Stock Portfolio Optimization

📌 Project Overview

This project is a Stock Portfolio Optimization tool that helps users optimize their investment portfolios. The backend is built using Flask, and it processes financial data stored in stock_data.csv, which has been extracted from Yahoo Finance using Python.

📂 Project Structure

├── templates/              # HTML templates for the frontend
├── app.py                  # Main Flask application
├── optimization.py         # Contains the portfolio optimization logic
├── stock_data.csv               # Pre-stored stock data extracted from Yahoo Finance
├── requirements.txt        # Required dependencies
├── README.md               # Project documentation

⚙️ Features

• Portfolio Optimization: Helps users allocate stocks efficiently on the basis of the historical data extracted from yahoo finance
• Optimization model: Uses two models to increase optimization accuracy and secure against single model failure.
• Flask API: Processes optimization requests and returns optimized values.
• Frontend Dashboard: Displays portfolio analytics and optimization results with interactive visualizations.

User Input

📊 Dashboard Information

The Dashboard provides an analytical view of:

• Stock analysis tab: Provides a comprehensive overview of individual stocks, including historical performance and key metrics.
• Risk-Return Analysis: Offers in-depth insights into the portfolio's composition, displaying risk-return analysis and asset distribution through interactive graphs.
• Historical Performance: Visualizes the improved portfolio after optimization, highlighting allocation adjustments for better performance..

🔧 Installation

1. Clone the repository:

   git clone <your-repo-link>
   cd <your-repo-folder>

2. Create a virtual environment (optional but recommended):

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

3. Install dependencies:

   pip install -r requirements.txt

4. Run the Flask application:

   python app.py

🛠 Technologies Used

• Python (Flask, Pandas, NumPy)
• Yahoo Finance API (for extracting stock data)
• HTML/CSS & JavaScript (for the frontend)
• Plotly (for data visualization on the dashboard)

📬 Contributions & Issues

Feel free to open an issue or pull request if you have suggestions or improvements!

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🚀 Happy Investing!