Financial Planning

Use an API to obtain investment data, and analyze this data to create forward-looking prediction to guide portfolio allocation. Use these tools to evaluate the potential forward looking returns on a stock/bond investment, and evaluate the potential for retirement
after 30-year & 10-year periods.

Requirements

User Knowledge

• Github (for pulling the app)
• Command line interface knowledge (for running and launching the software and app)
• Basic statistical analysis
• Access to your own Alpaca API Key set
  • Obtain for free at Alpaca's Website
  • Select the Individual Account
  • Store these keys in a safe place!
  • You will need to import them to the app as a .env file

Main

• Python 3.7
• Jupyter Labs

Dependencies

• Pandas 1.3.2
• OS
• matplotlib inline
• requests
• json
• dotenv
• alpaca_trade_api
• MCForecastTools (a python app file that can be obtained from this repository)

Contributors & License

The code used to evaluate the trades within is written by Eamon (ZrowGz). The basic framework and requirements and initial codebase identifiable in the initial commit are provided by UW & Trilogy.

The portions of the code I created are available as open source and shareable, just give credit, per standards if utilizezd.

GNU Public License V3.0