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.
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@@ -819,39 +819,14 @@ def _realized_vol_6m(closes: list[float], i: int) -> float | None:
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def _fip_id(closes: list[float], i: int) -> float | None:
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"""Da/Gurun/Warachka information discreteness over the 12-1 formation window.
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"""Point-in-time FIP ID for the signal harness; delegates to indicator_service."""
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from app.services.indicator_service import compute_fip_id
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from app.exceptions import ValidationError
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Formation matches ``mom_12_1``: cumulative return from close[i-252] to
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close[i-21] (231 daily returns ending one month before as-of).
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ID = sign(PRET) × (%neg − %pos)
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where %pos / %neg are fractions of up / down days over the formation window
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(zero-return days count in neither numerator, but remain in the denominator).
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Lower ID = smoother / more continuous path → expect negative cross-sectional
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IC (continuous-information winners outperform).
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"""
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if i - 252 < 0 or closes[i - 252] <= 0 or closes[i - 21] <= 0:
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try:
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return float(compute_fip_id(closes, as_of_index=i)["fip_id"])
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except (ValidationError, KeyError, TypeError, ValueError):
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return None
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pret = closes[i - 21] / closes[i - 252] - 1.0
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rets: list[float] = []
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for k in range(i - 251, i - 20):
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prev = closes[k - 1]
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if prev <= 0:
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return None
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rets.append(closes[k] / prev - 1.0)
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if len(rets) < 200:
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return None
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n = len(rets)
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pct_pos = sum(1 for r in rets if r > 0) / n
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pct_neg = sum(1 for r in rets if r < 0) / n
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if pret > 0:
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sign = 1.0
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elif pret < 0:
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sign = -1.0
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else:
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sign = 0.0
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return sign * (pct_neg - pct_pos)
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def _signal_values(
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@@ -28,6 +28,7 @@ MIN_BARS: dict[str, int] = {
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"atr": 15,
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"volume_profile": 20,
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"pivot_points": 5,
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"fip_id": 253, # 12-1 formation: need index i-252
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}
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DEFAULT_PERIODS: dict[str, int] = {
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@@ -407,6 +408,71 @@ def compute_pivot_points(
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}
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def compute_fip_id(closes: list[float], as_of_index: int | None = None) -> dict[str, Any]:
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"""Da/Gurun/Warachka information discreteness over the 12-1 formation window.
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Display / research context only — **not** used by the activation gate or
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production rank. Same window as residual 12-1 momentum: cumulative return
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from close[i-252] to close[i-21] (skip last month).
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ID = sign(PRET) × (%neg − %pos)
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Lower ID ⇒ smoother / more continuous path (for a winner: many small up days).
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Higher ID ⇒ jumpy / discrete path (few large moves). Zero-return days count
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in neither numerator but remain in the denominator.
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"""
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i = len(closes) - 1 if as_of_index is None else as_of_index
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if i < 252 or closes[i - 252] <= 0 or closes[i - 21] <= 0:
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raise ValidationError(
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f"FIP ID requires at least 253 bars with positive formation closes, "
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f"got {len(closes)}"
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)
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pret = closes[i - 21] / closes[i - 252] - 1.0
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rets: list[float] = []
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for k in range(i - 251, i - 20):
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prev = closes[k - 1]
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if prev <= 0:
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raise ValidationError("FIP ID requires positive closes in the formation window")
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rets.append(closes[k] / prev - 1.0)
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if len(rets) < 200:
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raise ValidationError(
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f"FIP ID requires ≥200 daily returns in formation, got {len(rets)}"
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)
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n = len(rets)
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pct_pos = sum(1 for r in rets if r > 0) / n
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pct_neg = sum(1 for r in rets if r < 0) / n
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if pret > 0:
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sign = 1.0
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elif pret < 0:
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sign = -1.0
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else:
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sign = 0.0
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fip = sign * (pct_neg - pct_pos)
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# Map [-1, 1] → score where lower ID (smoother) is higher for display only.
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score = max(0.0, min(100.0, 50.0 * (1.0 - fip)))
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if fip <= -0.25:
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path = "continuous"
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path_label = "smooth grind (continuous information)"
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elif fip >= 0.25:
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path = "discrete"
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path_label = "jumpy path (discrete information)"
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else:
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path = "mixed"
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path_label = "mixed path"
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return {
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"fip_id": round(fip, 4),
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"pret_12_1": round(pret, 4),
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"pct_up_days": round(pct_pos * 100.0, 1),
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"pct_down_days": round(pct_neg * 100.0, 1),
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"formation_days": n,
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"path": path,
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"path_label": path_label,
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"display_only": True,
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"note": "Not used by the production gate or rank — context only.",
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"score": round(score, 4),
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}
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def compute_ema_cross(
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closes: list[float],
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short_period: int = 20,
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@@ -451,7 +517,15 @@ def compute_ema_cross(
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# Supported indicator types
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# ---------------------------------------------------------------------------
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INDICATOR_TYPES = {"adx", "ema", "rsi", "atr", "volume_profile", "pivot_points"}
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INDICATOR_TYPES = {
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"adx",
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"ema",
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"rsi",
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"atr",
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"volume_profile",
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"pivot_points",
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"fip_id",
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}
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# ---------------------------------------------------------------------------
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@@ -514,6 +588,8 @@ async def get_indicator(
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result = compute_volume_profile(highs, lows, closes, volumes)
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elif indicator_type == "pivot_points":
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result = compute_pivot_points(highs, lows, closes)
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elif indicator_type == "fip_id":
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result = compute_fip_id(closes)
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else:
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raise ValidationError(f"Unknown indicator type: {indicator_type}")
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@@ -2,7 +2,15 @@ import { useQuery } from '@tanstack/react-query';
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import { getIndicator, getEMACross } from '../../api/indicators';
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import type { IndicatorResult } from '../../lib/types';
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const INDICATOR_TYPES = ['RSI', 'ADX', 'EMA', 'ATR', 'volume_profile', 'pivot_points'] as const;
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const INDICATOR_TYPES = [
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'RSI',
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'ADX',
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'EMA',
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'ATR',
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'volume_profile',
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'pivot_points',
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'fip_id',
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] as const;
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const INDICATOR_LABELS: Record<string, string> = {
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RSI: 'RSI',
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@@ -11,6 +19,7 @@ const INDICATOR_LABELS: Record<string, string> = {
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ATR: 'ATR · volatility',
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volume_profile: 'Volume profile',
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pivot_points: 'Pivot points',
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fip_id: 'FIP · path smoothness',
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};
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interface IndicatorSelectorProps {
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@@ -181,6 +190,22 @@ function interpretation(
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return { text: 'between pivots', tone: 'text-gray-400' };
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}
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case 'fip_id': {
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// Display context only — not a production gate input.
