Backtesting simulates a trading or decision strategy on historical data. It applies the strategy's rules to past observations and calculates outcomes such as returns, losses, hit rate, drawdown and the number of opportunities that met the entry conditions.
A backtest is only as reliable as its data and assumptions. Look-ahead bias, overfitting, ignored fees, unrealistic fills and repeated experimentation can produce misleading results, so robust workflows add walk-forward validation and out-of-sample testing.
