Report analysis: Vigorous EA · MT4 EURUSDi M15 Backtest
The Vigorous EA backtest on EURUSDi M15 shows a modest +3.37% return over 276 days but is driven by a handful of outlier trades, carries a 19.51% max drawdown, and rests on Control-point modelling quality that the tester itself says must not be considered.
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 limitsVigorous EA · MT4 EURUSDi M15 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 MT4 report |
|---|---|
| Broker | TradersWay-Demo |
| Symbol | EURUSDi |
| Timeframe | M15 |
| Trade period | 2026-01-06 — 2026-10-09 |
| Report type | BACKTEST |
| Reported trades | 505 |
| 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 | 3.4% |
|---|---|
| Max drawdown | 19.51% |
| PF | 1.29 |
| Win rate | 76.83% |
| Net profit | 336.97 |
| Expectancy | 0.67 |
| Payoff ratio | 0.39 |
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: 505 closed rows, 2026-01-06 to 2026-10-09 (276.4 days), net profit 336.97 on a 10,000 base, profit factor 1.29, win rate 76.83%.
- Verified: top 1% of trades (6 rows) account for 64.35% of gross profit; the remaining 499 rows net -621.22 with profit factor 0.46.
- Verified: top 5% (26 rows) account for 75.08% of gross profit; the rest nets -780.86 with profit factor 0.32.
- Verified: max drawdown of 19.51% against total net return of only +3.37% — a poor return-to-drawdown ratio.
- Verified: a single clustered close on 2026-06-30 accounts for roughly +450 swing in balance across many rows, an extreme concentration event.
- Verified: modelling is Control points, modelling quality is n/a, 4 mismatched charts errors, and the tester explicitly warns results must not be considered.
- Verified: StopLoss is configured as 0 in report_context.
- Pending: no Demo or Real forward record is supplied; only a Strategy Tester report exists.
Key risk flags
Profit concentration: 6 of 505 rows (top 1%) supply 64.35% of gross profit; without them the book is net negative.
- Return/drawdown asymmetry: +3.37% return against a 19.51% max drawdown — the payoff is far below the risk taken.
- A single 2026-06-30 close cluster moves balance from ~10,224 to ~11,188 then back to ~10,238, showing extreme single-event dependency.
- Control points modelling with 4 mismatched charts errors means the reported P/L, PF, and win rate cannot be relied upon as the strategy's true behaviour.
- StopLoss set to 0 in report_context — protective-stop behaviour is not evidenced by the supplied configuration.
- Close-only rows without paired tickets prevent verification of whether the many same-timestamp closes are independent trades, layered entries, or position management.
What the data cannot tell
Whether same-timestamp closes (e.g., 2026-01-06 01:43, 2026-02-02 15:21, 2026-06-30 17:42) are independent trades, layered entries, or position management — no entry tickets accompany the rows.
- Whether the 0.93-lot, 0.62-lot, and 0.41-lot sizes on 2026-06-30 follow a documented sizing rule — the rule is not provided.
- True spread, commission, swap, and slippage impact on net P/L (slippage 10 is a tester setting, not a cost model).
- Whether the strategy has any protective stop in live operation given StopLoss: 0.
- Behaviour under tick-level or real-tick modelling, since only Control points was used.
Next actions
Rerun the backtest on the correct EURUSDi chart history to clear the mismatched-charts errors, then report the resulting modelling-quality value.
- Rerun using a higher-quality modelling mode (e.g., every tick or real ticks) to test whether the outlier-driven P/L structure survives.
- Export paired entry/exit tickets to verify whether same-timestamp closes are separate trades, layered entries, or position management.
- Run sensitivity analysis on spread, commission, and slippage to test whether the thin net edge (336.97 on 10,000) survives realistic costs.
- Forward-validate on a Demo account for a comparable duration before drawing any live-performance conclusion.
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. Is the +3.37% return broad-based or dependent on a few trades?
A. It is heavily concentrated. The top 1% of closed rows (6 trades) contribute 64.35% of gross profit, and the remaining 499 rows net -621.22 with a profit factor of 0.46. The top 5% (26 trades) contribute 75.08% of gross profit, with the remainder netting -780.86. The headline return therefore rests on a small minority of trades.
Q. What does the 19.51% max drawdown mean relative to the 3.37% return?
A. The account gave up 19.51% at its worst point to earn a net +3.37% over 276.4 days. That is a weak payoff for the risk taken and means the equity curve carried materially more risk than its final return suggests.
Q. How reliable is this backtest given the tester warnings?
A. Reliability is limited. The report uses Control points modelling, reports modelling quality as n/a, lists 4 mismatched charts errors, and the tester itself explicitly warns the results must not be considered. Under those conditions the reported profit factor of 1.29, 76.83% win rate, and 19.51% drawdown cannot be trusted as representative of live behaviour.
Q. Why do many trades close at the same timestamp, such as 2026-06-30 17:42?
A. The supplied rows are close-only events and do not include paired entry tickets, so the same-timestamp closes cannot be classified as independent trades, layered entries, or position management from this evidence. This needs confirmation from paired ticket data; the 2026-06-30 cluster alone swings balance from roughly 10,224 up to 11,188 and back to about 10,238, which is why it should be verified before drawing conclusions.
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.