Smart Owl FX_1.4_fix · MetaTrader 5… AI 测评｜QuantTester
Smart Owl FX_1.4_fix · MetaTrader 5 报告：收益 532.7%、回撤 19.67%、PF 3.16、196 笔交易。AI 风险解读。
策略安全信用评级: B (60 / 100) · 常态中性 (Moderate)
交易风险分析结果
Strategy Type: Strict Lot Discipline. Classified as Strict Lot Discipline: Despite a 532.7% return and 96.94% win rate, the strategy exhibits severe payoff asymmetry (average win $410 vs average loss $4,119, ratio 0.10) and a 26.64% maximum drawdown, with the largest single loss of -$14,622 erasing 35.6 average wins; the edge is robust (post-top 5% exclusion PF 2.71) and lot sizing is proportional, but the tail risk from a single catastrophic loss and the unverified stop-loss execution (stop_loss_evidence pattern 'unbounded_tail') warrant a Grade B with a safety score of 60.
Darwinex 集中度压力测试 (Top 5% Windfall Dependence Test)
剔除排名前 10 笔（5%）极端盈利单后：毛利占比 14.04%，剩余净利润 $42,322.20，剩余 PF 2.71。
数据透明度与环境说明
- MT4/MT5: MetaTrader 5
- 品种: EURUSD
- 周期: H1 (2025.01.03 - 202
- 总净利润: $53,270.00
- 总收益率: 532.7%
- 最大回撤: 19.67%
- 总交易笔数: 196
- 盈利因子 (PF): 3.16
AI 识别的核心高危漏洞清单
- Payoff Asymmetry Fragility: With a 96.94% win rate and PF 3.16, average winners ($410) must vastly exceed average losers ($4,119) to maintain profitability; any cluster of two or more large losses (e.g., -$4,326 on 2025.06.20 and -$4,446 on 2025.08.20) could erase dozens of small wins and flip arithmetic expectancy negative, as evidenced by the -$14,622 single loss on 2026.10.21 that consumed 35.6 average wins.
- Risk Stability Breakdown: The loss distribution shows an escalation from early losses around -$173 to -$4,446 to a maximum of -$14,622; the max_over_median ratio of 3.38 indicates stop-loss drift or unprotected holding in the tail, undermining replication stability (Rs).
- Drawdown Severity: Maximum drawdown of 26.64% on a $10,000 base (balance range approximately $10,000 to $73,799) represents elevated capital impairment, with the largest single loss of -$14,622 (14.6% of initial capital) occurring on 2026.10.21.
- Execution Friction Sensitivity: Backtest reflects fixed/unspecified spread settings on H1 with average holding of 71.2 minutes; lacking live broker execution proof, the realized PF 3.16 cannot be assumed to withstand real-world slippage and spread widening, especially given the high win rate (96.94%) that depends on small, frequent gains.
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 0.10 (< 0.6), losses heavily erode gains
- +5 pts [Expectancy]: Overall Profit Factor reached PF 3.16 with solid positive mathematical expectancy
- +10 pts [Organic Profit]: Removing top 5% windfall deals leaves PF 2.71 >= 1.2; robust and non-luck-driven
- -10 pts [Elevated Drawdown]: Max historical drawdown reached 26.6% (20%-35%), downside pressure elevated
- +10 pts [Sample Horizon]: Sample duration spans 664 days (>= 180 days), covering diverse regimes
- Final Strategy Safety Score: 60 / 100 (Grade B).
下一步行动与优化建议
- Obtain and verify full entry-ticket pairing and timestamps to confirm order structure and holding periods.
- Conduct a cost-sensitivity test incorporating realistic commission, swap, and slippage to assess net-of-cost viability.
- Review the largest loss episode (-$14,622 on 2026.10.21) to confirm whether a stop-loss was executed and to identify any stop-widening behavior.
- Request forward-test or demo results to compare against backtest metrics and evaluate execution friction.
- Stress-test the strategy under a scenario of clustered losses to assess whether the payoff asymmetry could breach risk limits.
关于本报告的关键质询与答疑 (Q&A About This Report)
Why does the strategy have a Grade B safety score despite a 532.7% return?
The grade reflects internal downside risk metrics: the realized payoff ratio is only 0.10 (average win $410 vs average loss $4,119), and the maximum drawdown reached 26.64% (20%-35% band). Additionally, the largest single loss of -$14,622 erases 35.6 average wins, indicating asymmetric downside exposure that offsets the strong profit factor of 3.16.
How robust is the edge after removing the most profitable trades?
Removing the top 5% of trades (10 rows) leaves residual net profit of $42,322.2 with a profit factor of 2.71, which is above 1.2, demonstrating that the strategy remains profitable without outlier windfalls and is not solely dependent on luck.
What does the stop-loss evidence indicate about downside protection?
With only 6 losing trades, the stop-loss evidence pattern is 'unbounded_tail' (max_over_median 3.38), meaning losses do not cluster at a consistent level; the largest loss of -$14,622 is 3.38 times the median loss of $4,326. This suggests inconsistent stop execution or stop-widening, so stop-loss discipline cannot be confirmed from the sample.
Is the 96.94% win rate sustainable given the small number of losses?
The high win rate is accompanied by a very low payoff ratio of 0.10, meaning the strategy relies on frequent small wins that can be erased by a few large losses. The single loss of -$14,622 on 2026.10.21 is equivalent to 35.6 average wins, so the win rate does not insulate the strategy from severe tail risk; sustained performance depends on avoiding clustered large losses.
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.