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A simple python project where we use price data from the NASDAQ website to help optimize our portfolio of stocks using modern portfolio theory.

Right now, the library is not hosted on PyPi so you will need to do a local install on your system if you plan to use it in other scrips you use.

First, clone this repo to your local system. After you clone the repo, make sure to run the setup.py file, so you can install any dependencies you may need. To run the setup.py file, run the following command in your terminal.

pip install -e .

This will install all the dependencies listed in the setup.py file. Once done you can use the library wherever you want.

Here is a simple example of using the pyopt library to grab the index files for specific quarter.

import pandas as pd
from pyopt.client import PriceHistory

# Define the symbols
symbols = ['AAPL', 'MSFT', 'SQ']
number_of_symbols = len(symbols)

# Initialize the client.
price_history_client = PriceHistory(symbols=['AAPL','MSFT','SQ'])

# Dump it to a CSV file.
price_history_client.price_data_frame.to_csv(
    'stock_data.csv',
    index=False
)
pprint(price_history_client.price_data_frame)

Patreon: Help support this project and future projects by donating to my Patreon Page. I'm always looking to add more content for individuals like yourself, unfortuantely some of the APIs I would require me to pay monthly fees.

YouTube: If you'd like to watch more of my content, feel free to visit my YouTube channel Sigma Coding.