Pytrader

A simple 3-part CLI for executing on a single trading strategy.

1. Signal Scanner: Utilizes Yahoo finance to identify and create signals
2. Signal Responder: Responds to signals and places orders with a broker (Alpaca at the moment)
3. Order Monitor: Keeps order data in sync with the broker

Disclaimer This is a proof of concept developed by someone with no professional trading experience. Past performance is not indicative of future results.

Usage

1. Create a virtual environment: python -m venv .pytrader
2. Activate the virtual vironment: source $(pwd)/.pytrader/bin/activste
3. Install poetry: pip install poetry
4. Install app dependencies: poetry install
5. Copy scripts/example.env to a safe place and update its values
6. Execute pytrader: python pytrader/main.py or poetry run pytrader

Signal Scanner

Usage: main.py rsi [OPTIONS]

  Calculate RSI signals for all tickers in the S&P 500.

Options:
  --refresh  Force refresh of RSI signals.
  --help     Show this message and exit.

Process Signals

Usage: main.py process-signals [OPTIONS]

  Process RSI signals and execute trades.

Options:
  --help  Show this message and exit.

Turn on order monitoring

Usage: main.py monitor-orders [OPTIONS]

  Monitor open orders and execute stop losses.

Options:
  --help  Show this message and exit.

Dependencies

Technology: Python 3.10+ with Poetry for Package Management

Broker: Alpaca

Local Persistence: Google Firebase

Deployment

The only active strategy in this repository is a mean reversion strategy on the daily time frame. As such, deployment can be rather simple:

Applications

See the deployment folder for Linux deployment examples.

The Signal Scanner and Signal Processor need to each run once daily in sequence after the market closes and daily prices have been calculated. Here is an example using cron but Windows' built-in scheduler would suffice as well:

crontab -e

5 20 * * * /opt/pytrader/scrape-live.sh
15 20 * * * /opt/pytrader/process-live.sh

The Order Monitor listens for new orders and updates to existing orders. As such, this process should be run as a daemon or executed by a tool that can keep it alive if it should crash. Systemd is recommended if deploying to a Linux virtual machine. The deployment folder contains samples for setting up systemd. Docker is coming soon.

WARNING: Only a single instance of each process should be running at any point in time. No part of the tool is designed to run in a distributed infrastructure.

Contributing