Full optimisation + robust set files for 2 MT5 EAs (SSP & AIO Breakout)

指定

I need an experienced MT5/MQL5 quantitative developer to run full optimisations and robustness tests for two existing Expert Advisors:

SSP (scalping EA)
AIO Breakout (breakout EA)

This is NOT a full development job — it is optimisation, tuning, validation, and .set file creation.

1. Symbols & Timeframes
Optimise both EAs on:
XAUUSD (priority)
EURUSD
GBPUSD

Suggested timeframes: M5, M15, H1.
I’m open to additional recommendations if logical.

2. Data & Testing Periods
Use high-quality tick or 1-minute data.
In-sample: at least 5–8 years
Out-of-sample: at least the last 12–24 months

3. Optimisation Requirements
Optimise all relevant inputs:

SL / TP
Trailing
Session filters
Breakout thresholds
Volatility filters
ATR/volatility-based settings
Risk settings (fixed % only)

Avoid curve-fitting and unrealistic parameter combinations.

4. Target Metrics
Final sets must aim for:

Max Drawdown ≤ 20%
Profit Factor ≥ 1.3
Stable equity curve
Consistent trade count
NO martingale / NO grid

I prioritise stability over maximum net profit.

5. Robustness (Required)
Include at least one:

Out-of-sample validation
Walk-forward test
Monte-Carlo (randomised slippage/spread/tick noise)
Parameter sensitivity check

6. Deliverables
A. .SET files
For each EA + each symbol + each timeframe:

Conservative (prop-friendly)
Standard
Aggressive

B. Backtest reports
Provide MT5 HTML or CSV reports for all final sets.

C. Summary
Short documentation explaining:

Which parameters were optimised
In-sample vs OOS results
Recommended configuration
Any weaknesses or session notes

7. Developer Requirements
Please only apply if you have:

Proven MT5 optimisation experience
Past optimisation / set-file jobs
Strong understanding of curve-fit avoidance
Ability to provide robustness testing
Examples of previous optimisation reports (attach if possible)

Notes
All communication must remain on MQL5.
Code must compile cleanly in the latest MT5 build.
No hard-coded broker values.

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预算
30 - 200 USD