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Genetic Algorithm Simulator

Overview

This program implements a genetic algorithm to optimize a given model using historical stock data. It utilizes a simulation environment to evolve solutions through crossover and mutation processes, evaluating their performance over generations.

Installation

To install the required dependencies for this project, you should have Python 3.x installed. Create a virtual environment if needed, then use pip to install the packages listed in requirements.txt.

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

    python -m venv venv

  2. Activate the virtual environment:

    source venv/bin/activate

  3. Install the required packages:

    pip install -r requirements.txt

Usage

  1. Set up parameters:

    generation_size = 10
initial_amount = 100_000
generations = 10
ticker=["AAPL", "GOOGL"]

generation = []

  2. Run the program:

    python3 main.py

License

This project is licensed under the GPL v3 License. See the LICENSE file for details.