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docs: document post-stop gate reset results

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README.md
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Investing-signal platform for US equities. It runs one strategy, and it is a boring one:
> **A long-only cross-sectional momentum book.** Buy the top quintile by beta-adjusted 12-1 month momentum, tilt toward higher volatility, hold at most 10 names, cut at 1.5× ATR, then trail at 3× ATR for up to 30 trading days.
> **A long-only cross-sectional momentum book.** Buy the top quintile by beta-adjusted 12-1 month momentum, tilt toward higher volatility, hold at most 10 names, cut at 1.5× ATR, then trail at 3× ATR for up to 30 trading days. After an initial-stop exit, re-enter only after the gate has failed and subsequently qualified again.
**Philosophy:** don't predict price — rank it. The edge is *relative* strength across the universe, and the discipline is in the exit: cut losers fast, let winners run until the trail catches them.
**What is NOT the edge — read this before trusting a number on screen.** The composite score, the 5 dimensions, sentiment, fundamentals, and Structural S/R are **display context**, not validated predictors. The Gate Target Ladder is screening machinery that preserves the production setup population; it is not a claim about true market structure. In particular:
- **The headline "target" is not an exit.** It comes from the internal **Gate Target Ladder** and exists only to compute the R:R and reach-probability used by the activation gate. Human-facing chart S/R is a separate model. The live exit reads neither. Across 320 backtested production trades the exit reasons were **144 initial stop, 98 trailing stop, 78 max hold — and 0 targets.** Honoring the target as a take-profit was tested and *halves CAGR* ([research](docs/research/sr-levels-and-exits.md)).
- **The headline "target" is not an exit.** It comes from the internal **Gate Target Ladder** and exists only to compute the R:R and reach-probability used by the activation gate. Human-facing chart S/R is a separate model. The live exit reads neither. Across 472 trades in the current daily gate-reset replay, the exit reasons were **229 initial stop, 147 trailing stop, 96 max hold — and 0 targets.** Honoring the target as a take-profit was tested and *halves CAGR* ([research](docs/research/sr-levels-and-exits.md)).
- **The composite score does not select trades.** Residual momentum does.
Full experiment log — everything tested, kept, and rejected: **[docs/research/](docs/research/README.md)**.
@@ -36,19 +36,29 @@ flowchart TD
BOOK -->|yes| OPEN["OPEN — size at 1% account risk"]
OPEN --> EXIT{"Exit — whichever comes first"}
EXIT --> E1["Initial stop hit<br/>entry − 1.5 × ATR → −1R<br/><b>45% of trades</b>"]
EXIT --> E1["Initial stop hit<br/>entry − 1.5 × ATR → −1R<br/><b>49% of trades</b>"]
EXIT --> E2["Trailing stop hit<br/>highest close − 3 × ATR<br/><i>only binds once price is ~1R up</i><br/><b>31% of trades</b>"]
EXIT --> E3["Max hold reached<br/>30 trading days<br/><b>24% of trades</b>"]
EXIT --> E3["Max hold reached<br/>30 trading days<br/><b>20% of trades</b>"]
EXIT -.->|"NEVER"| E4["Gate Target Ladder target<br/><b>0% of trades</b>"]
E1 --> LOCK["Re-entry locked"]
LOCK --> GF{"Later daily scan<br/>fails the gate?"}
GF -->|no| LOCK
GF -->|yes| GQ{"A subsequent daily scan<br/>qualifies again?"}
GQ -->|no| GQ
GQ -->|yes| RANK
style M fill:#1e3a5f,color:#fff
style OPEN fill:#1e4d2b,color:#fff
style E4 fill:#2a2a2a,color:#888
style E1 fill:#4a1f1f,color:#fff
style E2 fill:#1e4d2b,color:#fff
style LOCK fill:#4a351f,color:#fff
```
**How to read the exit box.** The initial stop is tight (1.5× ATR) and the trail is wide (3× ATR), so the trail sits *below* the initial stop at entry and only takes over once price has advanced roughly 1R. Cut fast when wrong; give room once right. That asymmetry is what produces the right-tailed return profile the strategy depends on — most trades lose a little (win rate ~37.5%), a few win big (best trade +12.9R), and *that is why there is no take-profit*.
