This is something I genuinely struggle with.
Whenever I improve a strategy, I can usually find another parameter to tweak, another filter to add, or another optimization run to perform.
At some point, though, it feels like I'm fitting the system to the past rather than building something robust for the future.
How do you personally decide that an EA is "good enough" and ready for live trading?
Are there specific metrics or rules you follow before you stop optimizing and start trading?
Stop when your out-of-sample results stop improving.
That's the only metric that actually matters.
If tweaking parameters keeps making your backtest prettier but your unseen data stays flat or gets worse, you're curve-fitting, not improving.
A good rule: if you can't explain why a setting works with real market logic, remove it.
Fewer inputs usually means more robust. Go live when it's consistently decent on data it's never seen, not when it looks perfect on data it already knows.
This is something I genuinely struggle with.
Whenever I improve a strategy, I can usually find another parameter to tweak, another filter to add, or another optimization run to perform.
At some point, though, it feels like I'm fitting the system to the past rather than building something robust for the future.
How do you personally decide that an EA is "good enough" and ready for live trading?
Are there specific metrics or rules you follow before you stop optimizing and start trading?
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This is something I genuinely struggle with.
Whenever I improve a strategy, I can usually find another parameter to tweak, another filter to add, or another optimization run to perform.
At some point, though, it feels like I'm fitting the system to the past rather than building something robust for the future.
How do you personally decide that an EA is "good enough" and ready for live trading?
Are there specific metrics or rules you follow before you stop optimizing and start trading?