Revert blue-sky projection; keep played-out setup UX

A local backtest (offline prod snapshot, 506 tickers) evaluated blue-sky
projected targets under the PRODUCTION exit (3x ATR trailing + 30d max hold,
paper_trade_service DEFAULT_EXIT_MODE="atr_trailing"). Blue-sky setups are
dilutive: the qualified book scored 328% return / Sharpe 1.84 / DD -21.0%
WITHOUT them vs 300% / 1.58 / -18.7% WITH them. They rank high on momentum by
construction, so they grab slots from S/R setups that catch bigger runs under
a trailing-stop exit (only ~2pp worse drawdown doesn't justify the lost return
and Sharpe).

Reverts the scanner/TargetGenerator measured-move projection, the stricter
projected activation gate, the frontend qualification mirror, the `projected`
type field, and the projected tests -- all backend files are now byte-identical
to the pre-blue-sky commit.

Keeps the played-out "No current setup" UX (RecommendationPanel): when price
has run past the target (played out) or through the stop (invalidated), the
panel shows a plain no-setup state instead of a stale actionable card. This is
frontend-only (reads last close + existing setup fields) and is what actually
fixes the reported stale-below-price bug -- no backend change or rescan needed.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/services/qualification.py

@@ -16,15 +16,6 @@ from typing import Any
 
 HIGH_CONVICTION_ACTIONS = {"LONG_HIGH", "SHORT_HIGH"}
 
-# A projected (blue-sky) target has no S/R validation — it is a measured-move
-# extension used when nothing sits overhead. Because that is exactly the kind of
-# unvalidated target the gate exists to distrust, a projected setup clears a
-# STRICTER bar than an S/R-anchored one, regardless of whether the general
-# momentum gate is active: long-only (breakout continuation), strong residual
-# momentum, and a higher confidence floor. Mirrored in frontend/src/lib/qualification.ts.
-PROJECTED_MIN_MOMENTUM_PERCENTILE = 90.0
-PROJECTED_CONFIDENCE_MARGIN = 10.0
-
 
 def _action_direction(action: str | None) -> str:
     if not action or action == "NEUTRAL":
@@ -55,19 +46,6 @@ def primary_target_probability(setup: Any) -> float | None:
     return best if best > 0 else None
 
 
-def primary_target_is_projected(setup: Any) -> bool:
-    """Whether the setup's headline target is a blue-sky measured-move projection.
-
-    Prefers the starred primary; falls back to any projected target when none is
-    explicitly flagged primary (matches primary_target_probability's fallback).
-    """
-    targets = getattr(setup, "targets", None) or []
-    for target in targets:
-        if isinstance(target, dict) and target.get("is_primary"):
-            return bool(target.get("projected"))
-    return any(isinstance(t, dict) and t.get("projected") for t in targets)
-
-
 def live_risk_reward(setup: Any, current_price: float) -> float | None:
     """R:R recomputed from the CURRENT price, not the (possibly stale) entry.
 
@@ -124,18 +102,6 @@ def setup_qualifies(setup: Any, config: dict) -> bool:
         momentum_percentile = getattr(setup, "momentum_percentile", None)
         if momentum_percentile is None or momentum_percentile < min_pct:
             return False
-    # Projected (blue-sky) targets clear a stricter bar than S/R-anchored ones,
-    # independent of the general momentum gate above: long-only, strong residual
-    # momentum, and a higher confidence floor. The target has no S/R validation,
-    # so we only trust it for high-momentum breakout continuations.
-    if primary_target_is_projected(setup):
-        if (getattr(setup, "direction", "long") or "long").lower() != "long":
-            return False
-        momentum_percentile = getattr(setup, "momentum_percentile", None)
-        if momentum_percentile is None or momentum_percentile < PROJECTED_MIN_MOMENTUM_PERCENTILE:
-            return False
-        if (setup.confidence_score or 0.0) < config["min_confidence"] + PROJECTED_CONFIDENCE_MARGIN:
-            return False
     # A setup is actionable only when the live ticker action points in the same
     # direction. NEUTRAL means no clear signal; an opposite action means the
     # setup is counter-bias. ``exclude_neutral`` defaults on; callers that omit

app/services/recommendation_service.py

@@ -44,16 +44,6 @@ _MODERATE_MAX_ATR = 4.6
 # the same tolerance the chart and alerts use, so S/R is one model app-wide.
 _SR_ZONE_TOLERANCE = 0.02
 
