Report analysis: MonDip long · MT5 UK100 H1 Backtest
The MonDip long UK100 H1 backtest shows a modest +7.30% return with a 7.77% maximum drawdown and PF 1.44 over 35 trades, but small-sample and profit-concentration concerns limit confidence.
This page analyzes a user-submitted MT4/MT5 report. It does not authenticate ownership, rerun an independent backtest or predict future profit.
The 0–100 AI score is an evidence-based assessment, not a probability of profit. Read it with the rationale and unknowns.
Read metric definitions, report comparisons and evidence limitsMonDip long · MT5 UK100 H1 Backtest
The 0–100 AI score is an evidence-based assessment, not a probability of profit. Read it with the rationale and unknowns.
Data transparency
This page analyzes a user-submitted MT4/MT5 report. It does not authenticate ownership, rerun an independent backtest or predict future profit.
| Data source | User-submitted MT5 report |
|---|---|
| Broker | ForexTimeFXTM-Demo02 |
| Symbol | UK100 |
| Timeframe | H1 |
| Trade period | 2025-01-09 — 2026-10-01 |
| Report type | BACKTEST |
| Reported trades | 35 |
| Processing method | Parser extraction and supported calculations + AI review; not account authentication |
Key metrics
These metrics come from imported records and supported calculations. Check capital, costs, cash flows and period before comparing reports.
| Return | 7.3% |
|---|---|
| Max drawdown | 7.77% |
| PF | 1.44 |
| Win rate | 62.86% |
| Net profit | 730.11 |
| Expectancy | 20.86 |
| Payoff ratio | 0.85 |
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.
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
These metrics come from imported records and supported calculations. Check capital, costs, cash flows and period before comparing reports.
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 positive: 35 parsed closed rows, net profit 730.11 on 10,000 capital (+7.30%), profit factor 1.44, win rate 62.86%.
- Verified negative: small sample of 35 closed trades over a 630-day period (2025-01-09 to 2026-10-01).
- Verified concentration: top 1 trade accounts for 17.49% of gross profit; removing it drops remaining profit factor to 1.19.
- Verified concentration: top 2 trades account for 30.63% of gross profit; remaining net profit becomes -4.55 with profit factor 1.00.
- Verified drawdown: max drawdown 7.77%, balance range approximately 9,967 to 11,582 mid-period, within normal bounds for this strategy.
- Positive: fixed size 1 lot across all rows suggests no compounding, doubling, or martingale-like escalation is evident in the parsed rows.
- Pending: no commission, swap, or spread cost is present in report_context, so cost sensitivity cannot be assessed from this backtest.
Key risk flags
Small sample: only 35 closed trades across 630 calendar days; statistical confidence in the 62.86% win rate and PF 1.44 is limited.
- Profit concentration: top 2 trades contribute 30.63% of gross profit; without them, remaining net profit is -4.55 and remaining PF is 1.00.
- All parsed rows are sell/out, so direction bias or hedging behavior cannot be verified from the normalized close-only rows.
What the data cannot tell
Entry prices, entry timestamps, ticket pairing, and actual trade direction are not present in the close-only parsed rows.
- Commission, swap, and spread costs are not reported in report_context; net-of-cost performance is unknown.
- The strategy's entry rule, stop-loss/take-profit levels, and whether any exit was a trailing stop cannot be determined from close-only rows.
- Whether the 35 trades represent all strategy entries or only a subset of closed events is not specified.
Next actions
Obtain paired entry/exit ticket data to verify trade direction, entry timing, and whether any exit is a trailing-stop style positive s/l.
- Rerun the backtest with commission, swap, and realistic spread settings to assess net-of-cost performance.
- Extend the sample period or combine with additional out-of-sample data to test whether the win rate and profit factor hold beyond 35 trades.
- Run a forward Demo test on the same symbol and period to compare live execution against the backtest's fixed-size assumptions.
- Review the top 2 trades to understand whether their outsized contribution reflects a repeatable edge or a one-off event.
Frequently asked questions
The 0–100 AI score is an evidence-based assessment, not a probability of profit. Read it with the rationale and unknowns.
Q. How much of the reported profit comes from the largest trades?
A. The top 1 trade accounts for 17.49% of gross profit, and the top 2 trades account for 30.63%. Removing the top 2 trades leaves net profit at -4.55 and a remaining profit factor of 1.00, so the overall return is concentrated in a small number of trades.
Q. Is the trailing-stop style of exits visible in this report?
A. All parsed rows are close-only sell/out records with no entry tickets, so exit style cannot be identified. Some stop-loss exits show positive profit, which is typical of a trailing stop or breakeven stop, but the supplied evidence does not confirm the mechanism.
Q. How reliable is the 97% History Quality for this backtest?
A. The report states 97% History Quality with 2,321,739 ticks over 10,239 bars. No explicit tester warnings or error flags are present, so the quality figure indicates substantial but not perfect modelled tick coverage; it does not by itself establish statistical reliability of the 35-trade sample.
Q. Does the report include commission, swap, or spread costs?
A. No commission, swap, or spread cost fields appear in report_context. The +7.30% return and 1.44 profit factor are therefore gross-of-cost figures, and net performance after trading costs cannot be determined from this evidence.
Q. How is RBOT different from asking a general-purpose AI assistant (such as ChatGPT, Gemini, Claude or DeepSeek) to analyse my report myself?
A. RBOT parses MT4/MT5 reports into structured metrics and trade records before AI review. Supported calculations can be checked against the original export; AI wording and scores can vary and are not guaranteed to be deterministic or comparable across reports. General AI assistants may also use calculation tools. Missing actual slippage, ownership or forward validation still requires other evidence.