Recommender Trading Bot

This project demonstrates a simple trading advice pipeline that takes into account 30 day forward forecasts of company share prices and by extension, when certain simple moving average (SMA) indicator cross over. Potential buy and sell signals are collated for all companies and then emailed to a given address with information on:

• stock name
• when key indicators are forecast to cross

Simple trading Strategy

• Buy signal: when SMA_50 positively crosses SMA_200
• Short signal: when SMA_10 negatively crosses SMA_50

Instructions on running the code

1. Setup local database

   • example uses MYSQL with a named database called stocks
   • [TODO] add integration to GCP

2. Setup API key with AMERITRADE

   • needed to get access to all tickers on NYSE
   • go to https://www.tdameritrade.com/home.html
   • open free account to get api token
   • [TODO] find data source api to LSE

3. Fill on config

   • rename config.json.dist to config.json in config/ folder
   • fill in missing details

4. Pull and save historical share price data

   • run python3 main.py -b

5. Forecast for signals

   • run python3 main.py -f
   • will persist buy and sell signals to file in data/

6. Email signals

   • run python3 main -e
   • will email signals

7. Persist signals

   • run python3 main -p
   • persist buy/sell signals to table recommendations

Automating process with Airflow

8. Setup airflow locally
   • there are numerous websites to help setup airflow
   • currently this has been done on mac
   • once setup, copy trading_bot_dag.py into dags/ folder
   • change project paths for PROJECT_DIR and PYTHON_ENV
   • run dag

Note:

• PROJECT_DIR is the local directory that this project is located
• PYTHON_ENV is the python path for the virtual environment of this project

Disclaimer

This is my personal project aimed purely as a hobby to practice coding and to learn more about the stock market.

I take no responsibility for anyone's trading activities based off the recommendations from this work.