-# Measured-move projection used when a ticker has NO S/R level overhead in the
-# trade direction (genuine blue-sky, e.g. a stock at all-time highs). Without
-# this the scanner produces no setup and the last (now stale) one lingers. The
-# projected target sits this many ATRs from entry, so with the default 1.5-ATR
-# stop it is a clean 2:1 R:R. Projected targets carry no touch history, so they
-# take near-zero strength (small probability haircut via the strength magnet) and
-# face a stricter activation bar — see app/services/qualification.py.
-PROJECTED_TARGET_ATR_MULTIPLE = 3.0
-PROJECTED_TARGET_STRENGTH = 10.0
-
 
 def _clamp(value: float, low: float, high: float) -> float:
     return max(low, min(high, value))
@@ -320,43 +310,7 @@ class TargetGenerator:
             )
 
         if not candidates:
-            # No S/R level in the trade direction cleared the ATR distance
+            return []
-            # filter. If there is genuinely NO S/R overhead at all (blue-sky,
-            # e.g. all-time highs), project a measured-move target so a breakout
-            # name still yields a setup. When overhead S/R DOES exist but was
-            # merely too close/far to qualify, produce nothing as before — we
-            # never project a target through real, nearby resistance.
-            #
-            # Check both the level's tag AND its price. Zone representatives are
-            # typed relative to entry, so a resistance cluster straddling entry
-            # counts as overhead even if its near edge sits just below (which
-            # keeps this aligned with the scanner's raw ``levels_above`` gate);
-            # the price comparison covers raw levels for other callers.
-            has_overhead = any(
-                (direction == "long" and (lv.type == "resistance" or lv.price_level > entry_price))
-                or (direction == "short" and (lv.type == "support" or lv.price_level < entry_price))
-                for lv in sr_levels
-            )
-            if has_overhead:
-                return []
-            projected_price = (
-                entry_price + PROJECTED_TARGET_ATR_MULTIPLE * atr_value
-                if direction == "long"
-                else entry_price - PROJECTED_TARGET_ATR_MULTIPLE * atr_value
-            )
-            reward = abs(projected_price - entry_price)
-            return [
-                {
-                    "price": float(projected_price),
-                    "distance_from_entry": float(reward),
-                    "distance_atr_multiple": float(reward / atr_value),
-                    "rr_ratio": float(reward / risk),
-                    "classification": "Moderate",
-                    "sr_level_id": -1,
-                    "sr_strength": float(PROJECTED_TARGET_STRENGTH),
-                    "projected": True,
-                }
-            ]
 
         # Select up to 5 targets that SPAN the distance range, instead of the
         # top-5 by quality (which biases toward far, high-R:R levels and buries
@@ -496,11 +450,9 @@ def _choose_recommended_action(
     """Pick the ticker action — but only recommend a direction you can trade.
 
     A direction is recommendable only if a tradeable setup exists for it
-    (``available_directions``). A strong LONG bias on a stock with no tradeable
+    (``available_directions``). So a strong LONG bias on a stock at all-time
-    long setup does NOT yield LONG_HIGH; it falls through to NEUTRAL, and the
+    highs — where the scanner can build no long target — does NOT yield
-    reasoning explains why. (At genuine all-time highs the scanner now projects a
+    LONG_HIGH; it falls through to NEUTRAL, and the reasoning explains why.
-    measured-move long target, so blue-sky names can be recommendable; a name
-    capped just under resistance — with no ≥threshold R:R — still cannot.)
     """
     high = float(config.get("recommendation_high_confidence_threshold", 70.0))
     moderate = float(config.get("recommendation_moderate_confidence_threshold", 50.0))
@@ -706,14 +658,7 @@ async def enhance_trade_setup(
 
