This jupyter notebook will look at the future value of a portfolio of $15,000 invested in differently weighted combinations of 'NKE', 'T' and 'XON' stocks. The Monte Carlo Simulation will be used for forecasting and the Alpaca API will pull the historical data of the stocks of interest. Finally, a conclusion will be made about what distribution of stocks should yield the highest return.

To Run this you will need your own API key and API secret key for the Alpaca API. Set up an account at Alpaca for free and go to your paper account to find the keys for the API. Save these in a .env file in the same directory as this jupyter notebook and title them, ALPACA_API_KEY = 'Your Key Here' | ALPACA_SECRET_KEY = 'Your Key Here'

Language: Python 3.9.12

Libraries used:

Pandas - For the creation and visualization of Data Frames

Jupyter Labs - An ipython kernel for interactive computing in python

OS - Miscellaneous operating system interface

Dotenv - Module to load environment variables

Alpaca Trade API - API for the Alpaca trading platform

MC Forecast Tools - A copy of this module is included in the downloadable files for this project

If you are using an anaconda or a conda environment chances are pandas, os and jupyter labs are already installed in your virtual environment

If they are not then run:

    pip install pandas
    pip install jupyterlab
    pip install os

dotenv and alpaca_trade_api need to be installed separately as they do not come in the anaconda environment. You will need to run:

    pip install dotenv
    pip install alpaca-trade-api

A copy of the 'MCForecastTools.py' file is included in this repository.

To run this jupyter lab notebook you will need to use GitBash and navigate to where you have exported the files associated with this project.

Next you will need to type the following:

    jupyter lab --ContentsManager.allow_hidden=True

This will launch a Jupyter Labs notebook containing the working files with the allow_hidden permission to view .env files.

This notebook uses the Alpaca API and you will need the two keys stated above in the description: 'ALPACA_API_KEY' AND 'ALPACA_SECRET_KEY'. Create a new .env file and store the values here.

It should look something like this:

    ALPACA_API_KEY = '<YOUR KEY HERE>'
    ALPACA_SECRET_KEY = '<YOUR SECRET KEY HERE>'

Next open 'Three_Stock_Monte' and click the double arrow to run the notebook. Alternatively you can run each cell individually.

Make sure to follow the pseudocode to see the coding logic and fully understand what is being displayed.

Note - This may take a while to run as the Monte Carlo Simulation typically has a faily long run time. Expect around 1-2 minutes of waiting before notebook is complete.

Created by Silvano Ross while in the UW FinTech Bootcamp

Contact Info: email: [email protected] | GitHub | LinkedIn

MIT