Die sechs Prüfungen
A backtest result must clear all six checks before we cite it. Checks are applied in order; failure at any stage ends evaluation.
- 01 Transparenz des Quellcodes
We review the strategy logic and its settings for hidden martingale logic, undisclosed averaging-down, or hard-coded broker parameters. We only cite results whose logic we can read in full.
- 02 Mindestens 5 Jahre Historie
Backtest window covers at least 5 years, ensuring exposure to both the 2022 risk-off regime and the 2023–2024 recovery.
- 03 92–100% Modellierungsqualität
Every-tick backtests at 92–100% modelling quality. Lower quality settings are not accepted.
- 04 Out-of-Sample-Nachtest nach der Fixierung
Settings are frozen at a cutoff date. Every day after that cutoff is re-tested on market data released later — data the strategy was never fitted to — and the result is kept as a separate window, never merged into the backtest figures. This is a rolling out-of-sample re-test, not a live account: the tester does not simulate slippage, requotes or rejected orders.
- 05 Spread-Kompatibilität dokumentiert
How the result changes at different brokers' typical spreads is documented wherever it is cited. Multi-broker live/forward verification is not part of this method, and we do not present it as one.
- 06 Drawdown innerhalb von 20%
Max historical drawdown ≤ 20%. Where we hold the tester's equity drawdown — the deepest the account sat with open positions included — that is the figure we judge, not the shallower balance one. Exceptions are flagged with an explicit warning wherever the result is cited.
Backtest-Prozess
Five sequential steps from raw data to the figures we cite in our research.
- 01 Symbol & history selection
We run on real tick data. Which feed depends on the test — a broker's own tick history, or Dukascopy ticks loaded as a custom symbol — and the exact source, symbol and contract specification are named wherever the result is cited. History length is a minimum of 5 calendar years, capturing the 2022 Ukraine/USD risk-off shock and the 2023 banking stress.
- 02 Modelling quality
All backtests run on the every-tick model at 92–100% modelling quality (tick-level simulation). We do not publish results from open/close or 1-minute OHLC interpolation, which can produce systematically optimistic drawdown figures for scalping EAs.
- 03 Realistic spread & commission
We apply the broker's actual floating spread observed during the backtest period where available, plus realistic commission per lot. Variable spread is not collapsed to a fixed average.
- 04 Full-window test & in-sample disclosure
We do not run a separate held-out walk-forward optimisation. Instead, each strategy is tested across the full 2021–2026 window — which spans the 2022 risk-off shock rather than a flattering sub-period — and any parameter chosen by looking at the test window (an in-sample decision) is disclosed plainly wherever the result is cited.
- 05 Spread sensitivity
Performance is measured on Exness real retail-spread tick data, and how the result changes at other brokers' typical spreads is noted wherever it is cited. Live, multi-broker forward verification is not part of this method, and we do not present it as one.
Referenz
Kennzahlendefinitionen
Every figure we cite from these backtests — in guides, research and glossary examples — uses these exact definitions. No metric is renamed or recomputed differently between pages.
| Metric | Definition | Why it matters |
|---|---|---|
| Max Drawdown | Peak-to-trough equity decline during the backtest period, expressed as % of peak equity. | Primary measure of catastrophic risk — governs position sizing. |
| Worst Streak | Worst uninterrupted sequence of net-negative trades (not individual losing trades). | Stress-tests the psychological durability of a live operator running the EA. |
| Recovery Days | Calendar days from max-drawdown trough to new equity high. | Distinguishes fast-recovery profiles from 'stuck under water' patterns. |
| 12-Month Return | Most recent 12 months of backtest performance, not annualised from a longer period. | Recent regime relevance — markets change; a 2017 EA may be misadapted for 2024. |
| CAGR 5Y | Compound annual growth rate over the full 5-year window. | Long-term baseline normalises for lucky short windows. |
| Sharpe Ratio | Mean daily return divided by std deviation of daily returns, annualised. Risk-free rate = 0 (conservative). | Single number that captures return-per-unit-of-volatility. |
| Sortino Ratio | Like Sharpe but divides by downside deviation only (ignores upside volatility). | More relevant than Sharpe for EAs with asymmetric upside. |
| Win Rate | Percent of closed trades with positive net P&L. | Context only — a 40% win rate with a 3:1 R:R is fine; we always show alongside average R:R. |
Geltungsbereichsgrenzen
We document what our methodology does not cover so readers can calibrate confidence correctly:
- Live forward test results are not part of the data. Backtest data is the evidence base.
- Black-box EAs without source access are not reviewed. We cannot verify the absence of hidden logic.
- Crypto CFDs and metals are outside the scope of this data. Coverage is limited to major and minor Forex pairs on MT5.
- Optimised parameters are tested for robustness but not guaranteed future-proof. Market regimes shift; re-test any EA — including one you build — before relying on parameters chosen more than 12 months ago.
Questions about methodology specifics can be sent via the contact form.
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