Backtesting Checklist for MT5 EA
A practical checklist for MT5 Expert Advisor backtesting: data quality, spreads, slippage, fees, optimization, forward tests, and robustness.
Risk warning
Educational content only. Automated trading can lose money quickly. Backtests do not guarantee live results, and every bot should be demo-tested with realistic spread, commission, slippage, and news conditions before any live use. This is not financial advice.
Role of this page
Testing pages focus on evidence quality: data assumptions, tester settings, optimization discipline, out-of-sample splits, and live-forward checks.
Who this is for
- Teams deciding whether a bot is robust enough for demo or limited live evaluation.
- Comparing MT5 Strategy Tester results with Python research outputs.
Not for
- Using net profit alone as a pass/fail metric.
- Optimizing hundreds of inputs without parameter-stability checks.
Before the backtest
A backtest is only useful when assumptions are visible. Document symbol settings, spread model, commission, slippage, account type, timeframe, and test period before reading performance metrics.
- Confirm tick or candle data quality and missing periods.
- Use realistic spread, commission, swap, and slippage.
- Separate in-sample and out-of-sample periods.
After optimization
Do not trust one perfect parameter set. Look for stable regions, run forward tests, test multiple market cycles, and stress the strategy with worse execution assumptions.
- Run walk-forward and Monte Carlo resampling.
- Compare net profit with drawdown, expectancy, profit factor, and trade count.
- Forward-test on demo before live consideration.
Practical examples
- Walk-forward matrix with train/test windows, stable parameter ranges, and rejected overfit zones.
- Stress pack: double spread, worse slippage, missed fills, delayed entry, and shuffled trade order.
Checklist
- Document data source, timezone, spread, commission, slippage, swap, and account mode.
- Compare profit factor, expectancy, drawdown, recovery factor, trade count, and worst streak.
- Keep a forward-test journal for every parameter set considered for live use.
Validation plan
- Run baseline, optimized, out-of-sample, walk-forward, Monte Carlo, and demo forward stages.
- Retest after any broker, symbol, timeframe, spread, or code change.
Implementation notes
- For MT5, save set files, tester reports, optimization inputs, and terminal build number.
- For Python, version data snapshots, package versions, seeds, and notebook outputs.
Developer / IDE prompt
Create a validation plan for this bot. Include baseline test, optimization ranges, out-of-sample split, walk-forward matrix, Monte Carlo assumptions, stress scenarios, demo-forward checklist, acceptance thresholds, and reasons to reject the strategy.
FAQ
Does a good MT5 backtest prove an EA will work live?
No. Backtests are research tools. Live execution depends on broker fills, latency, spread changes, slippage, and market regime shifts.
Next step
Turn these concepts into a complete bot logic plan with the strategy builder wizard.
Open Strategy Builder