WGU Computer Science Capstone C964

Stock Price Prediction Model - v1.3

Andrew Castelli - #001488272

This Price Prediction Model was written using Python 3.9.1.

Constructed using a combination of PyCharm and Google Colab.

My hypothesis for this project is: If enough historical stock price data is available for any individual stock, then it can be used to train our recurrent neural network to then accurately predict future stock prices. Due to the strong correlations between prediction price and actual price, I confidently accept the hypothesis.

Try it for yourself:

• Make sure Python V3.6 or higher is on your device
• Check and/or download module requirements (requirements.txt).
• Download CapstoneProject folder from github

MacOS

Option 1

• Open Terminal in CapstoneProject folder or navigate to CapstoneProject folder
• Enter code 'python3 main.py' to run program
• Enter password 'luthor' to begin

Option 2

• Open CapstoneProject folder with PyCharm, Google Colab, or your IDE of choice
• Navigate to main.py python file
• Run main.py
• Enter password 'luthor' to begin

Windows

Option 1

• Open new Command Prompt (Windows key + X, click Command Prompt)
• Navigate to the directory you saved the CapstoneProject folder in
• Enter code 'python3 main.py' to run program
• Enter password 'luthor' to begin

Option 2

• Open CapstoneProject folder with PyCharm, Google Colab, or your IDE of choice
• Navigate to main.py python file
• Run main.py
• Enter password 'luthor' to begin

Python Module Requirements:

• psutil~=5.8.0
• yfinance~=0.1.55
• torch~=1.7.1
• numpy~=1.20.1
• pandas~=1.2.1
• matplotlib~=3.3.4
• sklearn~=0.0
• scikit-learn~=0.24.1