S&P 100 Index Fund Optimizer

Project Description

This project implements an index fund optimization tool that tracks the S&P 100 using a smaller subset of stocks. It's part of the Artificial Intelligence Driven Decision Making (MSCAI1) course project.

Features

• Mathematical optimization using scipy's SLSQP optimizer
• Correlation-based stock selection for comparison
• Performance analysis across multiple time periods
• Interactive visualization of results

Installation

1. Create a virtual environment:

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

2. Install dependencies:

pip install -r requirements.txt

Usage

Run the Streamlit application:

streamlit run app.py

Project Structure

fundforge/
├── app/                 # Next.js application
├── components/          # React components
├── contracts/           # Smart contracts
├── public/             # Static assets
├── styles/             # Global styles
└── utils/              # Utility functions

License

MIT