From a market microstructure perspective, the repeated emergence of similar indicator components was the most interesting outcome.
Across markets with very different behavior — crypto (jump-prone), FX (mean-reverting), equity indices (regime-switching) — the evolved indicators tended to modulate position sizing based on:
• local entropy (as a proxy for noise/chaos)
• short + medium horizon trend consistency
• volatility bursts
This is consistent with the idea that markets penalize signals most during entropy spikes, regardless of asset class.
Would be interested in perspectives from people studying microstructure-aware signal generation.
Across markets with very different behavior — crypto (jump-prone), FX (mean-reverting), equity indices (regime-switching) — the evolved indicators tended to modulate position sizing based on: • local entropy (as a proxy for noise/chaos) • short + medium horizon trend consistency • volatility bursts
This is consistent with the idea that markets penalize signals most during entropy spikes, regardless of asset class.
Would be interested in perspectives from people studying microstructure-aware signal generation.