zhaoli
c0eb65efa7
Mined from book/ on the 'book' branch (HEAD 436692a). 11 queued runs,
each = hypothesis + one-variable change vs the exp-26 reference + acceptance
metric, per the ch.02 isolation/falsification discipline.
- workflows/: 5 runnable config-only YAMLs (Q01 M2 repro, Q02 seed10, Q03 topk20,
Q04 label10d, Q05 label22d) byte-derived from the exp-26 reference
- designs/: 6 design docs needing custom strategy modules or tool-only A/B
(Q06 Kelly, Q07 weekly rebalance, Q08 risk-limit A/B, Q09 long-short,
Q10 HMM overlay, Q11 standalone reversal)
35 lines
1.8 KiB
Markdown
35 lines
1.8 KiB
Markdown
# QUEUE-10 — HMM regime overlay on the exp-26 book (overlay, not feature)
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**Status:** QUEUED · **Priority:** P2 · **Effort:** custom strategy + feature compute + run
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## Hypothesis (prove)
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Regime flags failed as model **features** (exp 9 idea, exp 25 clean-lake
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confirmation that model-specific families regress), but the surviving use is as
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an **overlay**: a long-only/regime-gate that holds names only in the favourable
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HMM state should cut drawdown / improve net IR on the same signal. Source:
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`book/chapters/01` regime section + `chat-ideas.md`
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(`TODO(evidence-needed: HMM regime gate as overlay on exp-26 book)`).
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## Change vs exp-26 reference (ONE variable)
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- **Strategy**: plain TopkDropout (topk 10, n_drop 1) → custom
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`RegimeGateDropoutStrategy`: identical selection, but when the per-symbol
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HMM posterior (`sp_hmm_p_regime1`) is below a calibrated threshold the name
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is held in cash instead of bought (entry gate); no new features enter the
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model — `sp_hmm_p_regime1` is computed for gating only, fit on the train
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window (no lookahead), via `get_lake_sp` with `fit_end=<train end>`.
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- All signal/config unchanged.
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## Acceptance
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- `net_max_drawdown < 7.69%` (reference) AND `net_IR >= 0.21`. If the gate
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never binds at a sensible threshold → the gate is a no-op on this signal
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(exp 20 pattern) → recorded REFUTED/neutral, not a failure.
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- Calibrate the threshold on the valid window only (avoid the exp 13/14
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threshold-overfit trap).
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## Execution prerequisites
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1. Persist `sp_hmm_p_regime1` for the universe (get_lake_sp, fit_end =
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2025-09-01) WITHOUT adding it to `feature_fields` of the model.
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2. New contrib module `tac_qlib/contrib/strategy/regime_gate.py`, copy to the
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venv site-packages copy.
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3. Workflow YAML wiring the strategy.
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4. Trace + run + snapshot. |