**How to read the exit box.** The initial stop is tight (1.5× ATR) and the trail is wide (3× ATR), so the trail sits *below* the initial stop at entry and only takes over once price has advanced roughly 1R. Cut fast when wrong; give room once right. That asymmetry is what produces the right-tailed return profile the strategy depends on — most trades lose a little (win rate 36.2%), a few win big (best trade +12.0R), and *that is why there is no take-profit*.
**What happens after an initial stop.** The stop always closes the trade and realizes its costs. The ticker is then locked until a successful daily full-universe scan first observes it outside the production gate and a later scan observes a fresh qualification. A continuously qualified ticker therefore cannot generate an immediate duplicate entry. Other exit reasons do not start this reset. See the [daily post-stop re-entry study](docs/research/post-stop-reentry.md).
## How It Works
@@ -121,7 +131,7 @@ Once a day (default 07:00). Steps run **in dependency order**, each consuming th
1. **OHLCV** — fetch the latest daily bars for every tracked ticker (Alpaca); new tickers backfill ~5 years.
2. **Sentiment** — fetch sentiment for the names that matter and are stale (> 5 days): top-pick feeders (residual-momentum leaders with a tradeable long setup), the watchlist, and open paper trades, plus a top-N-by-composite discovery net. Runs *before* the scan so the scan sees fresh sentiment.
3. **R:R Scan** — persist clean Structural S/R for charts/alerts, recompute the 5-dimension scores, and build long/short setups from a transient Gate Target Ladder (ATR stops and nominal gate targets) for every ticker. Attach each ticker's residual 12‑1 momentum activation percentile plus the promoted 80/20 production rank.
3. **R:R Scan** — persist clean Structural S/R for charts/alerts, recompute the 5-dimension scores, and build long/short setups from a transient Gate Target Ladder (ATR stops and nominal gate targets) for every ticker. Attach each ticker's residual 12‑1 momentum activation percentile plus the promoted 80/20 production rank. The completed full-universe scan also advances post-stop locks from gate failure to later requalification; failed scans never count as a transition.
4. **Outcome Eval** — resolve setups that hit target/stop or expired (default 30 trading days) and auto-close paper trades per the exit policy (default: 3x ATR trail with a 30-trading-day max hold).
5. **Market Regime** — recompute the regime index (breadth/trend).
6. **Regime Monitor** — separate v2 State/Warning risk thermometer with fixed-basket breadth, VIX, credit, and point-in-time fundamentals; feeds no trades.
@@ -155,6 +165,7 @@ Fundamentals (weekly, early Monday) · Alerts (hourly, Telegram) · Backtest (we
|---|---|---|
| **Residual 12-1 cross-sectional momentum** (the activation gate, long-only) | **Production gate — in-sample edge** | Promoted July 2026 after the portfolio variant beat raw 80 on CAGR, Sharpe and drawdown. Raw 12-1 remains a fallback only when benchmark data is unavailable |
| **3× ATR trailing exit** (+ 1.5× ATR initial stop, 30-day max hold) | **Production exit — best Sharpe of every exit tested** | Beat hold / SMA50 / 20-day-low / technical-40 and both take-profit variants (July 2026) |
| **Post-stop gate reset** | **Production re-entry policy** | The initial stop always closes; the ticker must later fail the daily gate and subsequently qualify again. At the production capacity of 10: Sharpe 1.67 → 1.77, CAGR 45.2% → 48.3%, DD 24.3% → 21.6% versus immediate re-entry. [Full study](docs/research/post-stop-reentry.md) |
| **Structural S/R** | **Human-facing context only — not a gate and not an exit** | Clean, capped zones are persisted for charts and alerts. The scanner deliberately does not read them. |
| **Gate Target Ladder** | **Gate input only — not market structure and not an exit** | Volume-free range grid + pivots preserves the useful legacy screening behavior exactly: 1,086/1,086 qualified setups retained and identical Sharpe 2.03 / CAGR 50.0% / DD 21.4% / 321 trades. The exit never reads its target. [Full write-up](docs/research/sr-levels-and-exits.md#explicit-gate-target-ladder) |
| Composite score + 5 dimensions | **Display/ranking only** | Sub-scores are hand-built heuristics; none has a measured IC. Note: the "momentum" *dimension* is 5/20-day ROC — NOT the validated 12-1 factor (that lives in `momentum_service`) |
@@ -167,11 +178,25 @@ Fundamentals (weekly, early Monday) · Alerts (hourly, Telegram) · Backtest (we
Caveats on the momentum result: in-sample, roughly one market regime, costs/slippage approximated at 0.1% per side, and residual momentum still needs SPY benchmark history to compute. The **out-of-sample proof is the forward paper-trade record**: Signals → Track Record compares live qualified expectancy against the backtest.
