This MT5 XAUUSD M1 backtest shows a very large reported return (12,792.9% on a 1,000 base) with a modest reported 11.33% maximum drawdown and 588 parsed closed rows, but profit is materially concentrated (top 1% of trades contribute 13.17% of gross profit, top 5% contribute 41.19%), so the headline metrics depend heavily on a small set of winners and should be validated before any live deployment.

Data transparency

Key metrics

Growth

Normalised to 100 at the starting capital of the imported report. The chart samples the saved per-trade results and is not a live broker equity curve.

Detailed calculations

Return = net profit ÷ initial capital × 100%; PF = gross profit ÷ absolute gross loss; expectancy = net profit ÷ number of closed trades; payoff ratio = average win ÷ absolute average loss. Max drawdown uses the value reported by the source report. If the report contains deposits or withdrawals, the return should be interpreted together with the cash flow.

Why this safety score

• Verified: MT5 tester report on XAUUSD, M1, 2025.01.03-2026.10.05, reporting 588 closed trades, profit factor 5.07, win rate 70.75%, return 12,792.904%, max drawdown 11.33%, net profit 127,929.04 on 1,000 capital.
• Verified: reported History Quality is 99% with 616,672 bars and 2,466,687 ticks, so the test ran on a large, largely complete history sample.
• Negative: profit concentration is material. The top 1% of trades (6 trades) account for 13.17% of gross profit, and the top 5% (30 trades) account for 41.19%, so a relatively small number of winners drive a disproportionate share of overall returns.
• Negative: individual wins are erratic in size, ranging from single-digit values up to 3,500 (capped at the stated Fixed TP level), while losses also reach -3,500 (Fixed SL), indicating the strategy uses a wide 3,500-point stop and take-profit with no evidence of a tight loss asymmetry; the equity curve depends on many large wins offsetting occasional full-size losses.
• Verified: position size grows from 0.03 lots early to 1.00 lots later in the sample as the account balance grows from 1,000 to about 128,929, consistent with some form of balance-scaled compounding, but the sizing rule itself is not stated in the evidence.
• Negative: the reported maximum drawdown of 11.33% is low relative to the reported return; trade-level losses of -3,500 and -773 etc. show that individual positions can move the account materially, and the drawdown figure should be treated as a backtest statistic rather than a forward expectation.
• Positive: no hard risk flags (stop-out, margin call, negative equity) were detected in the deterministic risk flags.
• Pending: no Demo or Real forward results accompany this backtest evidence.

Key risk flags

• Profit concentration: top 1% of parsed closed rows contribute 13.17% of gross profit and top 5% contribute 41.19%, so a small number of trades materially determine the reported outcome.
• Full-size stop-loss exposure: individual losses of -3,500 (equal to the stated Fixed SL) appear repeatedly, e.g. rows at 2025.12.24, 2026.01.30, meaning single losing trades can remove roughly 3.5% of the starting 1,000 capital before position sizing grew.
• Large loss spikes follow large profit spikes (e.g. -2,256.00 and -3,500.00 around 2026.01.30, -1,270.00 on 2026.01.29), showing that equity can give back a significant portion of recent gains.

What the data cannot tell

• Entry timestamps, trade duration, and per-trade holding periods cannot be confirmed because the parsed rows are close-only with no paired entry ticket.
• Whether the many same-minute or clustered closes represent multi-position baskets, grid entries, or independent orders cannot be determined from the supplied close-only rows.
• The exact position-sizing rule (e.g. fixed fractional, balance-scaled, or other) is not stated in the evidence, only the observed lot sequence.
• Commission, swap and fee costs are not present in the supplied report context, so net-of-cost performance cannot be independently verified.
• The sizing behaviour during a prolonged adverse period, and whether the strategy scales into losses, cannot be verified from the supplied evidence.

Next actions

• Re-run the backtest with paired entry/exit ticket data and per-trade holding times exported, to verify trade duration, direction pairing and whether any same-time exposure structure exists.
• Test cost sensitivity by adding the broker's actual commission and swap rates (and a realistic spread assumption) to the model, then compare resulting profit factor and drawdown against the reported figures.
• Validate the strategy on a Demo forward account using the same symbol, period and settings, then compare realised trade sizes, win rate and drawdown against the backtest.
• Stress-test the reported 3,500-point Fixed SL / TP on XAUUSD M1 by removing the top 5% of winning trades from the sample and recomputing profit factor and drawdown to quantify concentration dependence.
• Confirm and document the exact position-sizing rule with the EA's parameters so the relationship between balance growth and lot escalation can be checked directly.

Frequently asked questions