How I Built a Paper Trading Bot in Python with Alpaca

How I Built a Paper Trading Bot in Python with Alpaca Automated trading has always fascinated me — the idea that you can codify market intuition into rules that execute with machine precision. In this post I'll walk through building a Python paper trading bot using the Alpaca API, covering confluence signal generation, backtesting, and live paper execution. Why Paper Trading First? Before risking real capital, paper trading lets you stress-test your strategy against live market conditions without financial consequences. Alpaca's paper trading environment is a perfect sandbox — same API, real tick data, fake dollars. Strategy: Confluence Signals Rather than relying on a single indicator, confluence trading combines multiple signals. Our bot uses three: Moving Averages (EMA 9/21) — identify trend direction RSI — avoid buying overbought conditions Volume confirmation — filter out weak moves A "buy" fires only when all three align: price above EMA21, EMA9 crossing up, RSI < 65, volume abov