     # Per-setup conflicts (target availability is specific to this setup)
     setup_conflicts = list(conflicts)
-    primary_projected = bool(primary is not None and primary.get("projected"))
+    if len(targets) < 3:
-    if primary_projected:
-        # Blue-sky: no overhead S/R to anchor to. Flag it so the target's basis
-        # is explicit rather than looking like a normal S/R level.
-        setup_conflicts.append(
-            "projected-target: No overhead resistance — target is an ATR measured-move projection"
-        )
-    elif len(targets) < 3:
         setup_conflicts.append("target-availability: Fewer than 3 valid S/R targets available")
 
     # Action and reasoning are ticker-level: they consider both directions and

app/services/rr_scanner_service.py

@@ -29,7 +29,6 @@ from app.models.trade_setup import TradeSetup
 from app.services.indicator_service import _extract_ohlcv, compute_atr
 from app.services.price_service import query_ohlcv
 from app.services.recommendation_service import (
-    PROJECTED_TARGET_ATR_MULTIPLE,
     _risk_level_from_conflicts,
     build_recommendation_snapshot,
     enhance_trade_setup,
@@ -68,16 +67,6 @@ def _compute_quality_score(
     return w_rr * norm_rr + w_strength * norm_strength + w_proximity * norm_proximity
 
 
-def _projected_target(direction: str, entry_price: float, atr_value: float) -> float:
-    """Measured-move target for a blue-sky direction (no overhead S/R).
-
-    Mirrors the projection in recommendation_service so the scanner's emission
-    decision and the enhanced target agree.
-    """
-    move = PROJECTED_TARGET_ATR_MULTIPLE * atr_value
-    return entry_price + move if direction == "long" else entry_price - move
-
-
 async def _get_dimension_scores(db: AsyncSession, ticker_id: int) -> dict[str, float]:
     result = await db.execute(
         select(DimensionScore).where(DimensionScore.ticker_id == ticker_id)
@@ -439,13 +428,13 @@ async def scan_ticker(
     now = datetime.now(timezone.utc)
     setups: list[TradeSetup] = []
 
-    stop = entry_price - (atr_value * atr_multiplier)
+    if levels_above:
-    risk = entry_price - stop
+        stop = entry_price - (atr_value * atr_multiplier)
-    if risk > 0:
+        risk = entry_price - stop
-        best_candidate_rr = 0.0
+        if risk > 0:
-        best_candidate_target = 0.0
-        if levels_above:
             best_quality = 0.0
+            best_candidate_rr = 0.0
+            best_candidate_target = 0.0
             for lv in levels_above:
                 reward = lv.price_level - entry_price
                 if reward <= 0:
@@ -459,29 +448,21 @@ async def scan_ticker(
                     best_quality = quality
                     best_candidate_rr = rr
                     best_candidate_target = lv.price_level
-        else:
-            # Blue-sky: no resistance overhead. Project a measured-move target so
-            # a breakout name still yields a setup (it faces a stricter gate).
-            projected = _projected_target("long", entry_price, atr_value)
-            projected_rr = (projected - entry_price) / risk
-            if projected_rr >= rr_threshold:
-                best_candidate_rr = projected_rr
-                best_candidate_target = projected
 
-        if best_candidate_rr > 0:
+            if best_candidate_rr > 0:
-            setups.append(TradeSetup(
+                setups.append(TradeSetup(
-                ticker_id=ticker.id,
+                    ticker_id=ticker.id,
-                direction="long",
+                    direction="long",
-                entry_price=round(entry_price, 4),
+                    entry_price=round(entry_price, 4),
-                stop_loss=round(stop, 4),
+                    stop_loss=round(stop, 4),
-                target=round(best_candidate_target, 4),
+                    target=round(best_candidate_target, 4),
-                rr_ratio=round(best_candidate_rr, 4),
+                    rr_ratio=round(best_candidate_rr, 4),
-                composite_score=round(composite_score, 4),
+                    composite_score=round(composite_score, 4),
-                detected_at=now,
+                    detected_at=now,
-                momentum_percentile=momentum_percentile,
+                    momentum_percentile=momentum_percentile,
-                strategy_rank=strategy_rank,
+                    strategy_rank=strategy_rank,
-                volatility_percentile=volatility_percentile,
+                    volatility_percentile=volatility_percentile,
-            ))
+                ))
 
