Expensive fellow merchants,
Within the huge and various world of Professional Advisors (EAs), discovering a dependable one to entrust your capital to is all the time a difficult activity. Amidst numerous ads and guarantees of “enormous” earnings, transparency turns into the “guiding star” resulting in sensible funding choices.
Have you ever ever puzzled if the “dreamy” backtest outcomes offered by EA suppliers really replicate precise buying and selling efficiency? Can an EA “survive” and generate secure earnings when dealing with the unpredictable fluctuations of the stay market?
On this article, we are going to discover this query by conducting a particular backtest, not on distant historic knowledge, however on precise stay market knowledge. We’ll use an instance EA referred to right here as “Instance EA” as an example how backtesting on stay knowledge can present a extra practical view of an EA’s efficiency.
Backtest Interval: From Dwell Commerce Begin to Current
To supply probably the most goal and practical view, we’ve backtested Instance EA throughout the interval from March 2nd, 2025, to as we speak, March twenty first, 2025. This timeframe is critical as a result of it mirrors the precise market situations the EA encountered throughout stay buying and selling. Testing on stay knowledge like this presents a clearer image of how an EA performs in comparison with conventional historic backtests.
Backtest Parameters
The stay account began with $100,000, so we aligned the backtest parameters accordingly:
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Preliminary Capital: $100,000
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Leverage: 1:100
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Threat Degree: 3
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EA Configuration: Each Algo 1 & 2 operating concurrently
Backtest Outcomes: Uncooked Information
Right here’s a abstract of the MT5 backtest outcomes we obtained:
(Desk Word: Particular figures aren’t included right here, however a whole desk would listing key metrics corresponding to:)
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Complete revenue generated throughout the backtest interval. |
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Variety of trades executed by the EA. |
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Largest drop in account steadiness. |
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Moreover, we reviewed knowledge from the stay commerce account. The revenue proven there, after accounting for fee and swap charges, barely exceeded the backtest outcomes, providing an fascinating comparability.
Key Observations
Backtest outcomes, irrespective of how spectacular, are solely previous references and don’t assure future efficiency. Nevertheless, backtesting on stay knowledge, particularly over a latest interval like from March 2nd to March twenty first, 2025, supplies distinctive authenticity. Not like cherry-picked historic exams, this technique displays actual market challenges—volatility, slippage, and all.
This strategy avoids “portray” the previous with idealized outcomes. As a substitute, it presents an unfiltered take a look at how an EA like Instance EA behaves in a stay surroundings, giving merchants a extra dependable benchmark for analysis.
Why This Issues
Transparency in testing is significant for understanding an EA’s strengths and limitations. Sharing outcomes from stay knowledge isn’t about proving superiority—it’s about offering a sensible instance of how backtesting can align with real-world efficiency. Merchants can use this technique to evaluate any EA they’re contemplating, gaining confidence of their evaluation.
Let’s continue learning and sharing data to change into higher, extra knowledgeable merchants. Right here’s to profitable buying and selling and considerate decision-making!
