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)
32 lines
1.6 KiB
Markdown
32 lines
1.6 KiB
Markdown
# QUEUE-11 — Standalone 5-day reversal signal net of costs (unisolated)
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**Status:** QUEUED · **Priority:** P2 · **Effort:** dataset study + backtest
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## Hypothesis (prove)
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5-day momentum strongly reverses on this panel (pooled regression:
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`sp_trend_slope_5` β = −0.53, t = −24; VR < 1 at 5–20d for ~32/72 assets —
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chat-derived, pre-clean-lake idea material). The reversal has never been tested
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as a **standalone tradable strategy net of costs**. If it clears the 20bp
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round-trip cost, it is an independent alpha source that can be blended with (or
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replace) the model book.
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Source: `book/ch01` "Timeline" + `chat-ideas.md`
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(`TODO(evidence-needed: standalone 5d-reversal strategy net of costs)`).
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## Change vs exp-26 reference
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- This is NOT a model-construction variant — it isolates a SINGLE-FEATURE
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signal: a model trained on `sp_trend_slope_5` (plus raw OHLCV) alone, or a
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mechanical reversal book (rank by −`sp_trend_slope_5`, buy the most-reverted
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topk), backtested net of costs over the exp-26 window.
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- Control: exp-26 compact reference on the same window.
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## Acceptance
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- Standalone reversal `net_ann_return > 0` (clears 20bp round-trip) — proves
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the claim "reversal is tradable net of costs". Secondary: excess vs the
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model book is the blend decision for a future round.
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## Execution prerequisites
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1. `rd_train`/workflow with `feature_fields = $open,$high,$low,$close,$vwap,$volume,sp_trend_slope_5`
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(single feature) OR a mechanical rank backtest via `rd_backtest` on a
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hand-built pred (pred = −rank(sp_trend_slope_5)).
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2. Trace + run + record as a standalone study (dataset-study status, not
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necessarily a traced model experiment). |