Optimization should refine a stable thesis, not hide a broken one.
Review equity behavior, drawdown timing, and trade clusters before touching parameters. Understand the story first.
Ask which market conditions the strategy handled well, which it mishandled, and whether that matches the original design intent.
Only adjust logic or constraints when you can explain exactly what problem the change is supposed to solve.
Every meaningful change resets the burden of proof. A refined rule set still has to earn its place through validation again.
Tune a strategy hard enough and it fits the past perfectly — then falls apart on new data. Push the tuning up and watch the out-of-sample curve diverge from the in-sample one.
Do not optimize to erase normal drawdown.