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const label = typeof v.path_label === 'string' ? v.path_label : null;
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const path = typeof v.path === 'string' ? v.path : null;
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if (label) {
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if (path === 'continuous') return { text: label, tone: 'text-emerald-300' };
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if (path === 'discrete') return { text: label, tone: 'text-amber-300' };
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return { text: label, tone: 'text-gray-300' };
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}
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const fip = num('fip_id');
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if (fip == null) return null;
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if (fip <= -0.25) return { text: 'smooth grind (continuous)', tone: 'text-emerald-300' };
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if (fip >= 0.25) return { text: 'jumpy path (discrete)', tone: 'text-amber-300' };
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return { text: 'mixed path', tone: 'text-gray-300' };
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}
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default:
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return null;
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}
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@@ -226,11 +251,16 @@ function IndicatorCard({ symbol, type, refPrice }: { symbol: string; type: strin
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<h4 className="num text-[10px] uppercase tracking-[0.16em] text-gray-500">
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{INDICATOR_LABELS[type] ?? type}
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</h4>
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{query.data && (
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{query.data && type.toLowerCase() !== 'fip_id' && (
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<span className="num text-[10px] text-gray-600" title={`${query.data.bars_used} bars used · normalized score`}>
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score {query.data.score.toFixed(2)}
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</span>
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)}
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{query.data && type.toLowerCase() === 'fip_id' && (
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<span className="num text-[10px] text-gray-600" title="Display only — not used by the production gate">
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context only
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</span>
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)}
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</div>
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{query.isLoading && (
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@@ -253,13 +283,25 @@ function IndicatorCard({ symbol, type, refPrice }: { symbol: string; type: strin
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) : null;
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})()}
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<dl className="mt-2.5 space-y-1.5">
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{Object.entries(query.data.values).map(([key, val]) => (
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<ValueRow key={key} name={key} val={val} refPrice={refPrice} />
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))}
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{Object.entries(query.data.values)
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.filter(([key]) => {
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// Hide meta / prose fields already shown in the interpretation line.
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if (type.toLowerCase() !== 'fip_id') return true;
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return !['path', 'path_label', 'display_only', 'note'].includes(key);
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})
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.map(([key, val]) => (
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<ValueRow key={key} name={key} val={val} refPrice={refPrice} />
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))}
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{Object.keys(query.data.values).length === 0 && (
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<p className="text-xs text-gray-500">No values.</p>
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)}
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</dl>
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{type.toLowerCase() === 'fip_id' && (
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<p className="mt-2 text-[11px] leading-snug text-gray-600">
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How smooth the past ~12-month move was (skip last month). Lower FIP usually
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means a steadier grind. Not used to qualify or rank trades.
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</p>
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)}
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</>
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)}
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</div>
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@@ -8,6 +8,7 @@ from app.services.indicator_service import (
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compute_atr,
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compute_ema,
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compute_ema_cross,
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compute_fip_id,
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compute_pivot_points,
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compute_rsi,
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compute_volume_profile,
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@@ -262,3 +263,31 @@ class TestComputeEMACross:
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closes = _rising_closes(30)
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with pytest.raises(ValidationError, match="EMA Cross requires"):
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compute_ema_cross(closes, short_period=20, long_period=50)
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# ---------------------------------------------------------------------------
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# FIP ID (display / research context — not a gate)
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# ---------------------------------------------------------------------------
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class TestComputeFipId:
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def test_steady_climber_is_continuous(self):
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# Many small up days → low (negative) ID for a positive-return path.
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closes = [100.0 * (1.002 ** i) for i in range(280)]
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result = compute_fip_id(closes)
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assert result["fip_id"] < 0
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assert result["path"] == "continuous"
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assert result["display_only"] is True
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assert 0 <= result["score"] <= 100
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def test_jump_then_flat_is_more_discrete_than_steady(self):
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steady = [100.0 * (1.002 ** i) for i in range(280)]
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jumpy = [100.0] * 252
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jumpy.append(100.0 * 1.5)
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jumpy.extend([100.0 * 1.5] * 40)
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id_steady = compute_fip_id(steady)["fip_id"]
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id_jumpy = compute_fip_id(jumpy)["fip_id"]
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assert id_jumpy > id_steady
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def test_insufficient_data_raises(self):
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with pytest.raises(ValidationError, match="FIP ID requires"):
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compute_fip_id(_rising_closes(50))
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