YUDA Score is a sophisticated financial analysis tool designed to evaluate stocks based on a wide range of financial metrics, providing investors and analysts with deep insights into a stock's overall attractiveness. The system integrates real-time data retrieval, metric computations, benchmarking against sector averages, and visualization to support data-driven investment decisions.

• Utilizes Yahoo Finance API to fetch fundamental stock and sector-level data.
• Retrieves financial statements, balance sheets, and cash flow reports.

• Computes key financial indicators across various categories:
  • Profitability: Net Margin, Operating Margin, Return on Assets (ROA), Return on Equity (ROE).
  • Liquidity: Quick Ratio, Current Ratio.
  • Risk Assessment: Debt-to-Equity Ratio, Interest Coverage Ratio.
  • Valuation: Price-to-Earnings (P/E) Ratio, Price-to-Book (P/B) Ratio, Dividend Yield.
  • Cash Flow Analysis: Cash Conversion Cycle, Free Cash Flow.

• Compares a stock's financial metrics with its sector peers.
• Computes sector averages and integrates them into scoring.

• Normalizes financial data to ensure comparability across different industries and market conditions.
• Detects and adjusts for extreme outliers.

• Generates a comprehensive stock attractiveness score by weighting financial categories.
• Categorizes stocks as:
  • ✅ Very Attractive (≥ 1.5)
  • 👍 Attractive (0.5 to 1.5)
  • 😐 Neutral (-0.5 to 0.5)
  • ❌ Unattractive (-1.5 to -0.5)
  • 🚨 Very Unattractive (< -1.5)

• Bar Charts for financial metric weights.
• Time-Series Stock Price vs. YUDA Score Trends.
• Sector Comparisons & Score Distributions.
• Interactive visualizations powered by Matplotlib.

├── data_fetcher.py          # Retrieves stock & sector financial data
├── metrics_manager.py       # Computes and normalizes financial metrics
├── sector_manager.py        # Manages stock sector comparisons
├── weights_manager.py       # Handles dynamic weighting for financial categories
├── plotter.py               # Generates financial data visualizations
├── config.py                # Configuration settings (symbols, weights, metrics)
├── app.py                   # Main script to execute the YUDA Score pipeline
├── requirements.txt         # Dependencies list
└── README.md                # Documentation

1. Clone the repository:

   git clone https://github.com/mertmetin1/yuda-score.git
   cd yuda-score

2. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate   # Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

To compute financial scores and visualize insights, run:

python app.py

• Financial Metric Reports 📑
• Sector Comparisons & Benchmarking 📊
• YUDA Score Calculations & Rankings 🎯
• Stock Valuation Trends & Graphs 📉

1. Data Collection: Fetches stock and sector financials.
2. Metric Normalization: Applies Z-score transformations.
3. Sector Comparisons: Evaluates company performance against industry norms.
4. Score Computation: Weighs different financial factors based on category importance.
5. Visualization: Displays results with plots and tables.

Using the following customizable weight configuration:

weights = {
    "profitability": 0.25,
    "liquidity": 0.20,
    "risk": 0.15,
    "return": 0.25,
    "valuation": 0.10,
    "cash_flow": 0.05
}

Each stock is scored based on:

YUDA Score = Σ (Z-Score of Financial Metric * Category Weight)

Higher scores indicate stronger financial health & investment potential.

• Modify Weights: Adjust importance of each financial category in config.py.
• Add New Metrics: Extend metrics_manager.py to include additional financial indicators.
• Change Sector Comparisons: Edit stock sector configurations in sector_manager.py.
• Enhance Visualizations: Customize charting options in plotter.py.

🔥 Enhance your stock analysis with YUDA Score today! 🚀