feat: show FIP path-smoothness in ticker technicals

Display-only Da/Gurun/Warachka information discreteness on the ticker
indicator panel. Shared compute with the backtest harness; not wired into
gate or rank.

app/services/backtest_service.py

@@ -819,39 +819,14 @@ def _realized_vol_6m(closes: list[float], i: int) -> float | None:
 
 
 def _fip_id(closes: list[float], i: int) -> float | None:
-    """Da/Gurun/Warachka information discreteness over the 12-1 formation window.
+    """Point-in-time FIP ID for the signal harness; delegates to indicator_service."""
+    from app.services.indicator_service import compute_fip_id
+    from app.exceptions import ValidationError
 
-    Formation matches ``mom_12_1``: cumulative return from close[i-252] to
-    close[i-21] (231 daily returns ending one month before as-of).
-
-        ID = sign(PRET) × (%neg − %pos)
-
-    where %pos / %neg are fractions of up / down days over the formation window
-    (zero-return days count in neither numerator, but remain in the denominator).
-    Lower ID = smoother / more continuous path → expect negative cross-sectional
-    IC (continuous-information winners outperform).
-    """
-    if i - 252 < 0 or closes[i - 252] <= 0 or closes[i - 21] <= 0:
+    try:
+        return float(compute_fip_id(closes, as_of_index=i)["fip_id"])
+    except (ValidationError, KeyError, TypeError, ValueError):
         return None
-    pret = closes[i - 21] / closes[i - 252] - 1.0
-    rets: list[float] = []
-    for k in range(i - 251, i - 20):
-        prev = closes[k - 1]
-        if prev <= 0:
-            return None
-        rets.append(closes[k] / prev - 1.0)
-    if len(rets) < 200:
-        return None
-    n = len(rets)
-    pct_pos = sum(1 for r in rets if r > 0) / n
-    pct_neg = sum(1 for r in rets if r < 0) / n
-    if pret > 0:
-        sign = 1.0
-    elif pret < 0:
-        sign = -1.0
-    else:
-        sign = 0.0
-    return sign * (pct_neg - pct_pos)
 
 
 def _signal_values(

app/services/indicator_service.py

@@ -28,6 +28,7 @@ MIN_BARS: dict[str, int] = {
     "atr": 15,
     "volume_profile": 20,
     "pivot_points": 5,
+    "fip_id": 253,  # 12-1 formation: need index i-252
 }
 
 DEFAULT_PERIODS: dict[str, int] = {
@@ -407,6 +408,71 @@ def compute_pivot_points(
     }
 
 
+def compute_fip_id(closes: list[float], as_of_index: int | None = None) -> dict[str, Any]:
+    """Da/Gurun/Warachka information discreteness over the 12-1 formation window.
+
+    Display / research context only — **not** used by the activation gate or
+    production rank. Same window as residual 12-1 momentum: cumulative return
+    from close[i-252] to close[i-21] (skip last month).
+
+        ID = sign(PRET) × (%neg − %pos)
+
+    Lower ID ⇒ smoother / more continuous path (for a winner: many small up days).
+    Higher ID ⇒ jumpy / discrete path (few large moves). Zero-return days count
+    in neither numerator but remain in the denominator.
+    """
+    i = len(closes) - 1 if as_of_index is None else as_of_index
+    if i < 252 or closes[i - 252] <= 0 or closes[i - 21] <= 0:
+        raise ValidationError(
+            f"FIP ID requires at least 253 bars with positive formation closes, "
+            f"got {len(closes)}"
+        )
+    pret = closes[i - 21] / closes[i - 252] - 1.0
+    rets: list[float] = []
+    for k in range(i - 251, i - 20):
+        prev = closes[k - 1]
+        if prev <= 0:
+            raise ValidationError("FIP ID requires positive closes in the formation window")
+        rets.append(closes[k] / prev - 1.0)
+    if len(rets) < 200:
+        raise ValidationError(
+            f"FIP ID requires ≥200 daily returns in formation, got {len(rets)}"
+        )
+    n = len(rets)
+    pct_pos = sum(1 for r in rets if r > 0) / n
+    pct_neg = sum(1 for r in rets if r < 0) / n
+    if pret > 0:
+        sign = 1.0
+    elif pret < 0:
+        sign = -1.0
+    else:
+        sign = 0.0
+    fip = sign * (pct_neg - pct_pos)
+    # Map [-1, 1] → score where lower ID (smoother) is higher for display only.
+    score = max(0.0, min(100.0, 50.0 * (1.0 - fip)))
+    if fip <= -0.25:
+        path = "continuous"
+        path_label = "smooth grind (continuous information)"
+    elif fip >= 0.25:
+        path = "discrete"
+        path_label = "jumpy path (discrete information)"
+    else:
+        path = "mixed"
+        path_label = "mixed path"
+    return {
+        "fip_id": round(fip, 4),
+        "pret_12_1": round(pret, 4),
+        "pct_up_days": round(pct_pos * 100.0, 1),
+        "pct_down_days": round(pct_neg * 100.0, 1),
+        "formation_days": n,
+        "path": path,
+        "path_label": path_label,
+        "display_only": True,
+        "note": "Not used by the production gate or rank — context only.",
+        "score": round(score, 4),
+    }
+
+
 def compute_ema_cross(
     closes: list[float],
     short_period: int = 20,
@@ -451,7 +517,15 @@ def compute_ema_cross(
 # Supported indicator types
 # ---------------------------------------------------------------------------
 
-INDICATOR_TYPES = {"adx", "ema", "rsi", "atr", "volume_profile", "pivot_points"}
+INDICATOR_TYPES = {
+    "adx",
+    "ema",
+    "rsi",
+    "atr",
+    "volume_profile",
+    "pivot_points",
+    "fip_id",
+}
 
 
 # ---------------------------------------------------------------------------
@@ -514,6 +588,8 @@ async def get_indicator(
         result = compute_volume_profile(highs, lows, closes, volumes)
     elif indicator_type == "pivot_points":
         result = compute_pivot_points(highs, lows, closes)
+    elif indicator_type == "fip_id":
+        result = compute_fip_id(closes)
     else:
         raise ValidationError(f"Unknown indicator type: {indicator_type}")