### Current production baseline
### Daily post-stop re-entry decision (2026-07-17)
Use this as a regression guardrail for future strategy changes, not as a return promise. Backtest run: local production SQLite snapshot, 506 tickers, weekly cadence, 30-trading-day horizon, 2022-06-28 → 2026-07-02, 0.1% per-side costs, price-only SPY benchmark. Numbers below are the 2026-07-11 run (`reports/backtest-20260711-prod-baseline.json`) — measured *after* the primary-target probability floor shipped, which pruned lottery-target setups (1,428 → 1,089 qualified) and lifted Sharpe on all three promotion contenders.
The production policy is **normal gate reset**, evaluated with daily setup opportunities and live-like full-universe ranking. An initial stop always closes. Re-entry unlocks only after a later successful daily scan observes the ticker failing the gate and a subsequent scan observes it qualifying again. The study replayed 1,011,248 point-in-time candidate observations across 505 tickers from 2022-06-24 through 2026-07-02, with the production GTL gate, 80/20 rank, exit, fees, sizing, and 10-position capacity.
| Item | Current baseline |
| Re-entry policy | Total return | CAGR | Max DD | Sharpe | Trades |
|---|---:|---:|---:|---:|---:|
| Immediate | 348.4% | 45.2% | -24.3% | 1.67 | 489 |
| **Gate reset (production)** | **388.1%** | **48.3%** | **-21.6%** | **1.77** | **472** |
| Fixed five-session cooldown | 250.8% | 36.6% | -22.2% | 1.47 | 473 |
In the disjoint 2025+ book, gate reset also beat immediate re-entry (Sharpe 1.66 vs 1.55; CAGR 41.8% vs 39.3%) and the fixed five-session rule (Sharpe 1.43; CAGR 32.7%). Its lead over both survived costs of 0.2% and 0.3% per side. The result is capacity-specific: cooldown 5 won at capacity 5, while immediate had slightly higher return and Sharpe at capacity 15. Production uses capacity 10, so that is the portfolio for which this decision is valid.
`gate_reset` and a simple `next_session` block happened to produce the same executed live-universe portfolio in this sample. Their rules are still different: this establishes that same-day re-entry was harmful here, but does not isolate a separate historical return premium from the reset condition. Gate reset was promoted because it represents a genuinely new signal episode and did not sacrifice results in the production book. Full definitions, all nine policy arms, cost/capacity sensitivity, and legacy-rank results are in [docs/research/post-stop-reentry.md](docs/research/post-stop-reentry.md); source report: [`reports/daily_reentry_matrix.json`](reports/daily_reentry_matrix.json).
### Historical weekly production baseline (pre gate-reset)
Use this as the historical ranking/exit regression guardrail, not as a return promise or the current re-entry-policy result. This run predates the post-stop gate reset and uses weekly entry replay, so its portfolio headline is not directly comparable with the daily matrix above. Backtest run: local production SQLite snapshot, 506 tickers, weekly cadence, 30-trading-day horizon, 2022-06-28 → 2026-07-02, 0.1% per-side costs, price-only SPY benchmark. Numbers below are the 2026-07-11 run (`reports/backtest-20260711-prod-baseline.json`) — measured *after* the primary-target probability floor shipped, which pruned lottery-target setups (1,428 → 1,089 qualified) and lifted Sharpe on all three promotion contenders.
