Quantum Emperor V7.5 EA · MetaTrader 5… AI 测评｜QuantTester
Quantum Emperor V7.5 EA · MetaTrade 报告：收益 -0.8%、回撤 3.60%、PF 0.94、303 笔交易。AI 风险解读。
策略安全信用评级: C (35 / 100) · 高危预警 (High Risk)
交易风险分析结果
Strategy Type: Strict Lot Discipline. Classified as Single-Order Trend (Strict Lot Discipline): a fixed 0.01-lot XAUUSD system with a high 84.16% win rate but a realized payoff ratio of only 0.18 (average win $4.76 versus average loss -$27.02) posts a net loss of -$83.04 (-0.83%, PF 0.94) over 303 trades and 632 days while containing drawdown to 3.6%; the capital-preservation architecture is sound but expectancy is mathematically negative and dependent on loser-timing precision, so live viability is limited without repricing the stop/target asymmetry.
Darwinex 集中度压力测试 (Top 5% Windfall Dependence Test)
剔除排名前 16 笔（5%）极端盈利单后：毛利占比 11.05%，剩余净利润 $-217.24，剩余 PF 0.83。
数据透明度与环境说明
- MT4/MT5: MetaTrader 5
- 品种: XAUUSD
- 周期: H1 (2025.01.03 - 202
- 总净利润: $-83.04
- 总收益率: -0.8%
- 最大回撤: 3.60%
- 总交易笔数: 303
- 盈利因子 (PF): 0.94
AI 识别的核心高危漏洞清单
- [R+ Return Consistency] Outlier Dependency: the top 5% of trades (16 of 303) contribute 11.05% of gross profit; excluding them the residual net reaches -$217.24 at PF 0.83, while excluding the top 1% (4 rows) leaves -$143.12 at PF 0.89 — the entire positive gross-profit profile sits inside a narrow row set rather than a broad systematic edge.
- [La Loss Aversion] Payoff Asymmetry Fragility: with an 84.16% win rate but average win of only $4.76 against an average loss of -$27.02 (payoff 0.18), roughly 5.7 winning trades are required to absorb one losing trade; any deterioration in winner capture or a cluster of near-full stop losses converts the -$0.27 expectancy into a steeper negative drift.
- [Rs Risk Stability] Loss-Scale Drift in the Late Sequence: late-period losses register -$36.81 (2026-02-04), -$32.22 (2026-02-10) and -$41.40 (2026-02-17), versus the earlier modal cluster around -$25.1 to -$26.6 — the maximum loss in the sample occurs in the middle of the 2026 sequence, indicating occasional stop realization deeper than the typical -$26 band (48-loss median $26.36, max/median 1.57).
- [D-Score Quote Shape] Unrecovered Nominal Equity: the account equity base was $10,000 and ended at $9,916.96 on 2026-10-08, i.e. no new high was reached across the 632-day window despite a contained 3.6% maximum drawdown — a shallow but persistently negative trajectory that offers no momentum or shape stability for replication.
- [Execution Feasibility] Thin Effective Edge: at 0.01 lots on XAUUSD, gross profit totals $1,214.15 against $1,297.19 gross loss; with a fixed 5-point slippage test setting and no broker-level cost fields, the $83 deficit means per-trade spread and slippage management is the deciding variable that cannot be verified from this evidence.
客观数学打分明细
- [Base Score] All valid statements start at 50 points neutral benchmark (Grade B-)
- +15 pts [Lot Discipline]: Fixed/proportional lot execution, no adverse counter-trend doubling
- -20 pts [Poor Payoff]: Win/loss payoff ratio only 0.18 (< 0.6), losses heavily erode gains
- -20 pts [Negative Expectancy]: Net loss of -0.83% incurred, negative return
- -15 pts [Windfall Reliance]: Removing top 5% outlier deals drops system into loss (Remaining PF 0.83 < 1.0)
- +15 pts [Minimal Drawdown]: Max historical drawdown only 3.6% (< 10%), excellent downside preservation
- +10 pts [Sample Horizon]: Sample duration spans 632 days (>= 180 days), covering diverse regimes
- Final Strategy Safety Score: 35 / 100 (Grade C).
下一步行动与优化建议
- Extract the full MT5 report with entry timestamps, ticket pairing and populated sl/tp columns to verify the actual executed stop distance behind the 48 losses.
- Recompute expectancy under cost sensitivity: apply realistic gold spread and commission per trade to test whether the -$0.27 per-trade deficit is a cost artefact or a structural payoff weakness.
- Evaluate whether the take-profit rule (nominal $3-$6 winners) can be widened or the -$26 stop tightened to lift the payoff ratio toward at least 0.30 without collapsing the 84% hit rate.
- Explain and audit the 2025-12-11 to 2026-01-14 inactivity gap to confirm the strategy was running rather than suspended.
- Collect a demo or real forward record of at least 100 trades to observe whether the -$26 typical stop band holds under live execution.
关于本报告的关键质询与答疑 (Q&A About This Report)
The win rate is 84.16% and the account barely lost money — why is this only Grade C?
The grade reflects the EA's internal downside arithmetic, not the size of the loss. The 255 wins average $4.76 while the 48 losses average -$27.02, giving a realized payoff ratio of 0.18; roughly 5.7 wins are needed to offset a single loss. Gross profit of $1,214.15 is outweighed by $1,297.19 gross loss, producing PF 0.94 and expectancy of -$0.27 per trade. The 3.6% maximum drawdown is genuinely strong capital preservation and is credited, but a high hit rate with this payoff structure is negative-expectancy arithmetic.
What evidence proves the strategy relies on a small number of trades rather than a consistent edge?
Removing the top 5% of trades (16 of 303 rows, which hold 11.05% of gross profit) leaves net profit at -$217.24 with PF 0.83. Removing only the top 1% (4 rows) still leaves -$143.12 at PF 0.89. Because the full sample already nets -$83.04, the positive contribution is concentrated in a narrow subset of rows rather than distributed across the trade population.
Does the 3.6% maximum drawdown mean the EA has hard stop discipline?
The evidence points to consistent loss termination: 48 losses cluster with a median of $26.36 and a maximum of $41.40, giving a max/median ratio of 1.57 and a clustered share of 85.4% — consistent with an executed fixed stop band rather than unbounded holding. However, the parsed rows are close-only with all sl/tp fields at zero, so the exact stop level and whether any exits were trailing or breakeven corrections cannot be confirmed from this table; the StopLoss 2500.0 parameter is a configuration literal, not proof of execution.
Is the position sizing a martingale or recovery ladder?
No. Every parsed entry is 0.01 lots over the 303 trades, and the audit shows no step-up in lot size. The parameters contain a SmartRecovery setting with a 1.6 multiplier, but the executed trade table shows no geometric lot expansion and no verified adverse sequence of same-symbol entries with increasing size, so martingale classification is not supported by the trade data.
How is QuantTester different from asking a general-purpose AI assistant myself?
QuantTester parses MT4/MT5 reports into structured metrics and trade records before AI review. Supported calculations can be checked against the original export, guaranteeing consistent audit facts.
Which broker is recommended for trading and running MT4/MT5 strategies?
For algorithmic trading, EA execution and reliable backtesting, we strongly recommend IC Markets (Raw Spread Account) with 0.0 pip spreads.