What is backtesting?

What it means

Every backtest is a simulation with assumptions baked in — about fills, about spread, about intrabar movement, about which data the strategy was allowed to see. Those assumptions determine the result at least as much as the strategy does, which is why two honest backtests of the same rules can disagree substantially.

Why it matters

The characteristic failures are lookahead bias (using information that was not available at the time), survivorship bias, and overfitting. The first two produce results that are simply wrong; the third produces results that are correct about the past and useless about the future.

What this changes in practice

A backtest earns trust through what surrounds it: a held-out period, published costs, a stated sample size, and a record of what failed as well as what worked. Ours is published with two separate periods, roughly 20% drawdown in both, and a public list of the 24 strategies that were cut and why.