     if levels_below:
         stop = entry_price + (atr_value * atr_multiplier)

frontend/src/components/ticker/RecommendationPanel.tsx

@@ -103,7 +103,6 @@ function TargetTable({ setup }: { setup: TradeSetup }) {
               <td className="py-2 pr-3 text-gray-300">
                 {target.is_primary && <span className="mr-1 text-blue-300">★</span>}
                 {target.classification}
-                {target.projected && <span className="ml-1 text-sky-400">(projected)</span>}
               </td>
               <td className="py-2 pr-3 font-mono text-gray-200">{formatPrice(target.price)}</td>
               <td className="py-2 pr-3 font-mono text-gray-200">{formatPercent((target.distance_from_entry / setup.entry_price) * 100)}</td>
@@ -130,7 +129,6 @@ function SetupCard({ setup, action, currentPrice, risk, regime }: { setup?: Trad
   const drift = entryDrift(setup, currentPrice);
   const sizing = positionSize(risk.accountSize, risk.riskPct, setup.entry_price, setup.stop_loss);
   const counterTrend = regime ? isCounterTrend(setup.direction, regime.label) : false;
-  const primaryProjected = setup.targets?.some((t) => t.is_primary && t.projected) ?? false;
 
   // When price has run to/past the target (played out) or through the stop
   // (invalidated), there is no fresh setup — show a plain "no current setup"
@@ -205,11 +203,6 @@ function SetupCard({ setup, action, currentPrice, risk, regime }: { setup?: Trad
         </p>
       )}
 
-      {primaryProjected && (
-        <p className="text-[11px] text-sky-400">
-          ⚑ Blue-sky: no resistance overhead — target is an ATR measured-move projection, not an S/R level.
-        </p>
-      )}
       {drift && drift.status === 'invalidated' && (
         <p className="text-[11px] text-red-400">
           ⚠ Price ({formatPrice(currentPrice!)}) is past the stop — this setup is invalidated.

frontend/src/lib/qualification.ts

@@ -2,20 +2,6 @@ import type { ActivationConfig, TradeSetup } from './types';
 
 const HIGH_CONVICTION_ACTIONS = new Set(['LONG_HIGH', 'SHORT_HIGH']);
 
-// Projected (blue-sky) targets clear a stricter bar than S/R-anchored ones —
-// long-only, strong momentum, higher confidence floor. Mirrors the constants in
-// app/services/qualification.py; keep the two in sync.
-const PROJECTED_MIN_MOMENTUM_PERCENTILE = 90;
-const PROJECTED_CONFIDENCE_MARGIN = 10;
-
-/** Whether the setup's headline target is a blue-sky measured-move projection. */
-export function primaryTargetIsProjected(setup: TradeSetup): boolean {
-  const targets = setup.targets ?? [];
-  const primary = targets.find((t) => t.is_primary);
-  if (primary) return Boolean(primary.projected);
-  return targets.some((t) => t.projected);
-}
-
 function actionDirection(action: TradeSetup['recommended_action']): 'long' | 'short' | 'neutral' {
   if (!action || action === 'NEUTRAL') return 'neutral';
   if (action.startsWith('LONG')) return 'long';
@@ -65,16 +51,6 @@ export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boo
       return false;
     }
   }
-  // Projected (blue-sky) targets clear a stricter bar than S/R-anchored ones,
-  // independent of the general momentum gate: long-only, strong momentum, higher
-  // confidence floor. Mirrors app/services/qualification.py.
-  if (primaryTargetIsProjected(setup)) {
-    if (setup.direction !== 'long') return false;
-    if (setup.momentum_percentile == null || setup.momentum_percentile < PROJECTED_MIN_MOMENTUM_PERCENTILE) {
-      return false;
-    }
-    if ((setup.confidence_score ?? 0) < config.min_confidence + PROJECTED_CONFIDENCE_MARGIN) return false;
-  }
   // NEUTRAL = "no clear setup"; an opposite action means this setup is counter-bias.
   if (config.exclude_neutral) {
     const actionDir = actionDirection(setup.recommended_action);

