feat: log Phase A decisions and add execution-recovery matrix
Document Phase A (max-hold/vol/corr closed; next-open as decision baseline). Add stale_close and next_open gap-cap fill modes plus a small matrix to test whether near-close scheduling recovers overnight momentum drift.
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# Phase A research matrix (2026-07-18) — results and decisions
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Report: `reports/research-matrix-phase-a.json` / `.md`
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Branch: `research/portfolio-vol-and-followups`
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Validation split: entries ≥ **2024-07-01** (called *validation*, not holdout — this window has been opened before).
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Cadence: daily, production gate/rank/trail + gate-reset re-entry.
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Pre-registered N for DSR: **20**.
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## Pre-registered promotion rule (unchanged after run start)
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Promote only if **all** of:
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1. Validation Sharpe ≥ control
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2. Validation max DD not worse by more than **2pp**
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3. Train Sharpe not worse (both-windows consistency)
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Always report whether validation ΔSharpe exceeds **1 × SE** (expect most will not).
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Mechanics guards confirmed before reading results: calendar truncation asserted on every arm; next-open re-anchors stop to fill − 1.5×ATR(signal); vol scalars apply at entry only.
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---
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## Control baseline
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| Window | Sharpe | SE | CAGR | MaxDD | Calmar | Trades |
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|---|---:|---:|---:|---:|---:|---:|
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| Train | 1.75 | 0.68 | 49.8% | 17.9% | 2.78 | 240 |
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| **Validation** | **1.68** | **0.72** | **41.6%** | **20.9%** | **1.99** | **239** |
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| Full (close-fill) | 1.77 | 0.50 | 48.3% | 21.6% | 2.23 | 472 |
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Validation SE ≈ 0.72 — almost no arm clears a 1-SE delta.
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---
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## Per-arm decisions
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### A2 — Max hold {30, 45, 60, 90} — **note and move on**
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| Hold | Val Sharpe | Val DD | Train Sharpe | Trades train |
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|---:|---:|---:|---:|---:|
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| 30 | 1.68 | 20.9 | 1.75 | 240 |
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| 45 | **2.07** | 19.3 | **1.43** | 218 |
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| 60 | **2.12** | 19.3 | **1.11** | 186 |
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| 90 | 2.04 | 23.1 | 1.30 | 179 |
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Validation-only would have “found” +0.4 Sharpe. Train collapses: longer holds leave stale names blocking slots (240 → 186 trades at hold-60). This is a **regime interaction** (trend validation vs chop train), not a free knob. A regime-conditional hold is a large research program; prior regime-overlay work already argues against that path.
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**Decision: keep max hold 30. Do not ship longer static holds.**
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### A3 — Equity-curve vol targeting — **reject as edge; park as optional insurance**
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Scalars averaged 0.77–1.07 as designed (grid straddled historical book vol ~22–25%). Lower targets de-levered; **vt25** was nearly neutral (val Sharpe 1.63 vs 1.68). Wide clamp ≈ headline clamp. Lookback sensitivity did not unlock a win.
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This sample has **no major vol-regime shift**, so the run **rejects vol targeting as an edge on this data** — it does **not** reject crash-insurance value in a future high-vol regime. The ~0.02 Sharpe cost at vt25 is a nearly free insurance policy if drawdown tolerance ever tightens.
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**Decision: do not ship. Settles “Phase 2 = vol-scaled momentum” as an edge plan on this snapshot. Park vt25 as optional risk preference only.**
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### A5 — Correlation caps — **reject; sector caps stay Phase B with reduced expectations**
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Best near-miss: **0.6 skip** — val Sharpe 1.70, val DD **17.0%** (tempting), but train Sharpe 1.61 < 1.75 and full-period Sharpe **1.59 vs 1.77** (the cap deletes real momentum concentration profit). Half-size variants were worse.
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**Decision: no pure corr cap. Sector caps remain Phase B with reduced expectations.**
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### A4 — Next-open fill — **not a reject; the discovery**
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| | Close control | Next-open |
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|---|---:|---:|
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| Full Sharpe | 1.77 | **1.20** |
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| Full CAGR | 48.3% | **30.0%** |
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| Val Sharpe | 1.68 | 1.44 |
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| Val DD | 20.9% | **28.2%** |
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Overnight gap on validation entries: mean **−0.52%**, median −0.18%, p05 −4.5%, p95 +2.1% (n=243).
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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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**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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### `fip_id` re-derivation — **validated**
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Weekly IC fingerprint on this snapshot: **mean IC −0.045, t = −2.92**, reliable (35 weeks). Matches the July record. Safe to reuse when the universe broadens.
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---
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## Promotion table (rule as written)
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| Outcome | Arms |
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|---|---|
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| Promote | only `a2_hold_30` (identity with control) |
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| Reject | every other arm |
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No arm cleared ΔSharpe > 1 SE.
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---
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## What not to do next
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- Re-litigate rejected-table items, min_rr, GTL
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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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## 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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