summary
python analysis/trading_performance_analyzer.py --summary

# AI decision quality analysis
python analysis/decision_quality_analyzer.py --recent-days 7

# Symbol-specific performance
python analysis/symbol_performance_analyzer.py --symbol BTCUSDT

Detailed Analysis

# Full performance report with charts
python analysis/trading_performance_analyzer.py --full-report --export-charts

# AI reasoning pattern analysis
python analysis/ai_reasoning_analyzer.py --analyze-patterns --export-report

# Market regime analysis
python analysis/market_regime_detector.py --detect-current --historical-analysis

Real-time Monitoring

# Start real-time dashboard
python analysis/real_time_dashboard.py --port 8080

# System health monitoring
python analysis/system_health_monitor.py --continuous

Configuration

All analysis tools use the same database and configuration:

  • Database: ../data/trading.db
  • Config: ../config/agent.yaml
  • Logs: ../logs/

Output Formats

  • Console: Colored terminal output with tables and metrics
  • JSON: Machine-readable format for integration
  • HTML: Rich reports with charts and visualizations
  • CSV: Raw data export for external analysis

Dependencies

# Install additional analysis dependencies
pip install plotly dash pandas numpy scikit-learn matplotlib seaborn

Contributing

When adding new analysis tools:

  1. Follow the naming convention: {category}_{tool_name}.py
  2. Include CLI argument support with --help
  3. Add both summary and detailed modes
  4. Support multiple output formats
  5. Update this README with usage examples

Future Enhancements

  • Machine learning model performance tracking
  • Automated anomaly detection alerts
  • Integration with external monitoring systems
  • Custom metric definitions and tracking
  • A/B testing framework for trading strategies