frontend/src/lib/types.ts

@@ -577,8 +577,6 @@ export interface TradeTarget {
   sr_level_id: number;
   sr_strength: number;
   is_primary?: boolean;
-  /** Blue-sky measured-move target (no overhead S/R); sr_level_id is -1. */
-  projected?: boolean;
 }
 
 export interface RecommendationSummary {

tests/unit/test_projected_targets.py

@@ -1,201 +0,0 @@
-"""Tests for blue-sky projected targets.
-
-When a ticker has NO S/R level overhead in the trade direction (e.g. a stock at
-all-time highs), the scanner would otherwise produce no setup and the last stale
-one would linger. Instead we project a measured-move (ATR) target so a breakout
-name still yields a setup — one that faces a stricter activation bar. These
-tests cover the target generator's projection rule and the scanner emission.
-"""
-
-from __future__ import annotations
-
-from datetime import date, datetime, timedelta, timezone
-from types import SimpleNamespace
-
-import pytest
-from sqlalchemy.ext.asyncio import AsyncSession
-
-from app.models.ohlcv import OHLCVRecord
-from app.models.score import CompositeScore
-from app.models.sr_level import SRLevel
-from app.models.ticker import Ticker
-from app.services.recommendation_service import (
-    PROJECTED_TARGET_ATR_MULTIPLE,
-    PROJECTED_TARGET_STRENGTH,
-    target_generator,
-)
-from app.services.rr_scanner_service import scan_ticker
-
-
-def _lvl(price: float, type_: str, strength: int = 50, id_: int = 1) -> SimpleNamespace:
-    return SimpleNamespace(id=id_, price_level=price, type=type_, strength=strength)
-
-
-class TestGenerateTargetsProjection:
-    """target_generator.generate_targets(direction, entry, stop, sr_levels, atr)."""
-
-    def test_blue_sky_long_projects_target(self):
-        # Entry 100, stop 97 (risk 3), ATR 2 — no resistance overhead at all.
-        targets = target_generator.generate_targets(
-            direction="long",
-            entry_price=100.0,
-            stop_loss=97.0,
-            sr_levels=[_lvl(90.0, "support"), _lvl(85.0, "support")],
-            atr_value=2.0,
-        )
-        assert len(targets) == 1
-        t = targets[0]
-        assert t["projected"] is True
-        assert t["sr_level_id"] == -1
-        assert t["sr_strength"] == PROJECTED_TARGET_STRENGTH
-        # 100 + 3 ATR (=6) = 106; reward 6 / risk 3 = 2.0 R:R
-        assert t["price"] == pytest.approx(100.0 + PROJECTED_TARGET_ATR_MULTIPLE * 2.0)
-        assert t["rr_ratio"] == pytest.approx(2.0)
-
-    def test_blue_sky_with_no_levels_at_all_projects(self):
-        targets = target_generator.generate_targets(
-            direction="long", entry_price=100.0, stop_loss=97.0, sr_levels=[], atr_value=2.0,
-        )
-        assert len(targets) == 1 and targets[0]["projected"] is True
-
-    def test_overhead_resistance_too_close_does_not_project(self):
-        # A resistance 0.5 ATR above (< 1.0 ATR min distance) is filtered out as a
-        # candidate — but it IS real overhead, so we must NOT project through it.
-        targets = target_generator.generate_targets(
-            direction="long",
-            entry_price=100.0,
-            stop_loss=97.0,
-            sr_levels=[_lvl(101.0, "resistance")],
-            atr_value=2.0,
-        )
-        assert targets == []
-
-    def test_normal_overhead_resistance_is_not_projected(self):
-        targets = target_generator.generate_targets(
-            direction="long",
-            entry_price=100.0,
-            stop_loss=97.0,
-            sr_levels=[_lvl(106.0, "resistance", strength=80)],
-            atr_value=2.0,
-        )
-        assert len(targets) == 1
-        assert not targets[0].get("projected")
-        assert targets[0]["sr_level_id"] == 1
-
-    def test_resistance_tagged_straddle_does_not_project(self):
-        # A resistance-tagged zone rep whose near edge sits just BELOW entry still
-        # means real overhead — never project through it, even though its price is
-        # under entry and it isn't a valid candidate.
-        targets = target_generator.generate_targets(
-            direction="long",
-            entry_price=100.0,
-            stop_loss=97.0,
-            sr_levels=[_lvl(99.5, "resistance"), _lvl(90.0, "support")],
-            atr_value=2.0,
-        )
