XAUUSD Wolfe SMC Pro ea… AI Review | QuantTester
XAUUSD Wolfe SMC Pro ea · Me: return 65.8%, DD 23.85%, PF 1.26, 228 trades. Read the review.
Strategy Safety Grade: B- (55 / 100) · Caution Advised
Trading risk analysis result
Strategy Type: Strict Lot Discipline. Classified as Single-Order Trend: a 100% short-only XAUUSD H1 system with fixed 0.1 lots and no adverse scaling, producing PF 1.26 over 421 days, but the edge is structurally fragile—removing the top 5% of trades leaves residual PF 0.78, the stop-loss evidence shows an unbounded tail (max/median loss 21.1x, clustered share 4.9%) and max drawdown of 27.69%—yielding a Grade B- / 55 safety score.
Darwinex 集中度压力测试 (Top 5% Windfall Dependence Test)
剔除排名前 12 笔（5%）极端盈利单后：毛利占比 38.31%，剩余净利润 $-5,558.10，剩余 PF 0.78。
Data transparency & Environment
- MT4/MT5: MetaTrader 5
- Symbol: XAUUSD
- Timeframe: H1 (2025.01.03 - 202
- Net profit: $6,579.70
- Return: 65.8%
- Max drawdown: 23.85%
- Total Trades: 228
- Profit Factor (PF): 1.26
Critical Algorithmic Vulnerabilities
- Outlier Dependency (Return Consistency / R+): The top 5% of trades (12 rows) account for 38.31% of gross profit; removing them leaves residual net profit at -5,558.1 with a PF of 0.78. Expectancy therefore relies on a small set of outliers rather than a consistent repeatable edge, which is hazardous for live capital allocation because a regime that suppresses these tail wins moves the system into structural loss.
- Loss Scale Escalation (Risk Stability / Rs): Stop-loss evidence shows an unbounded tail — maximum single loss of 2,911.3 versus a median loss of 138 (21.1x), with only 4.9% of losses clustered at a consistent level. This indicates stop distances and dollar risk are not stable across the sample, undermining the replicability of risk per trade and exposing the account to isolated loss shocks (e.g., the 2026-01-30 -2,911.3 and 2025-10-21 -1,325.8 losses).
- Payoff Asymmetry Fragility (Loss Aversion / La): Win rate is 46.49% with a realized payoff ratio of 1.45; average winner 298.88 versus average loser -205.75. With sub-50% accuracy, the positive expectancy depends on large winning expansions; any choppy interruption that truncates winners would immediately flip arithmetic expectancy negative, as reflected in the residual PF of 0.78.
- Drawdown Amplitude (Momentum Decay / D-Score): Maximum equity drawdown of 27.69% is high relative to the 65.8% total return, and the longest loss streak reached 8 trades. A 27.69% equity contraction represents a deep quote-shape impairment that would require substantial recovery momentum to offset, creating adverse behavioral pressure during live replication.
- Execution Friction Sensitivity (Capacity / Execution Feasibility): The strategy is short-only and fully dependent on the H1 close; with report_context empty and no documented spread/commission/slippage model, the realized PF of 1.26 cannot be verified to withstand real-world spread widening or slippage on entries and exits.
Score Breakdown Details
- [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
- +5 pts [Expectancy]: Overall Profit Factor reached PF 1.26 with solid positive mathematical expectancy
- -15 pts [Windfall Reliance]: Removing top 5% outlier deals drops system into loss (Remaining PF 0.78 < 1.0)
- -10 pts [Elevated Drawdown]: Max historical drawdown reached 27.7% (20%-35%), downside pressure elevated
- +10 pts [Sample Horizon]: Sample duration spans 421 days (>= 180 days), covering diverse regimes
- Final Strategy Safety Score: 55 / 100 (Grade B-).
Recommended Next Actions
- Run a cost-sensitivity backtest with realistic spread, commission and slippage to measure how much of the 1.26 PF survives friction.
- Inspect the trade-level loss distribution around 2026-01-30 and 2025-10-21 to determine whether the -2,911.3 and -1,325.8 losses were stop-loss exits or signal-based discretionary closes, and formalize a hard stop-loss input.
- Evaluate a version with a defined maximum risk per trade (e.g., fixed stop distance) to test whether the unbounded tail contracts without destroying the trend capture.
- Conduct walk-forward and out-of-sample testing on the 100% short-only logic across a bull-gold regime to assess directional bias dependency.
- Collect a demo or live forward record to verify execution quality, spread behavior, and whether the outlier trades remain achievable outside the tester.
Q&A About This Report (Quant Due Diligence)
With a 65.8% return and PF 1.26, why is the strategy safety score only 55 (Grade B-)?
The score is driven by the EA's internal downside characteristics rather than the headline return. Removing the top 5% of trades leaves a residual net profit of -5,558.1 and a PF of 0.78, showing that expectancy depends on a small set of outliers. Maximum equity drawdown reached 27.69%, and stop-loss evidence shows an unbounded loss tail (max 2,911.3 versus median 138, a 21.1x ratio). These factors place the strategy in the B- band despite its positive overall PF.
The audit says 'no martingale', but the trade table shows only 0.1-lot sells. How was the single-order, lot-discipline classification verified?
Every parsed row uses exactly 0.1 lots, and audit_facts confirm max_sim_orders = 1 and martingale_stepup = false. There is no progressive adverse entry sequence or geometric lot multiplier; the parameters show a fixed InpLots = 0.1. Therefore the evidence supports a single-order trend classification and not a martingale or grid scale-in.
Some losing trades are much larger than the median loss. Does that mean the strategy lacks stop-loss discipline?
The stop-loss evidence pattern is unbounded_tail: 122 losses have a median of 138, a mean of 205.75, a maximum of 2,911.3, and only 4.9% of losses cluster at a consistent level. This shows that losses are not terminating at a stable pre-set level, so the sample cannot establish a consistent hard-stop discipline. The largest losses, such as -2,911.3 on 2026-01-30, are evidence of unverified loss termination rather than a confirmed stop-loss mechanism.
Is the 100% short-only exposure a concern, and how does the drawdown compare to the return?
Yes. All 228 parsed rows are sell orders (long_pct = 0, short_pct = 100), so the strategy's performance is directionally dependent on gold weakness or mean reversion. The maximum drawdown of 27.69% against a 65.8% return means the return-to-drawdown ratio is approximately 2.38, which is moderate but leaves limited cushion if the short-only regime reverses. The longest loss streak of 8 trades further illustrates the equity path's vulnerability.
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.