| Item | Historical weekly baseline |
|---|---|
| Strategy version | `residual_highvol_80_20_atr_trail3_v1` |
| Production gate | Long-only, residual 12-1 momentum percentile >= 80, headline gate-target R:R >= 2.0 (live `activation_min_rr`; the code default is 1.2), primary-target reach-probability >= 20%, NEUTRAL excluded, confidence floor off (0) |
@@ -218,6 +243,7 @@ A systematic single-variable sweep (offline prod snapshot, production gate/rank/
| Momentum lookback: 6-1, 3-1, 12-7 (Novy-Marx), composites | **Keep residual 12-1** | 6-1/3-1 rank-IC ≈ 0; 12-7 IC 0.045 / t 1.58 — weaker than residual 12-1 (0.055 / t 1.98) |
| Selection cutoff {70, 75, 85, 90} × book size {10, 15, 20} | **Keep 80 × 10** | Monotonically worse in both directions from 80; the 10-slot cap never binds (<10 concurrent) |
| Position sizing: equal-weight, inverse-vol, risk-% sweep | **Keep 1% fixed-fractional** | See the inverse-vol warning below |
| Post-stop re-entry: immediate, fixed 2–5 sessions, gate resets, confirmation filters | **Keep normal gate reset for the 10-position production book** | Sharpe 1.77 vs 1.67 immediate and 1.47 cooldown 5; rerun before changing portfolio capacity |
| FIP path-smoothness as an in-book tie-breaker/filter | **Reject** (but see the lead below) | Non-monotonic across FIP quintiles within the qualified set; either half of a median split underperforms the full book — thinning the entry stream costs more compounding than the tilt returns |
Two findings future sessions must not re-litigate:
@@ -450,6 +476,14 @@ python scripts/run_backtest_snapshot.py backtest_snapshots/prod.sqlite --workers
.venv\Scripts\python.exe scripts\run_backtest_snapshot.py backtest_snapshots\prod.sqlite --workers 6 --allow-spawn
```
Weekly remains the resource-safe default. Add `--cadence daily` for live-like daily entry opportunities; this performs roughly five times as many setup evaluations. To generate the complete weekly/daily × immediate/gate-reset comparison in one invocation, use:
```bash
python scripts/run_backtest_cadence_comparison.py backtest_snapshots/prod.sqlite --workers 7
```
On Windows, add `--allow-spawn`. The comparison runner writes the two full cadence reports plus one compact four-arm report. For the larger nine-policy daily research matrix used in the post-stop decision, see `scripts/run_daily_reentry_matrix.py` and the [research record](docs/research/post-stop-reentry.md).
On an 8-thread machine, `--workers 6` is a good starting point: it leaves a
couple of threads for Windows, the shell, and browser/UI work while still using
most of the CPU.
@@ -490,6 +524,7 @@ matching decision. Every change still goes through the factor harness first (see
| `gate_ablation` | Net expectancy with each floor removed | Drop a floor only if removing it doesn't hurt net expectancy |
| `time_exit_sweep` | Net avg R / net R-per-day by hold length | Whether a fixed time exit beats the promoted ATR trail |
| `portfolio_monitor`, `portfolio_sim`, `strategy_variants` | CAGR, Sharpe, max drawdown, per-year returns | Promote a strategy only if it beats the current baseline on CAGR/Sharpe/DD |
| `production_cadence_comparison` | Immediate vs production gate reset at the selected weekly or daily cadence | Isolates the re-entry rule while keeping gate, rank, exit, fees, sizing, and capacity fixed |
| `signal_eval` | Mean IC, t-stat, IC>0 %, `reliable` | Iron rule: wire a new factor in only if \|IC\| ≳ 0.03 with a consistent sign and `reliable: true` |
| `holdout` (opt-in) | Train vs test books, split by entry date | **The only honest OOS read.** Set `BACKTEST_HOLDOUT_SPLIT=YYYY-MM-DD` |
| `recommendation`, `research_recommendation` | The report's own headline read | A starting point, not a substitute for the sections above |
docs/research/README.md
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@@ -8,7 +8,9 @@ was run and the data said no.** Detail lives in the linked docs and in
**The one-line summary of the whole platform:** it is a **long-only
cross-sectional momentum book** — buy the top quintile by beta-adjusted 12-1
momentum, tilt toward higher volatility, hold ≤ 10 names, cut at 1.5× ATR, then
trail at 3× ATR for up to 30 trading days. Everything else in the app (composite
trail at 3× ATR for up to 30 trading days. After an initial stop, require the
daily production gate to fail and subsequently qualify again before re-entry.
