Backtesting Metrics That Actually Matter

A backtest that only reports total return tells you almost nothing about whether a strategy is safe to run live. On Algo AI Trade, a backtest runs the exact strategy version that would run live against historical candles — the same definition, no rewriting required — so the metrics are directly comparable to what you'd see going forward.

Beyond total return

• Max drawdown — the largest peak-to-trough loss. This is the number that tells you whether you could actually stomach running the strategy live.
• Win rate vs. average win/loss size — a low win rate can still be profitable if winners are large relative to losers, and vice versa.
• Trade frequency — too few trades in the backtest window means your metrics are statistically thin, whatever they say.
• Consistency across periods — a strategy that only worked in one six-month window is a bigger red flag than mediocre average metrics.

What a backtest can't tell you

Past performance on historical candles doesn't guarantee future results, and backtests can't fully model slippage, liquidity constraints, or broker-side execution quirks. Treat a strong backtest as a reason to move to paper trading next, not as a reason to skip it.