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Institutional Backtesting

Last updated: July 19, 2026 · [email protected]

What is it?

Backtesting evaluates a strategy against historical market data to measure how it would have performed. It is the standard way to separate ideas that worked from ideas that only sound good.

How Trade11AI does it

Trade11AI's backtest engine validates strategies before they are recommended, and its rejection criteria are published: a strategy is automatically rejected if its win rate is below 55%, its profit factor is below 1.5, its maximum drawdown exceeds 15%, its expectancy is negative, or the sample contains fewer than 5 trades. Passing strategies are marked VERIFIED and graded from Average to Elite; failing ones are marked REJECTED and excluded from recommendations.

Key facts

Published rejection criteria: WR < 55%, PF < 1.5, DD > 15%, negative expectancy, sample < 5 trades
VERIFIED / REJECTED badges on strategies in the app
Score grades from Average to Elite
Backtests describe history and never promise future results

Common questions

Why publish rejection criteria?

Transparency. Users can verify that recommendations are filtered by fixed, falsifiable thresholds rather than cherry-picked examples.

Does a VERIFIED badge guarantee the strategy will keep working?

No. Backtests measure historical behavior only; market conditions change and future results are never guaranteed.

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Risk disclaimer: Trade11AI provides educational scanner data only. Nothing on this page is financial or investment advice. Trading forex, crypto, indices, and derivatives involves substantial risk of loss, and past performance does not guarantee future results.