Everything else in the app (composite
score, Structural S/R, the Gate Target Ladder, sentiment, fundamentals) is
**display or screening**, not edge.
@@ -22,6 +24,7 @@ score, Structural S/R, the Gate Target Ladder, sentiment, fundamentals) is
| 80/20 residual-momentum / 6m-volatility rank | Ranking tilt | Buys ~2pp CAGR over momentum-only; costs ~6pp drawdown |
| 1.5× ATR initial stop | Real exit | Cuts losers fast |
| 3× ATR trailing stop, 30-day max hold | Real exit | Best Sharpe of every exit tested |
| Post-stop normal gate reset | Re-entry policy | Stop always closes; a later gate failure and subsequent fresh qualification define the next signal episode. Sharpe 1.67 → 1.77 and CAGR 45.2% → 48.3% at production capacity 10. [Full study](post-stop-reentry.md) |
| Max 10 concurrent positions, 1% risk per trade | Sizing | Cap never binds in practice |
| Structural S/R | Human-facing product context | Clean, capped zones for charts and alerts; not read by the scanner |
| Gate Target Ladder | Screening machinery | Volume-free transient proposals preserve the production candidate set exactly; never an exit |
@@ -63,6 +66,7 @@ invites overfitting.
| Primary-target R:R selector | **Keep 1.5** — target choice is intentionally independent of the later 2.0 activation floor |
| Exit policy (hold / SMA50 / 20-day low / technical-40 / ATR trail) | **Keep 3× ATR trail** — best Sharpe (2.04) |
| **Activation R:R floor `min_rr`** (swept 2026-07-12) | **Keep 2.0** — best in-sample *and* out-of-sample. But it is a **spike, not a plateau** — see below |
| Post-stop re-entry (nine daily policy arms) | **Keep normal gate reset at production capacity 10** — Sharpe 1.77 vs 1.67 immediate and 1.47 fixed cooldown 5. The result changes with book capacity; see [post-stop-reentry.md](post-stop-reentry.md) |
### The `min_rr` sweep (2026-07-12)
@@ -142,6 +146,10 @@ it is internal screening machinery whose broad historical-price-traffic behavior
was preserved explicitly and volume-free, with exact full-period parity. It is
still neither market structure nor an exit. The one component that *does* have
measured predictive edge is the momentum gate, and every knob on it has been
swept and confirmed.
swept and confirmed. After an initial-stop exit, that same gate now also defines
when a new episode may begin: one later failed observation followed by a fresh
qualification. The [daily re-entry matrix](post-stop-reentry.md) supports this
for the current 10-position book, but not as a universal rule for other
portfolio capacities.
The next real evidence is **forward**, not backward: the live paper-trade record.
docs/research/post-stop-reentry.md
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@@ -0,0 +1,169 @@
# Post-stop re-entry: daily policy study and production decision
## Decision
Use a **normal gate reset** after an initial-stop exit:
1. The initial stop always closes the trade. It is never cancelled because the
ticker still passes the gate.
2. Re-entry remains locked until a later full-universe daily scan observes the
ticker **failing** the production activation gate.
3. The lock remains in place until a subsequent daily scan observes a **fresh
qualification**.
4. Only then may the ticker return to the actionable setup list or be opened
through `create_trade`.
Trailing-stop, time, target, and manual exits do not start this state machine.
Scanner errors do not count as a gate failure. The two transitions are persisted
on the latest initial-stop `PaperTrade`, so neither a service call nor a restart
can bypass the rule.
This replaces the previously proposed fixed five-session lockdown. The normal
reset counts an unqualified stop-day close when that close is observed after the
stop. The stricter experiment, which required a failed close on a later session,
was not promoted.
