Rewrite Regime Monitor as v3: fundamentals off the score, desaturate P3

The LLM-sourced capex/earnings observations carried 12+8 of 100 Warning points,
so both pegged at 100 produced a Warning of 20.0 -- below the event study's 25.3
alarm threshold and still inside the "stable" band. The reading was
arithmetically incapable of changing anything on screen, which is why refreshing
it appeared to do nothing. They are now a qualitative overlay reported beside
the scores rather than diluted into them.

Calibrated against the 408 v2 sessions to 2026-07-24, reproduced offline from
Alpaca + FRED; the harness matched the stored prod distribution exactly before
any parameter was changed.

State:
- P3 used dd_pct * 5, reaching 100 at a 20% drawdown -- the 90th percentile of
  the observed distribution -- so 39/408 sessions sat at exactly 100 with no
  resolution left during the part of a selloff that matters most. Replaced with
  anchored breakpoints keeping headroom past the observed 36% maximum, blended
  2:1 like P1/P2 instead of max(). P3's realized share of State falls from 65%
  to 40%, matching its nominal weight.
- Credit level is now anchors-only. ICE capped FRED's BAMLH0A0HYM2 at a rolling
  3-year window in April 2026, silently turning the 10-year percentile leg into
  a 3-year one that scored 20 points of stress at an OAS of 3.5 -- the level its
  own anchors call "mild". The anchors already encode the long-run distribution.

Warning:
- Added HY OAS 20-session widening (25%). The level is pinned at zero below the
  3.5 anchor; its rate of change is not.
- Divergence tapers to a 0.35 floor instead of a hard price_ret >= 0 gate, which
  zeroed the sensor through every decline: on 2026-07-24 the basket shed 10
  points of participation in 20 sessions and Warning printed exactly 0.
- The event study and the live monitor now share one sensor definition, so they
  cannot silently drift apart.

Bands are per axis (State 20/50/80, Warning 20/40/60) with quadrant dividers at
50/40; v2 Warning never exceeded 64.9 against a shared 60, leaving that half of
the quadrant unreachable. Realized shares: State 73/15/8/3%, Warning 69/20/8/3%.

Snapshots now record credit_history_days and vix_history_days -- the percentile
defect went unnoticed for months because nothing asserted the window the code
claimed.

Cutover: the first run rebuilds 400 sessions automatically; the Event Study job
must be re-run, as its cached report self-invalidates on the methodology check.

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

app/services/breadth_service.py

@@ -72,15 +72,25 @@ def _breadth_from_closes(
     return _breadth_with_counts(closes_by_symbol, window, min_tickers)[0]
 
 
+# Breadth deterioration counts fully when price masks it (true divergence, the
+# dangerous pre-top case) and at CONFIRMED_FLOOR when price falls with it.
+# v2 used a hard ``price_ret >= 0`` cliff, which zeroed the sensor during every
+# decline -- so on 2026-07-24, with the basket shedding 10 percentage points
+# above their 200-DMA in 20 sessions, Warning read exactly 0.  Breadth *level*
+# lives in State but breadth *velocity* appears nowhere else, so partial credit
+# here is not double counting.
+DIVERGENCE_CONFIRMED_FLOOR = 0.35
+DIVERGENCE_TAPER_PCT = 3.0
+
+
 def compute_divergence_series(
     breadth: dict[date, float], benchmark_closes: Series, lookback: int = 20
 ) -> dict[date, float]:
     """Early-warning score (0-100, high = fragile) per date.
 
-    This is deliberately a pure divergence: it is positive only when benchmark
-    price holds/rises while breadth falls.  Absolute low breadth belongs in the
-    State score, so it is not counted again here.  A 20 percentage-point breadth
-    deterioration maps to 100.
+    A 20 percentage-point breadth deterioration maps to 100 when the benchmark
+    is flat or rising, tapering to ``DIVERGENCE_CONFIRMED_FLOOR`` of that once
+    the benchmark is down ``DIVERGENCE_TAPER_PCT`` or more over the window.
     """
     bench = {d: c for d, c in benchmark_closes}
     common = sorted(d for d in bench if d in breadth)
@@ -93,8 +103,9 @@ def compute_divergence_series(
         price_ret = (bench[d] / price_past - 1.0) * 100.0   # %
         breadth_chg = breadth[d] - breadth[d0]              # percentage points
         deterioration = max(0.0, -breadth_chg)
-        score = deterioration * 5.0 if price_ret >= 0 else 0.0
-        out[d] = max(0.0, min(100.0, round(score, 2)))
+        taper = max(0.0, min(1.0, (price_ret + DIVERGENCE_TAPER_PCT) / DIVERGENCE_TAPER_PCT))
+        gate = DIVERGENCE_CONFIRMED_FLOOR + (1.0 - DIVERGENCE_CONFIRMED_FLOOR) * taper
+        out[d] = max(0.0, min(100.0, round(deterioration * 5.0 * gate, 2)))
     return out