/commodity-charter

An analysis app for commodities for trading futures and knockout certs

Primary LanguagePython

Commodity Charter Pro

Build and Test

A comprehensive financial analytics dashboard for commodity market analysis with advanced COT (Commitments of Traders) insights.

Commodity Charter Pro Screenshot

Features

  • Real-time Price Data: Integration with Yahoo Finance for up-to-date commodity prices
  • COT Analysis: Advanced analysis of CFTC Commitments of Traders data
  • Merchant Position Tracking: Analysis of commercial trader positions and their success rate
  • Signal Generation: Automated trading signals based on merchant positioning
  • Interactive Visualization: Bloomberg terminal-style interface with candlestick charts and technical indicators
  • Multiple Commodities: Support for major commodities including:
    • Crude Oil
    • Natural Gas
    • Gold
    • Silver
    • Copper
    • Corn
    • Soybeans
    • Wheat

Installation

Using Docker (Recommended)

  1. Clone the repository:

    git clone https://github.com/norandom/commodity-charter.git
cd commodity-charter

  2. Run with Docker Compose:

    docker-compose up --build

  3. Access the application at http://localhost:8501

Manual Installation

  1. Clone the repository:

    git clone https://github.com/norandom/commodity-charter.git
cd commodity-charter

  2. Create and activate a virtual environment:

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

  3. Install dependencies:

    pip install -r requirements.txt

  4. Run the application:

    streamlit run app.py

Configuration

Signal Ranges

Configure commodity-specific signal ranges in cot_signals.csv:

  • Bullish Range: Percentage of short positions indicating bullish signal
  • Bearish Range: Percentage of long positions indicating bearish signal

Development

Running Tests

pytest --cov=./ --cov-report=term-missing

Code Style

flake8 .

Docker Development

For development with hot-reload:

docker-compose up --build

Technical Details

Architecture

  • Frontend: Streamlit web interface
  • Data Sources:
    • Yahoo Finance API
    • CFTC (Commodity Futures Trading Commission)
  • Analysis:
    • 50-day trend analysis
    • Weekly signal generation
    • Merchant position correlation

Key Components

  1. Price Analysis

    • Candlestick/Line charts
    • 50-day moving average
    • Volume tracking

  2. COT Analysis

    • Merchant position percentages
    • Weekly signal generation
    • Position success rate tracking

  3. Open Interest Analysis

    • Trend change detection
    • Peak analysis
    • Correlation with price movements

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Data provided by Yahoo Finance and CFTC
  • Inspired by professional trading terminals
  • Built with Streamlit and Python