## Experiment design
Source: [`reports/daily_reentry_matrix.json`](../../reports/daily_reentry_matrix.json),
generated 2026-07-17.
| Input | Value |
|---|---|
| Snapshot | Production SQLite snapshot through 2026-07-02 |
| Period used by the all/5y rows | 2022-06-24 to 2026-07-02 |
| Tickers | 505 |
| Point-in-time candidate observations | 1,011,248 (492,850 long; 518,398 short) |
| Live-universe rank observations | 584,393 |
| Qualified candidates under `live_universe` ranking | 5,189 |
| Entry cadence | Daily |
| Selection and ordering | Production GTL gate; residual/high-vol 80/20 rank; long-only after ranking |
| Exit | 1.5× ATR initial stop; 3× ATR trailing stop; 30-session maximum hold |
| Portfolio | 10 positions; 1% risk per trade; $10,000 initial capital |
| Trading cost | 0.1% per side in the primary matrix; 0.1–0.3% robustness sweep |
| Holdout split | 2025-01-01 |
The expensive daily candidate replay was performed once. Every policy arm then
used the same candidates, prices, costs, position sizing, capacity, and exit
logic. `live_universe` ranks all eligible tickers once per session like the live
scanner. `backtest_legacy` retains the older candidate-only rank approximation as
a sensitivity check.
### Policies tested
| Arm | Rule after an initial stop |
|---|---|
| `immediate` | No memory; a same-day close re-entry is possible |
| `next_session` | Block only the stop session |
| `cooldown_2/3/5` | Re-entry allowed at wait-session N |
| `gate_reset` | Require a failed gate observation, then a later qualification; the stop-day close may establish the failure |
| `strict_gate_reset` | Ignore the stop-day failure; require a later failed close and then requalification |
| `gate_reset_improved` | Gate reset plus a higher new stop and non-weaker production rank |
| `two_session_confirmation` | Require two consecutive qualified post-stop closes |
## Primary result: production-like `live_universe` ranking
The available history is shorter than five years, so the report's `5y` and
`all` rows cover the same period.
| Policy | Total return | CAGR | Max DD | Sharpe | Trades | Win rate | Post-stop re-entries |
|---|---:|---:|---:|---:|---:|---:|---:|
| Immediate | 348.4% | 45.2% | 24.3% | 1.67 | 489 | 35.6% | 155 |
| Next session | 388.1% | 48.3% | 21.6% | 1.77 | 472 | 36.2% | 142 |
| Cooldown 2 | 343.5% | 44.8% | 23.4% | 1.68 | 472 | 35.8% | 146 |
| Cooldown 3 | 293.4% | 40.6% | 22.7% | 1.56 | 474 | 35.9% | 146 |
| Cooldown 5 | 250.8% | 36.6% | 22.2% | 1.47 | 473 | 35.9% | 145 |
| **Gate reset** | **388.1%** | **48.3%** | **21.6%** | **1.77** | **472** | **36.2%** | **142** |
| Strict gate reset | 342.7% | 44.8% | 23.4% | 1.68 | 471 | 35.9% | 144 |
| Gate reset + improved setup | 267.4% | 38.2% | 24.9% | 1.60 | 422 | 36.3% | 69 |
| Two-session confirmation | 296.1% | 40.8% | **17.6%** | 1.65 | 441 | **37.9%** | 96 |
At the production capacity, normal gate reset improved all four portfolio
objectives relative to immediate re-entry: higher total return, CAGR, and
Sharpe, with lower drawdown. The fixed five-session rule reduced churn but gave
up too many profitable re-entry opportunities.
`gate_reset` and `next_session` produced exactly the same executed portfolio in
the `live_universe` runs. Their rules are not equivalent. In this sample, the
portfolio-level candidate path happened to converge to the same trades. This is
evidence that blocking same-day re-entry helped; it does **not** isolate an
independent return premium for the reset condition itself.
## Disjoint 2025+ test window
These are separate books with entries on or after 2025-01-01. They are a useful
temporal sensitivity check, but not forward evidence: the policy was still
selected after the historical data existed.
| Policy | Total return | CAGR | Max DD | Sharpe | Trades |
|---|---:|---:|---:|---:|---:|
| Immediate | 64.1% | 39.3% | 19.6% | 1.55 | 181 |
| Next session | 68.5% | 41.8% | 19.2% | 1.66 | 183 |
| **Gate reset** | **68.5%** | **41.8%** | **19.2%** | **1.66** | **183** |
| Cooldown 5 | 52.7% | 32.7% | 19.8% | 1.43 | 175 |
| Strict gate reset | 52.9% | 32.9% | 21.0% | 1.38 | 181 |
| Two-session confirmation | 35.4% | 22.5% | **18.1%** | 1.02 | 183 |
The gate-reset result did not depend solely on the earlier training period: it
also beat immediate and the fixed five-session rule in the disjoint test book.
