Genome Lab

What the search did to each of the 11 genes across 8 generations. Selection swept trailing_stop through the population: a gene that starts in almost nobody and ends in almost everybody is one the search kept choosing.

The exploration width does not narrow, and that is a choice, not an oversight. Mutation keeps a constant width by default, so the search looks just as widely in the last generation as in the first. Annealing it was measured: it does make the population converge, but on this data a converging search settles for a steadier, smaller champion while the constant-width one stumbles onto the lucky outlier — and the ranking policy says a lucky winner is a winner. Annealing is a lever a competitor can pull (--annealing-rate), not the house setting.

ADX_min
27
exploration did not narrow (23 → 38)
ATR_period
5
exploration narrowed (40 → 21)
SL
375.934
exploration did not narrow (1314.59 → 1759.43)
TP_R
5.5514
exploration did not narrow (3.9847 → 7.1379)
break_even
on
adoption 92% → 87%
lot_multiplier
1.3132
exploration did not narrow (1.0416 → 3.0689)
risk_percent
2.3344
exploration did not narrow (6.4714 → 8.6465)
trailing_stop
on
swept the population, 0% → 80%
use_grid
off
adoption 0% → 13%
use_martingale
off
adoption 8% → 20%
use_session_filter
on
adoption 92% → 87%

Convergence is not proof. A gene can sweep because every survivor inherited it from one lucky ancestor, not because it is good. That is what the held-out slice and the walk-forward windows are for.

Public-safe research view from the local reference engine. Not an MT5 Strategy Tester run, not a trading signal, not a profit guarantee.