docs: lock execution-recovery decisions and ops constraints
Record monotone fill-timing gradient, live [1.57,1.77] bracket, recover-flag interpretation, gap-cap as third tail-trim, and pre-scheduler ops checklist.
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@@ -115,10 +115,24 @@ Full write-up: **[phase-a-matrix.md](phase-a-matrix.md)** ·
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| Max-hold {45,60,90} | **Note and move on** — validation glitter, train collapse (regime interaction) |
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| Equity-curve vol targeting | **Reject as edge** on this sample; park vt25 as optional DD insurance only |
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| Correlation caps | **Reject**; sector caps stay Phase B with reduced expectations |
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| Next-open fill | **Discovery, not reject** — honest deployable ~Sharpe 1.2 / CAGR 30%. Decision baseline for future promotion = `next_open` |
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| Next-open fill | **Discovery, not reject** — honest deployable ~Sharpe 1.2 / CAGR 30% under overnight scanner. Decision baseline until near-close ships = `next_open` |
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| `fip_id` re-derive | **Validated** (IC −0.045, t = −2.92) |
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**Highest-leverage open work:** near-close execution recovery (scheduling, not a new signal). Simulator: `scripts/run_execution_recovery_matrix.py` (`stale_close` + gap-cap).
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### Execution recovery (same day) — closed as evidence
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Full write-up: **[execution-recovery.md](execution-recovery.md)** ·
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`reports/execution_recovery_matrix.json`.
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| Finding | Decision |
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|---|---|
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| Monotone fill timing (next_open → stale → close) + DD recovery | **When you fill**, not decaying alpha |
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| Live bracket **[1.57, 1.77]** full Sharpe | Near-close expected near top of bracket; no more fill-timing sim |
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| Gap-cap | **Dead** — third tail-trim instance |
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| Auto-`recover: false` | Not a null — bar hit the lower-bound arm by 0.03 train SE |
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**Highest-leverage open work:** **ops** — move the single daily R:R scan to
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`America/New_York` near-close (checklist in execution-recovery.md). Not more research
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knobs.
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---
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@@ -126,10 +140,10 @@ Full write-up: **[phase-a-matrix.md](phase-a-matrix.md)** ·
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| Lead | Why it's interesting | Blocker |
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|---|---|---|
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| **Near-close / MOC execution** | Recovers the overnight momentum drift a 07:00-Berlin scanner leaves on the table (~0.5 Sharpe / ~18pp CAGR vs close-fill) | Prove with `stale_close` arm; then schedule change |
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| **`fip_id`** (information discreteness over the 12-1 window) | **Strongest cross-sectional signal measured on this universe** — IC −0.045, t = −2.91, correct sign; re-derived fingerprint matched Phase A | Doesn't improve *this* book. Revisit when the universe broadens |
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| **Broader universe** (`nasdaq_all`) | Strengthens every week's cross-section and the IC t-stat | Also where `fip_id` could become tradeable |
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| **Forward paper-trade record** | The only true out-of-sample evidence the snapshot cannot give | Time |
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| **Near-close / MOC execution (ops)** | Recovers overnight momentum drift left on the table by a morning EU scan; evidence closed | Implement schedule + partial-bar scan path; one qualifying scan/day only |
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| **`fip_id`** (information discreteness over the 12-1 window) | **Strongest cross-sectional signal measured on this universe** — IC −0.045, t = −2.91, correct sign; re-derived fingerprint matched Phase A | Doesn't improve *this* book. Revisit when the universe broadens — **after** execution path is decided |
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| **Broader universe** (`nasdaq_all`) | Strengthens every week's cross-section and the IC t-stat | Grade under the fill mode you will trade |
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| **Forward paper-trade record** | The only true out-of-sample evidence the snapshot cannot give | Time; mark entries at actual near-close fill once ops ships |
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| **Better target model for clear-air names** | The return is demonstrably there (#2 wins on raw CAGR in *both* train and test); it's the *flat* 3× ATR target that makes it too expensive in risk | Needs a per-name model, not a constant k×ATR |
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---
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@@ -138,7 +152,8 @@ Full write-up: **[phase-a-matrix.md](phase-a-matrix.md)** ·
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1. **Nested lookback windows are NOT out-of-sample.** The clear-air result (#2) was
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clean, large, and consistent across five nested windows — and still died on a
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proper train/test split by entry date. Use `BACKTEST_HOLDOUT_SPLIT`.
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proper train/test split by entry date. Use `BACKTEST_HOLDOUT_SPLIT` / a named
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validation window — and do not pretend a repeatedly opened window is pristine.
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2. **Check what population an ablation actually admits.** The blanket fallback (#3)
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looked like it tested the "resistance famine" hypothesis. It didn't — 65% of the
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setups it let in were a different population entirely, and they drove the result.
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@@ -148,6 +163,12 @@ Full write-up: **[phase-a-matrix.md](phase-a-matrix.md)** ·
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4. **The iron rule:** a signal earns its way into selection *only* through the
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factor harness — |mean IC| ≳ 0.03, consistent sign, `reliable: true` (≥ 12
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non-overlapping windows). Never let an unvalidated score gate setups.
