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foxhunt/infra
jgrusewski c7fdc617dc fix(ml-backtesting): variance-cap sample-size gate + aggregate GPU req
Three follow-ups to the cold-start floor fix:

1. Kernel: MIN_TRADES_FOR_VAR_CAP gate. After the first trade closed,
   `isv_kelly_update_on_close` set `realised_return_var = ret²` — a
   single-sample variance proxy that systematically collapses
   `cap_units = target_vol / sqrt(var × ann_factor)` near zero for
   any biased return. cap_lots → 0 → no further trades despite strong
   alpha. Gate the variance-derived cap behind `n_trades_seen >= 10`;
   below the threshold cap falls back to host-supplied `max_lots`,
   same as the pre-first-trade path. Same gate applied to both
   `decision_policy_default` and `decision_policy_program`.

   Regression: `post_first_loss_state_does_not_lock_out_further_trades`
   reproduces the exact pre-fix state from the smoke (n_trades_seen=1,
   var=103.6) and asserts the kernel still fires a long with p=0.8.

2. Aggregate: add `nvidia.com/gpu: 1` resource request. Scaleway's
   L40S device plugin mounts libcuda.so.1 into the container only on
   GPU-requesting pods; the aggregate logic is CPU-only but the
   binary's dynamic loader needs the driver libs. Cheapest correct
   fix until a separate CPU-only aggregator binary exists.

3. Smoke YAML: `max_events: 0` (exhaust loader). 100k events is
   minutes of ES.FUT, far shorter than the h6000 holding horizon the
   model was trained on. Full quarter exercises sustained trading +
   variance estimate ramp-up.

All three regression tests pass locally on RTX 3050 Ti.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 14:07:37 +02:00
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