Cross-post. Original: stellarbytecapital.com/blog/backtesting-overfitting
A profitable backtest is the easiest thing to produce in all of quant trading, and the most worthless. Give a motivated person historical data and enough parameters, and they'll hand you a strategy that turned $10k into $10M — on paper, on data that already happened. The hard part was never getting a good backtest. It's getting one that predicts anything about tomorrow. The gap between those two is overfitting.
What overfitting actually is
Overfitting is when your strategy learns the noise in your historical data instead of a real, repeatable pattern. Markets are mostly noise with a little signal. A model with enough freedom will memorize the noise — every lucky spike, every specific dip — because that maximizes backtest performance. It fits the past perfectly and the future not at all.
A backtest tells you what would have happened. Overfitting is mistaking that for what will happen.
