Backtesting
Backtesting is evaluating a strategy's rules against historical price data to estimate how they would have performed, before risking anything on them.
It ranges from manual bar-by-bar replay to fully coded simulation. The outputs that matter are a trade sample large enough to mean something — win rate, average R, worst losing streak, and drawdown — rather than a single equity curve that happens to end high. As a rough floor, a hundred trades is a sample; ten is an anecdote.
The classic failure modes are overfitting rules to the tested data, look-ahead bias (using information that was not available at the time), and ignoring the spread and slippage, which can erase a thin edge entirely. A backtest is evidence about the past, not a promise about the future, and its results deserve a discount.
In a prop-firm challenge
Backtest against the rulebook, not just for profitability. Check the strategy's worst historical losing streak against a 10% max drawdown, its worst single day against a 4–5% daily limit, and how many trading days it naturally produces against any minimum-day requirement. Then forward-test the same rules on virtual funds — paper trading under challenge constraints — so the first live test of the numbers is not a paid attempt.