This project focuses on optimizing investment portfolios using brute force and optimized algorithms. The goal is to maximize profits while considering constraints like cost and return on investment over two years.
- Brute force algorithm for profit maximization.
- Optimized algorithm to handle larger datasets efficiently.
- Visual comparison of algorithm complexities.
- Portfolio and action management features.
Clone the repository:
git clone https://github.com/Loytifi/investment-optimizer.git
pip install -r requirements.txtUsage
Run the main script:
python main.py
Here is a simple example of how the program outputs a portfolio:
Selected Portfolio:
- Action: "TechCorp", Price: 200, Profit: 30%
- Action: "HealthInc", Price: 150, Profit: 25%
Total Cost: $350 Total Profit: $105