Pricing
Check an EA, private audit and robustness improvement.
Three commitment levels built around the same idea: do not judge an Expert Advisor only on the exact historical path that made it look good.
A private buyer-focused AntiOverfit screening before purchasing an MT5 Expert Advisor.
- Private AntiOverfit Robustness Score from 0 to 100
- Reduced synthetic-world robustness screening, normally 30 valid worlds
- Green / Yellow / Orange / Red decision label
- Short buyer-focused interpretation
- Main warnings and robustness concerns
- No badge, no public certificate and no public Audit ID
Best when you are considering an EA purchase and want a technical robustness signal before paying for the product. The score is private and cannot be used as a public AntiOverfit certificate.
Service 02
Private Robustness Audit
€390
Independent robustness analysis for one existing MetaTrader 5 Expert Advisor configuration.
- 1 Expert Advisor audit
- 1 symbol / timeframe configuration
- Original vs. synthetic-world comparison
- Robustness Score and grade
- Metric distribution analysis
- Warnings and interpretation
- Optional public certificate page and badge if suitable and approved
Best when you already have a configuration and want an external robustness result that can remain private or become a public verification asset.
Service 03
Robustness Improvement Sprint
from€790
A robustness-oriented improvement workflow using AntiOverfit PRO and internal tooling to search for EA parameter candidates less dependent on a single market path.
- Improvement workflow focused on robustness, not only maximum historical profit
- Candidate parameter filtering using synthetic market worlds
- Original vs. synthetic-world comparison for selected candidates
- Robustness-oriented ranking and technical interpretation
- Recommended candidate set or shortlist when viable candidates exist
- Private technical summary of strengths, fragilities and warnings
This is not a guarantee that a profitable or publishable set will be found. The objective is to reduce obvious fragility and avoid selecting parameters only because they dominated one historical backtest.
