I Ran 10 Trading Strategies for 30 Days — Here Is What Actually Worked

I Ran 10 Trading Strategies for 30 Days — Here's What Actually Worked I built a paper trading framework, ran 10 different algorithmic strategies through it for a full month, and the results were... humbling. Some strategies I expected to crush it. Most didn't. One I almost skipped ended up being the standout. Here's the unfiltered breakdown. The Setup I built TradeSight ( https://github.com/rmbell09-lang/tradesight ) specifically for this kind of systematic testing. It's a Python paper trading framework that connects to Alpaca's paper API, runs strategies against live market data without real money, and tracks every metric I care about: win rate, max drawdown, Sharpe ratio, average trade duration. Test period: 30 days. Universe: S&P 500 components. Capital: $100k paper. The Strategies I ran 10 total but I'll focus on the ones with interesting results. The Winners Bollinger Band Mean Reversion Win rate: 61% Max drawdown: 8.2% Sharpe: 1.34 This was the surprise. Mean reversion on the 2-h