-        assert targets == []
-
-    def test_blue_sky_short_projects_below(self):
-        targets = target_generator.generate_targets(
-            direction="short",
-            entry_price=100.0,
-            stop_loss=103.0,
-            sr_levels=[_lvl(110.0, "resistance")],
-            atr_value=2.0,
-        )
-        assert len(targets) == 1
-        assert targets[0]["projected"] is True
-        assert targets[0]["price"] == pytest.approx(100.0 - PROJECTED_TARGET_ATR_MULTIPLE * 2.0)
-
-
-# ---------------------------------------------------------------------------
-# Scanner emission
-# ---------------------------------------------------------------------------
-
-@pytest.fixture
-async def scan_session() -> AsyncSession:
-    from tests.conftest import _test_session_factory
-
-    async with _test_session_factory() as session:
-        yield session
-
-
-def _make_bars(ticker_id: int, num_bars: int = 20, base_close: float = 100.0):
-    bars = []
-    start = date(2024, 1, 1)
-    for i in range(num_bars):
-        close = base_close + (i % 3 - 1) * 0.5
-        bars.append(OHLCVRecord(
-            ticker_id=ticker_id,
-            date=start + timedelta(days=i),
-            open=close - 0.3,
-            high=close + 1.0,
-            low=close - 1.0,
-            close=close,
-            volume=100_000,
-        ))
-    return bars
-
-
-@pytest.mark.asyncio
-async def test_scan_emits_projected_long_when_blue_sky(scan_session: AsyncSession):
-    """A ticker with only support below entry (no overhead) yields a projected long."""
-    ticker = Ticker(symbol="BLUESKY")
-    scan_session.add(ticker)
-    await scan_session.flush()
-
-    scan_session.add_all(_make_bars(ticker.id, num_bars=20, base_close=100.0))
-    # Only support levels below entry — nothing overhead.
-    scan_session.add_all([
-        SRLevel(ticker_id=ticker.id, price_level=95.0, type="support", strength=80,
-                detection_method="pivot_point"),
-        SRLevel(ticker_id=ticker.id, price_level=90.0, type="support", strength=60,
-                detection_method="pivot_point"),
-    ])
-    scan_session.add(CompositeScore(
-        ticker_id=ticker.id, score=70.0, is_stale=False, weights_json="{}",
-        computed_at=datetime.now(timezone.utc),
-    ))
-    await scan_session.commit()
-
-    setups = await scan_ticker(scan_session, "BLUESKY", rr_threshold=1.5, atr_multiplier=1.5)
-
-    long_setups = [s for s in setups if s.direction == "long"]
-    assert len(long_setups) == 1, "blue-sky ticker should still yield a long setup"
-    long_setup = long_setups[0]
-
-    # Target is the measured-move projection, well above entry, R:R ~2.0.
-    assert long_setup.target > long_setup.entry_price
-    assert long_setup.rr_ratio == pytest.approx(2.0, abs=0.05)
-
-    primary = [t for t in long_setup.targets if t.get("is_primary")]
-    assert primary and primary[0]["projected"] is True
-    assert primary[0]["sr_level_id"] == -1
-    assert any("projected-target" in c for c in long_setup.conflict_flags)
-
-
-@pytest.mark.asyncio
-async def test_scan_does_not_project_when_resistance_overhead(scan_session: AsyncSession):
-    """With a normal resistance overhead, the long target is that S/R level, not a projection."""
-    ticker = Ticker(symbol="CAPPED")
-    scan_session.add(ticker)
-    await scan_session.flush()
-
-    scan_session.add_all(_make_bars(ticker.id, num_bars=20, base_close=100.0))
-    scan_session.add_all([
-        SRLevel(ticker_id=ticker.id, price_level=106.0, type="resistance", strength=80,
-                detection_method="pivot_point"),
-        SRLevel(ticker_id=ticker.id, price_level=95.0, type="support", strength=60,
-                detection_method="pivot_point"),
-    ])
-    scan_session.add(CompositeScore(
-        ticker_id=ticker.id, score=70.0, is_stale=False, weights_json="{}",
-        computed_at=datetime.now(timezone.utc),
-    ))
-    await scan_session.commit()
-
-    setups = await scan_ticker(scan_session, "CAPPED", rr_threshold=1.5, atr_multiplier=1.5)
-    long_setups = [s for s in setups if s.direction == "long"]
-    assert len(long_setups) == 1
-    primary = [t for t in long_setups[0].targets if t.get("is_primary")]
-    assert primary and not primary[0].get("projected")

