feat: wide_stop_veto_v1 — skip entries with stops >12% below entry (shadow)

Year-replay stop-width buckets: <8% +0.072R, 8-12% +0.120R, 12-16%
-0.054R, >16% -0.092R — the wide cohort holds every recent dollar
disaster (BIYA 16.7%, FCUV day-2 17.5%), where the exit ladder's blind
spot (BE/trail only arm on the way up) rides the full catastrophe
distance. New stopwidth_gate intervention (fail-open without levels) +
registered spec, same forward bar as the pm-high gate; the two cohorts
overlap so the adjudicator attributes which does the work. In-sample
counts for nothing.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

experiments/wide_stop_veto_v1.json

@@ -0,0 +1,9 @@
+{
+  "id": "wide_stop_veto_v1",
+  "hypothesis": "Skip ORB entries whose stop sits more than 12% below entry. Year-replay buckets (2026-08-03): <8% +0.072R, 8-12% +0.120R, 12-16% -0.054R, >16% -0.092R; both July dollar-disasters (BIYA 16.7%, FCUV day-2 17.5%) were wide-stop, where the exit ladder's blind spot (nothing arms until price rises) rides the full catastrophe distance. In-sample evidence counts for nothing toward the bar; overlaps orb_pmhigh_gate_v1's cohort — adjudicate both to attribute the work.",
+  "population": {"min_entry_gap_pct": 0.10, "min_day_volume": 300000, "price_min": 2.0, "price_max": 20.0},
+  "intervention": {"kind": "stopwidth_gate", "max_stop_pct": 0.12},
+  "bars": {"expR_delta_min": 0.05, "min_n": 200},
+  "futility": {"min_n": 400, "expR_delta_max": -0.02},
+  "fidelity": {"atr_frac": 0.25, "spread_mult": 3, "adverse_ticks": 1}
+}

research/experiments/replay.py

@@ -476,6 +476,26 @@ def iv_asym_exit(con, fire, bars, bars_after, params, fidelity):
 # multi-fire coordination needed, so it plugs into the per-fire _compute_fire
 # path instead of a _run_rank-style batch).
 # --------------------------------------------------------------------------- #
+def iv_stopwidth_gate(fire: "Fire", baseline: float | None,
+                      params: dict) -> tuple[float | None, dict]:
+    """variant_r = 0.0 when the entry's stop distance exceeds ``max_stop_pct``
+    of the entry price, else keep baseline.
+
+    Year-replay buckets (2026-08-03): stop <8% +0.072R (n=647), 8-12% +0.120R
+    (n=340), 12-16% -0.054R (n=112), >16% -0.092R (n=67) — and every dollar
+    disaster of late July (BIYA 16.7%, FCUV day-2 17.5%) sat in the wide
+    cohort, where the exit ladder's blind spot (nothing arms until price
+    rises) rides the full catastrophe distance. Overlaps the pmhigh_gate
+    cohort (faded day-2 monsters have both traits); running both lets the
+    adjudicator attribute the work."""
+    if fire.entry_price in (None, 0) or fire.stop_price is None:
+        return baseline, {"kind": "stopwidth_gate", "stop_pct": None, "reason": "no_levels"}
+    stop_pct = (fire.entry_price - fire.stop_price) / fire.entry_price
+    wide = stop_pct > float(params.get("max_stop_pct", 0.12))
+    return (0.0 if wide else baseline), {"kind": "stopwidth_gate",
+                                         "stop_pct": round(stop_pct, 4), "gated": wide}
+
+
 def iv_pmhigh_gate(con, fire: "Fire", bars, entry_idx: int,
                    baseline: float | None) -> tuple[float | None, dict]:
     """variant_r = baseline if REGULAR-HOURS price reclaimed the PREMARKET high
@@ -857,6 +877,12 @@ def _compute_fire(con, exp: dict, fire: Fire, favorable: dict | None = None,
         if fire.sim_baseline:
             d["source"] = "setup_sim"
         return {"baseline_r": baseline, "variant_r": v, "detail": d}
+    if kind == "stopwidth_gate":
+        baseline = _sim_baseline_r(fire, bars_after, fidelity) if fire.sim_baseline else fire.baseline_r
+        v, d = iv_stopwidth_gate(fire, baseline, params)
+        if fire.sim_baseline:
+            d["source"] = "setup_sim"
+        return {"baseline_r": baseline, "variant_r": v, "detail": d}
     if kind == "regime_gate":
         # needs the baseline BEFORE computing variant (unlike the other kinds,
         # which compute variant first and attach fire.sim_baseline's simulated

tests/unit/experiments/test_pmhigh_gate.py

@@ -54,3 +54,23 @@ def test_bars_after_entry_do_not_count():
     bars = _bars([(9.5, False), (10.1, True), (10.9, True)])
     v, d = iv_pmhigh_gate(_Con(10.5), _fire(), bars, 1, 1.0)
     assert v == 0.0 and d["broke"] is False
+
+
+def test_stopwidth_gate_zeroes_wide_and_keeps_tight():
+    from research.experiments.replay import iv_stopwidth_gate
+    P = {"max_stop_pct": 0.12}
+    wide = Fire(fire_id="o1", symbol="W", session_date=date(2026, 8, 3), fill_ts=None,
+                entry_price=17.60, stop_price=14.43, exit_price=None, baseline_r=-0.7,
+                trigger_price=17.35)                      # 18% stop -> gated
+    v, d = iv_stopwidth_gate(wide, -0.7, P)
+    assert v == 0.0 and d["gated"] is True
+    tight = Fire(fire_id="o2", symbol="T", session_date=date(2026, 8, 3), fill_ts=None,
+                 entry_price=10.0, stop_price=9.2, exit_price=None, baseline_r=0.5,
+                 trigger_price=10.0)                      # 8% stop -> kept
+    v, d = iv_stopwidth_gate(tight, 0.5, P)
+    assert v == 0.5 and d["gated"] is False
+    nolvl = Fire(fire_id="o3", symbol="N", session_date=date(2026, 8, 3), fill_ts=None,
+                 entry_price=None, stop_price=None, exit_price=None, baseline_r=0.3,
+                 trigger_price=None)
+    v, d = iv_stopwidth_gate(nolvl, 0.3, P)
+    assert v == 0.3 and d["reason"] == "no_levels"        # fail-open