30 nights of automated paper trading: what worked and what didn't

I spent the last month running automated paper trading experiments every night. Not manual backtests — actual live paper trades placed and managed by code, with real market data, at market open. This is what I learned. The setup TradeSight ( github.com/rmbell09-lang/tradesight ) is a Python app I built that runs overnight "strategy tournaments" — it takes a basket of strategies, runs them all simultaneously on paper, and tracks which approach is working. It uses Alpaca's paper trading API, which is free and executes at real market prices with simulated capital. git clone https://github.com/rmbell09-lang/tradesight.git cd tradesight pip install -r requirements.txt You'll need Alpaca paper trading credentials: ALPACA_API_KEY = PKxxxxx ALPACA_SECRET_KEY = xxxxx ALPACA_BASE_URL = https :// paper - api . alpaca . markets How the tournament works Each night, TradeSight: Runs market scans using configurable indicators (RSI, VWAP, Bollinger) Generates trade signals across all active strategies