## Cost and capacity sensitivity
At the production capacity of 10, gate reset remained ahead of both immediate
and cooldown 5 as costs increased.
| Cost per side | Policy | Total return | CAGR | Max DD | Sharpe |
|---:|---|---:|---:|---:|---:|
| 0.1% | Immediate | 348.4% | 45.2% | 24.3% | 1.67 |
| 0.1% | **Gate reset** | **388.1%** | **48.3%** | **21.6%** | **1.77** |
| 0.1% | Cooldown 5 | 250.8% | 36.6% | 22.2% | 1.47 |
| 0.2% | Immediate | 296.3% | 40.8% | 25.2% | 1.54 |
| 0.2% | **Gate reset** | **333.0%** | **44.0%** | **22.9%** | **1.64** |
| 0.2% | Cooldown 5 | 209.9% | 32.5% | 23.4% | 1.33 |
| 0.3% | Immediate | 249.8% | 36.5% | 26.0% | 1.41 |
| 0.3% | **Gate reset** | **284.0%** | **39.7%** | **24.2%** | **1.51** |
| 0.3% | Cooldown 5 | 164.0% | 27.3% | 24.7% | 1.16 |
The capacity sweep is a real limitation, not a footnote:
| Capacity at 0.1% cost | Immediate Sharpe / CAGR / DD | Gate-reset Sharpe / CAGR / DD | Cooldown-5 Sharpe / CAGR / DD |
|---:|---|---|---|
| 5 | 1.33 / 31.9% / 16.8% | 1.37 / 32.8% / 17.5% | **1.46 / 35.8% / 18.3%** |
| **10 (production)** | 1.67 / 45.2% / 24.3% | **1.77 / 48.3% / 21.6%** | 1.47 / 36.6% / 22.2% |
| 15 | **1.66 / 44.8% / 24.3%** | 1.63 / 43.0% / **21.6%** | 1.33 / 32.8% / 22.2% |
The promotion is therefore specific to the actual 10-position production book.
At capacity 5, cooldown 5 ranked best; at capacity 15, immediate had slightly
higher return and Sharpe while gate reset retained the shallower drawdown. Do
not generalize the chosen rule to a differently sized portfolio without rerunning
the matrix.
## Legacy-rank sensitivity
The older candidate-only ranking approximation also favored normal gate reset
over immediate and cooldown 5, although `next_session` was slightly stronger.
| Policy | Total return | CAGR | Max DD | Sharpe | Trades |
|---|---:|---:|---:|---:|---:|
| Immediate | 357.4% | 45.9% | 17.9% | 1.73 | 480 |
| Next session | **421.5%** | **50.8%** | 18.5% | **1.86** | 466 |
| **Gate reset** | 408.3% | 49.8% | 18.3% | 1.84 | 464 |
| Cooldown 5 | 332.3% | 43.9% | 19.6% | 1.71 | 459 |
| Strict gate reset | 351.3% | 45.5% | 20.4% | 1.72 | 457 |
## Why gate reset was promoted
- It is tied to a new signal episode instead of an arbitrary elapsed time.
- At the production capacity, it beat immediate and five-session cooldown on
return, CAGR, drawdown, and Sharpe.
- The advantage survived costs of 0.2% and 0.3% per side and the disjoint 2025+
test book.
- It avoids cancelling a valid stop: the loss and transaction costs are always
realized before any later trade.
- It avoids the extra filters that weakened strict reset, improved-setup reset,
and two-close confirmation.
The correct interpretation is deliberately modest: **normal gate reset is the
best production rule among the tested policies for the current 10-position
book.** It is not proof that gate reset is a universal source of alpha. Forward
paper-trade monitoring is still the only genuinely new evidence.