Python Stock Trend-Following Algo

I have a manual trend-following approach for equities that I now want fully automated in Python. The goal is a clean, modular script that can:

• ingest and clean EOD or intraday stock data
• generate buy/sell signals from a moving-average-based trend filter (I’ll share exact rules)
• size positions with basic risk controls—fixed % stop-loss and optional trailing stop
• execute trades through a broker API such as Interactive Brokers or Alpaca (open to whichever you are most comfortable with)
• run fast, reproducible back-tests so I can tweak parameters and view performance metrics before going live
• log trades and key statistics to CSV and simple plots for equity curve, drawdown, and hit rate

Please keep everything in standard Python 3, using common libraries like pandas, NumPy, TA-Lib or backtrader/zipline for back-testing. Comment your code clearly and include a short README explaining setup, config options, and how to switch between paper and live trading.

I’ll consider the job complete when the strategy:

1. Reproduces at least the same signals I currently get manually on a supplied sample list of 20 US stocks.
2. Shows a valid back-test report covering the past five years.
3. Places test orders in a paper account without errors.

If you need any clarifications on the entry/exit logic or preferred APIs, let me know and I’ll provide full details.