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5. **Momentum filters are guilty of tail-trimming until proven otherwise.**
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Independent failures: take-profit exits, FIP as an in-book filter, gap-up entry
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caps. Cosmetic quality up, P&L down — the right tail *is* the edge.
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6. **Fill timing is part of the strategy.** Close-fill reports are not deployable
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numbers for an overnight scanner. Grade promotion under the fill mode you will
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actually trade.
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---
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@@ -0,0 +1,146 @@
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# Execution recovery (2026-07-18) — when you fill is the edge you leave on the table
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Report: `reports/execution_recovery_matrix.json` / `.md`
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Follows Phase A A4 ([phase-a-matrix.md](phase-a-matrix.md)).
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Arms: `close_control` · `next_open` · `stale_close` · `next_open_gap2`.
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Mechanics verified before sign-off: `stale_close` re-anchors stop to
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fill − 1.5×ATR(signal day); no same-day stop after a close fill; each t−1
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candidate keeps its own gate/rank cross-section (no lookahead). Numbers trusted.
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---
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## Results
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| Arm | Full Sharpe | Full CAGR | Full DD | Train Sharpe | Val Sharpe |
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|---|---:|---:|---:|---:|---:|
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| **close_control** | **1.77** | **48.3%** | **21.6%** | 1.75 | 1.68 |
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| **stale_close** | **1.57** | **40.6%** | **21.8%** | 1.36 | **1.74** |
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| next_open | 1.20 | 30.0% | 28.2% | 0.94 | 1.44 |
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| next_open_gap2 | 1.06 | 25.2% | 27.8% | 0.72 | 1.41 |
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### Monotonicity (the strongest evidence)
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In every window, Sharpe recovers as the fill moves **toward** the signal:
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| Window | next_open → stale_close → close |
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|---|---|
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| Train | 0.94 → 1.36 → 1.75 |
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| Validation | 1.44 → 1.74 → 1.68* |
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| Full | 1.20 → 1.57 → 1.77 |
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\*Val close 1.68 is within SE of stale 1.74 — not a break of the story.
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A dead edge does **not** produce a monotone gradient in fill timing. A live edge
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that is progressively surrendered to execution delay does. Combined with full-period
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**DD recovery** (28.2% → 21.8% ≈ close’s 21.6%), this confirms the diagnosis:
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**when you fill**, not decaying alpha.
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### Auto-flag `recover: False` is not a null
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Pre-registered recovery applied the “≥ close − 0.5 SE” bar to **`stale_close`**,
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the **lower-bound** arm (one full session of lag). Flags:
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| Flag | Result |
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|---|---|
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| near_close_control (val) | **True** (Δ +0.06) |
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| beats_next_open | **True** (val Δ +0.30) |
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| train_ok | **False** (1.36 vs need ≥ ~1.39 — miss by ~0.03) |
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The floor missed “≥ close − 0.5 SE” by 0.03 while the live design is expected to
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sit **above** the floor. The flag worked correctly on the wrong object.
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**Log sentence:** *Partial recovery proven; full recovery needs same-day fill.*
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### Live outcome bracket
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| Bound | Arm | Meaning |
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|---|---|---|
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| Floor | stale_close ~1.57 full | One-session-stale close fill (conservative) |
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| Ceiling | close_control ~1.77 full | Same-day close; optimistic only by final ~15 min of signal info |
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Real near-close execution (scan ~15:30–15:40 ET on a ~99% complete bar, MOC by
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15:50/15:55) is signal-at-partial-bar filled at the same close the control uses.
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**Live truth is bracketed [1.57, 1.77]** with residual uncertainty of ~15 minutes
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of staleness, not 24 hours — expect near the **top** of the bracket.
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`stale_close` alone already justifies the schedule change. **No further fill-timing
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simulation on this snapshot** — the bracket is the result. You cannot simulate
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15:45 partial bars from daily data, and you do not need to.
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### Gap-cap — dead (third tail-trim instance)
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`next_open_gap2` worse than plain next_open on every window (full Sharpe 1.06 vs
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1.20). **262** full-period gap-ups skipped — they were continuations.
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This is the **third independent instance** of the same lesson:
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1. Take-profit exits (gate target as TP)
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2. FIP as an in-book filter
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3. **Gap-up entry caps**
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Any rule that trims the right tail improves cosmetic quality metrics and destroys
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P&L. **Standing method rule:** momentum filters must be presumed guilty of
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tail-trimming until shown otherwise.
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---
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## Decisions locked
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1. **Biggest lever is execution scheduling**, not a strategy rewrite.
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2. **Until near-close execution is live:** grade strategy promotion under
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`fill_mode=next_open`; keep close-fill as historical control.
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3. **After near-close ships:** grade under a close-like / near-close fill mode
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(actual live path).
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4. **No more sim arms** on fill timing for this snapshot.
