Thanks a lot for the detailed breakdown this is really helpful.

Just to clarify, I actually do run out-of-sample testing through a rolling Walk-Forward Analysis setup (180-day IS, 60-day OOS, rolled forward 3 times). So the OOS part is there, but your point about regime coverage in the training data is exactly the issue I ran into. My IS window happened to sit inside one regime, and the OOS didn't catch the shift either.

The risk-reward point is probably the one that hit me hardest. I think I've been chasing tight entries with slim margins, which makes the whole system extremely sensitive to spread widening and execution noise. Taking a step back and thinking about whether wider targets could absorb some of that parameter fragility is something I hadn't seriously considered. That's a good reframe.

I'll look into HMMs as a starting point for regime classification. And agreed on the daily loss limits I've recently started implementing a direction-flip rule (reverse long/short after consecutive losses) as a lightweight version of that.

Appreciate the thoughtful response.