Why your backtest lies: walk-forward vs. overfitting

It's easy to build a strategy that looks spectacular on historical data. Just tune enough parameters until the curve climbs smoothly. The problem is that this fit describes the past; it doesn't predict the future. That's overfitting, and it's the number-one cause of strategies that die live.

Walk-forward validation attacks the problem by splitting the data: the strategy is optimized on one slice and evaluated on the next, which it never saw. If performance collapses out-of-sample, you know you were looking at noise, not an edge.

Cortex's Strategy Lab makes this the default path. The goal isn't to produce the prettiest backtest, but the most honest one.