Report analysis: BTC SCALPER IA · MT5 BTCUSD H1 Backtest
A high-return BTCUSD H1 backtest (694 parsed closed rows, PF 6.66, 58.93% win rate) with good test quality (100% history quality) but a 60.43% max drawdown and very high profit concentration, so safety is moderate and high-return claims remain unverified outside this backtest.
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 limitsBTC SCALPER IA · MT5 BTCUSD 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 | ForexClub-MT5 Demo Server |
| Symbol | BTCUSD |
| Timeframe | H1 |
| Trade period | 2025-01-03 — 2026-10-08 |
| Report type | BACKTEST |
| Reported trades | 694 |
| 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 | 31,442.5% |
|---|---|
| Max drawdown | 60.43% |
| PF | 6.66 |
| Win rate | 58.93% |
| Net profit | 3,144,252.00 |
| Expectancy | 4,530.62 |
| Payoff ratio | 4.64 |
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: 694 closed trades over 2025-01-03 to 2026-10-08 (642.5 days), PF 6.66, win rate 58.93%, net profit 3,144,252 on a 10,000 base.
- Verified positive: report states History Quality 100%, 15,522 bars and 3,693,032 ticks, which supports the internal consistency of the tested sample.
- Verified negative: max drawdown 60.43%, a large peak-to-trough decline that is the main safety concern.
- Verified negative: top 1% of trades (7 rows) contribute 10.6% of gross profit and top 5% (35 rows) contribute 33.11%, so profit is concentrated in a small number of exits.
- Verified trade-style observation: the recurring -1950 loss row (0.1 lot) appears many times and is the typical stop-loss exit size, while repeated +5850 rows suggest a common take-profit/trailing-stop exit; the largest gains (e.g. 91,168, 79,385, 45,966) are outliers relative to the rest.
- Pending: no forward (Demo or Real) account records were supplied, so live execution quality, slippage impact and broker minimum-holding behavior cannot be verified from this backtest.
- Pending: the supplied report_context does not include commission or swap values, so net-of-cost performance cannot be confirmed.
Key risk flags
Maximum drawdown of 60.43% is large relative to the 10,000 starting balance and represents a substantial capital risk.
- Profit concentration: 35 trades (top 5%) account for 33.11% of gross profit, and 7 trades (top 1%) for 10.6%, meaning a small number of large wins drives the return profile.
- Loss concentration in stop-loss exits: the -1950 row recurs frequently across the sample, reflecting repeated full stop-loss hits.
- Return magnitude (31,442.52%) is extremely high relative to the 642.5-day test period and small base, and depends on the same backtest conditions that produced a 60.43% drawdown.
- Slippage 500 is a tester setting; it is not evidence of real execution quality or a complete cost model.
What the data cannot tell
Entry timestamps, entry tickets and position-pairing are not present in the parsed close-only rows, so entry timing, simultaneous exposure and direction baskets cannot be determined.
- The strategy rules behind the fixed 0.1 lot size and the -1950 / +5850 exit levels are not described in the report.
- Whether the largest gains (e.g. 91,168, 79,385, 45,966) occurred under unusual market conditions cannot be determined from the supplied data.
- No commission, swap or fee values are present, so net-of-cost results are unknown.
- Broker minimum-holding rules, depth of book and real slippage behavior are outside the scope of this report.
Next actions
Run a Demo or Real forward test on the same BTCUSD H1 setup and compare trade-level results with this backtest.
- Verify entry/exit ticket pairing and entry timestamps for the repeated -1950 and +5850 exits to confirm whether they reflect independent trades or multi-position management.
- Confirm commission, swap and spread assumptions used in the tester and re-run if any cost component is missing.
- Inspect the largest winning trades (e.g. the 91,168 gain on 2025.08.24) to verify they are not dependent on a single event or data anomaly.
- Stress-test the strategy with higher slippage and cost assumptions to check the sensitivity of the 60.43% drawdown and PF 6.66.
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. What does the 60.43% max drawdown mean for this backtest?
A. It is the largest peak-to-trough equity decline reported for the test, measured against the account balance progression. The account started at 10,000 and ended at 3,154,252, but at some point during the 2025-2026 sample it fell 60.43% from a prior equity peak, which is the main safety concern in this report.
Q. Why do many losing rows show exactly -1950 and many winning rows exactly +5850?
A. These recurring values match the fixed 0.1 lot size and the strategy's stop-loss/take-profit style. A -1950 row is a stop-loss exit, and a +5850 row is a profit-target or trailing-stop exit. Equal P/L values at a fixed lot size are normal in this report and are not by themselves evidence of a data defect.
Q. How much of the profit comes from a few trades?
A. The top 1% of parsed closed rows (7 trades) account for 10.6% of gross profit, and the top 5% (35 trades) account for 33.11%. This means a meaningful share of the return depends on a small number of large winning exits, including gains such as 91,168 and 79,385, so profit concentration is a key feature of this report.
Q. How reliable is this backtest given the reported test settings?
A. The report states 100% history quality, 15,522 bars and 3,693,032 ticks, with no tester warnings, which supports the internal consistency of the backtest. However, the report does not include commission, swap or forward (Demo/Real) results, and the slippage setting of 500 is only a test parameter, so live execution quality and net-of-cost performance cannot be verified 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.