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5. **Gap-cap:** do not ship.
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6. **Strategy work** (nasdaq_all, fip_id, sector) waits until the execution path
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is decided — those experiments must be graded under the fill mode you will trade.
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---
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## Ops design — settle before touching the scheduler
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### 1. One canonical qualifying scan per day (non-negotiable)
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Post-stop gate-reset was validated on **one full-universe observation per day**.
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Adding a near-close scan *alongside* the 07:00 scan would let fail→qualify
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transitions complete twice as fast and **silently change** the validated re-entry
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policy.
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**Move** the R:R scan to near-close. **Leave** sentiment / fundamentals /
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OHLCV-backfill at 07:00 (or existing early slots). Preserve **scan before
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Outcome Eval** (scan late session, eval after close) so the documented
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strict-gate-reset live analogue is unchanged.
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### 2. Cron in `America/New_York`, not `Europe/Berlin`
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DST offsets shift on different dates. A Berlin-fixed wall time drifts ~1 hour
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off the US close for a week or two twice a year.
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### 3. Fill mechanics and feed honesty
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- NYSE MOC cutoff **15:50 ET**; Nasdaq **15:55 ET**.
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- Scan ~**15:30–15:40 ET** on a latest-price snapshot; place entries by 15:50.
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- For now: paper-trade entries marked at the **actual close**.
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- Document Alpaca entitlement: if only 15-minute-delayed SIP, a 15:35 scan sees
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~15:20 prices — immaterial for a 12-month signal, but write it down so nobody
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treats it as a bug.
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### 4. Partial-bar plumbing
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- Scan synthesizes day-t’s in-progress bar from the snapshot.
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- Nightly OHLCV job overwrites with the final bar via existing idempotent upsert.
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- Forward paper record marks entries at the actual near-close fill so the live
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track measures the new execution honestly.
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---
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## Implementation status
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| Item | Status |
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|---|---|
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| Research evidence | **Closed** — this doc + matrix report |
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| Scheduler move (R:R scan → NY near-close) | **Not started** — blocked on ops design above |
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| Partial-bar scan path | **Not started** |
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| Paper fill-at-close marking | **Not started** (may already mark at close; verify when shipping) |
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@@ -74,9 +74,15 @@ Overnight gap on validation entries: mean **−0.52%**, median −0.18%, p05 −
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This is not “slippage noise.” It is largely the **overnight momentum drift** that close-fill earns and a 07:00-Berlin scanner (signal yesterday’s close → fill tomorrow’s open) **structurally cannot**. Honest deployable number under that schedule is ~Sharpe 1.2 / CAGR 30%, not 1.77 / 48%.
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**Decision baseline going forward:** grade **promotion** under `fill_mode=next_open`; keep close-fill as the historical control for comparability with prior reports.
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**Decision baseline going forward (until near-close ships):** grade **promotion** under
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`fill_mode=next_open`; keep close-fill as the historical control for comparability
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with prior reports.
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**Highest-leverage follow-up (not a strategy change):** near-close / MOC-style execution (~15:45 ET) so live fills sit near the close the signal is built on. Simulator proof arm: `stale_close` (signal t−1 close, fill t close). Secondary: next-open **gap-cap** (skip open > +2% vs signal close) — measure, don’t assume.
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**Follow-up (done):** execution recovery matrix — see
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**[execution-recovery.md](execution-recovery.md)**. Short version: monotone fill-timing
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gradient + DD recovery prove this is *when you fill*; live bracket **[1.57, 1.77]**;
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gap-cap dead; no more fill-timing sim on this snapshot; ops move R:R scan to NY
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near-close (one scan/day).
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### `fip_id` re-derivation — **validated**
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@@ -101,10 +107,14 @@ No arm cleared ΔSharpe > 1 SE.
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- Regime-conditional max-hold as a “small” experiment
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- Treat validation-only max-hold glitter as a free CAGR lift
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- Ship vol targeting as edge without a vol-regime sample
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- More fill-timing simulation on this snapshot (settled — see execution-recovery.md)
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- Dual daily qualifying scans (would break gate-reset validation)
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- Gap-up entry filters (third tail-trim failure)
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## What to do next
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1. **Execution recovery matrix** — `stale_close` vs close vs next_open; optional gap-cap under next_open (`scripts/run_execution_recovery_matrix.py`).
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2. If `stale_close` ≈ close control: schedule scan near the US close (not a signal rewrite).
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3. Until near-close execution ships live: **decision baseline = next_open**.
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4. Phase B data work only when wanted: `nasdaq_all` + `fip_id`, earnings calendar, sector residual/caps.
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1. **Ship near-close execution** — ops checklist in [execution-recovery.md](execution-recovery.md)
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(one R:R scan/day in `America/New_York`, MOC window, partial-bar honesty).
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2. Until that ships: **decision baseline = next_open**.
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3. Strategy work (nasdaq_all, fip_id, sector) only **after** execution path is decided,
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graded under the fill mode you will trade.
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