This project works to find what stock trading strategy is the most successful when given the choice between a machine, people on a subreddit, and company/stock metrics. An LSTM Neural Network was used to predict stocks for the machine learning method, WSB was used to make the decisions for the reddit method, and value metrics such as price-to-earnings and price-to-book were used for the algorithmic value investing strategy. You can check out my live dashboard and the performance/holdings of each account here.

1. Python 3.10 installed
2. A MYSQL Database named purchase_history
3. Initialized tables under the aliases:
   • algo_method
   • net_method
   • reddit_method
     • Can be done by calling db_initializer and changing the table name at the bottom
4. Run pip install -e .
5. Run pip install -r requirements.txt
6. Have filled in all the necessary information from config_template.py

1. Call bot.py
2. Choose which method to run
   • R = Reddit Method (WSB)
   • A = Algorithmic Method (Value Trading Strategy)
   • M = Machine Learning Method (LSTM time-series predictions)
3. Allow loading time to finish and purchases to be made
4. Check MYSQL tables to make sure purchases went through

1. Run sheet_writer.py by 4 a.m. (When account monitoring begins)
2. Run streamlit run app.py
   • Local and remote links will be given once run to check the app
   • Feel free to use my powershell scripts by exporting the XML file to the Task Scheduler