tests/unit/test_qualification.py

@@ -6,7 +6,6 @@ from types import SimpleNamespace
 
 from app.services.qualification import (
     best_target_probability,
-    primary_target_is_projected,
     primary_target_probability,
     setup_qualifies,
 )
@@ -156,54 +155,6 @@ class TestExcludeNeutral:
         assert setup_qualifies(_setup(recommended_action="NEUTRAL"), DEFAULT_GATE) is True
 
 
-def _projected_setup(**kwargs):
-    """A setup whose primary (headline) target is a blue-sky projection."""
-    base = dict(
-        direction="long",
-        momentum_percentile=92.0,
-        confidence_score=80.0,
-        targets=[{"probability": 30.0, "is_primary": True, "projected": True}],
-    )
-    base.update(kwargs)
-    return _setup(**base)
-
-
-class TestProjectedTargetGate:
-    """Projected targets clear a stricter bar, independent of the momentum gate."""
-
-    def test_projected_passes_stricter_bar(self):
-        # DEFAULT_GATE has the momentum selection OFF, yet the projected block
-        # still requires strong momentum + higher confidence — and this one clears.
-        assert setup_qualifies(_projected_setup(), DEFAULT_GATE) is True
-
-    def test_projected_fails_below_momentum_floor(self):
-        assert setup_qualifies(_projected_setup(momentum_percentile=85.0), DEFAULT_GATE) is False
-
-    def test_projected_fails_missing_momentum(self):
-        assert setup_qualifies(_projected_setup(momentum_percentile=None), DEFAULT_GATE) is False
-
-    def test_projected_fails_below_raised_confidence_floor(self):
-        # min_confidence 55 + 10 margin = 65; a 60% confidence projected setup fails
-        # even though it would clear the plain 55 floor.
-        assert setup_qualifies(_projected_setup(confidence_score=60.0), DEFAULT_GATE) is False
-
-    def test_projected_short_never_qualifies(self):
-        s = _projected_setup(direction="short", recommended_action="SHORT_HIGH")
-        assert setup_qualifies(s, DEFAULT_GATE) is False
-
-    def test_sr_anchored_setup_unaffected_by_projected_bar(self):
-        # A normal (non-projected) setup with modest momentum still passes DEFAULT.
-        assert setup_qualifies(_setup(momentum_percentile=10.0), DEFAULT_GATE) is True
-
-    def test_primary_target_is_projected_helper(self):
-        assert primary_target_is_projected(_projected_setup()) is True
-        assert primary_target_is_projected(_setup()) is False
-
-    def test_projected_flag_falls_back_when_no_primary(self):
-        s = _setup(targets=[{"probability": 30.0, "projected": True}])
-        assert primary_target_is_projected(s) is True
-
-
 class TestBestTargetProbability:
     def test_returns_max(self):
         s = _setup(targets=[{"probability": 40.0}, {"probability": 72.0}, {"probability": 55.0}])