Stock Forecasting Portfolio

A comprehensive stock portfolio analysis and forecasting application built with Streamlit, featuring advanced analytics, risk management, and market sentiment analysis.

🌟 Features

• Portfolio Tracking: Monitor your stock portfolio performance in real-time
• Advanced Forecasting: Multiple forecasting models including:
  • ARIMA
  • GARCH
  • XGBoost
  • LightGBM
  • Ensemble Methods
  • Polynomial Regression
  • LSTM
• Risk Management:
  • Value at Risk (VaR) calculations
  • Maximum Drawdown analysis
  • Stop-loss recommendations
  • Risk-adjusted performance metrics
• Technical Analysis:
  • RSI
  • Moving Averages
  • MACD
  • Bollinger Bands
• Market Analysis:
  • Sector performance tracking
  • Market breadth indicators
  • Market sentiment analysis
• News Analysis:
  • Real-time news aggregation
  • Sentiment analysis
  • Source filtering
• Portfolio Optimization:
  • Modern Portfolio Theory
  • Efficient Frontier
  • Risk-adjusted returns

🚀 Getting Started

Prerequisites

• Python 3.8+
• pip (Python package installer)

Installation

1. Clone the repository:

git clone https://github.com/gamzeakkurt/stock-forecasting-portfolio.git
cd stock-forecasting-portfolio

2. Create a virtual environment (recommended):

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

3. Install required packages:

pip install -r requirements.txt

4. Run the application:

streamlit run app.py

📦 Dependencies

The project uses the following main libraries:

• Streamlit
• yfinance
• pandas
• numpy
• scikit-learn
• plotly
• prophet
• tensorflow
• talib
• xgboost
• lightgbm
• textblob
• vaderSentiment

📊 Usage

1. Launch the application using streamlit run app.py
2. Configure your portfolio in the sidebar
3. Select forecasting models and parameters
4. View various analyses and visualisations
5. Export reports in your preferred format

📈 Features in Detail

Portfolio Management

• Add/remove stocks
• Set quantity for each stock
• Track portfolio value over time
• Calculate returns and performance metrics

Forecasting

• Multiple model options for different forecasting needs
• Customizable forecast periods
• Confidence intervals
• Model comparison and evaluation

Risk Analysis

• Comprehensive risk metrics
• Portfolio optimisation
• Stop-loss recommendations
• Risk-adjusted performance analysis

Market Analysis

• Sector performance tracking
• Market breadth indicators
• Sentiment analysis
• News impact analysis

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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.

📧 Contact

Project Link: https://github.com/gamzeakkurt/stock-forecasting-portfolio