marketswimmer 2.0.16

Warren Buffett's Owner Earnings Analysis Tool - Calculate true economic earnings for any stock

MarketSwimmer - Owner Earnings Analysis Tool

A comprehensive tool for analyzing Warren Buffett's "Owner Earnings" from financial statement data.

📁 Directory Structure

MarketSwimmer/
├── 📊 charts/                  # Generated visualization charts
├── 📈 data/                    # CSV output files and analysis results
├── 📥 downloaded_files/        # Financial data Excel files from StockRow
├── 📝 logs/                    # Application logs
├── 🛠️ scripts/                # Utility and test scripts
├── 🚀 Main Applications
│   ├── market_swimmer_gui_clean.py      # Main GUI application
│   ├── analyze_ticker_gui.py           # Complete analysis workflow
│   ├── owner_earnings_fixed.py         # Core analysis engine
│   └── visualize_owner_earnings.py     # Chart generation
├── 🔧 Utilities
│   ├── open_charts.py                  # Chart viewer
│   ├── monitor_downloads.py            # Download automation
│   ├── auto_download.py               # Download helper
│   └── logger_config.py               # Logging configuration
└── 📋 Batch Files
    ├── launch_clean_gui.bat           # Start GUI
    ├── start_gui_safe.bat             # Safe startup
    └── [other .bat files]

🚀 Quick Start

1. Launch GUI: Double-click launch_clean_gui.bat
2. Select Ticker: Choose a stock symbol (e.g., AAPL, MSFT, BRK.B)
3. Download Data: System opens StockRow page for data download
4. Analyze: Automatic calculation of Owner Earnings
5. View Charts: Generated visualizations open automatically

📊 Output Files

• Charts: charts/[ticker]_*.png - Visual analysis charts
• Data: data/owner_earnings_*.csv - Raw analysis data
• Logs: logs/marketswimmer_*.log - Application logs

💡 Owner Earnings Formula

Owner Earnings = Net Income + Depreciation/Amortization - CapEx - Working Capital Changes

🎯 Features

• ✅ Ticker-specific analysis
• ✅ Annual and quarterly data processing
• ✅ Professional visualizations
• ✅ Automated chart generation
• ✅ Clean directory organization
• ✅ Comprehensive logging

📋 Requirements

• Python 3.12+
• pandas, matplotlib, seaborn
• PyQt6 (for GUI)
• Internet connection (for data download)