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Investment Optimization Program

Overview

The Investment Optimization Program is designed to assist in making strategic investment decisions. It leverages various algorithms - Brute Force, Glouton (Greedy), and Dynamic Programming - to analyze and select the best combination of stock actions that maximize profit while adhering to a specified budget.

Features

  • Data Processing: Loads and cleans stock action data from a CSV file.
  • Algorithm Selection: Offers the choice of three distinct algorithms:
    • Brute Force: Exhaustively searches all possible combinations of actions.
    • Glouton (Greedy): Utilizes a greedy approach for quick and effective decision-making.
    • Dynamic Programming: Applies a more sophisticated method to solve the problem efficiently.
  • Result Visualization: Displays the best combination of actions, total profit, and investment cost.

How to Use

  1. Clone the Repository
git clone https://github.com/kenza12/Projet-7.git
cd Projet-7
  1. Set Up Your Environment
  • Ensure Python 3 is installed on your system.
  • Create a virtual environment:
  python3 -m venv venv

  • Activate the virtual environment:

    • On Windows: venv\Scripts\activate
    • On macOS/Linux: source venv/bin/activate

  • Install dependencies:

  pip install -r requirements.txt
  1. Run the Program

Execute the script with the desired algorithm and data file:

python main.py path/to/your/datafile.csv [algorithms]

Replace [algorithms] with one or more of the following: bruteforce, glouton, dynamic.

  1. View Results

The program will output the most profitable combination of actions based on the chosen algorithm.

Dependencies

  • Python 3
  • Pandas
  • Numpy
  • tabulate