Python application serving as a quick and dirty prototype to use quantitive security analysis & Monte Carlo simulation to identify potentially profitable stock trades and place order in Alpaca Paper Trading Account directly via API.
In the future, more parts can be gradually added to this prototype such as: connecting with Database/SQL, using AI / machine-learning to identify potentially profitable trades, expanding to crypto & futures/options trading etc
The ultimate goal is to build a paper trading verified algorithmic trading application for realtime trading (for example connecting with Robin-hood live trading act)
This project leverages python 3.7 +, fire, questionary, pathlib
Before running the application, first make sure below libaries are installed
pip install fire
pip install questionaryAlerternatively you can simply just install requirement file included in this folder
pip install -r requirement.txtStep 1: run paper_trading_with_alpaca_api.ipynb
python paper_trading_with_alpaca_api.ipynbStep 2: use api key and secret key from alpaca to get account info (account cash balance, purchasing power etc)
Step 3: place an order to buy AAPL stock 10 shares, at market price, gtc
Step 4 go to alpaca account to check the order being placed
Brought to you by TaoNYC. connorchen7@gmail.com
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