- {weight != null && (
+ {d.dimension === 'sentiment' && compositeBreakdown?.sentiment_adjustment != null ? (
+
;
formula: string;
+ base_score?: number | null;
+ sentiment_score?: number | null;
+ sentiment_adjustment?: number | null;
+ max_sentiment_adjustment?: number | null;
}
export interface ScoreResponse {
diff --git a/tests/unit/test_scoring_sentiment_adjustment.py b/tests/unit/test_scoring_sentiment_adjustment.py
new file mode 100644
index 0000000..8908c88
--- /dev/null
+++ b/tests/unit/test_scoring_sentiment_adjustment.py
@@ -0,0 +1,91 @@
+"""Composite scoring: sentiment applied as a signed adjustment around neutral,
+not averaged in. Going from no sentiment to bullish must never lower the score."""
+
+from __future__ import annotations
+
+from datetime import datetime, timezone
+
+import pytest
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
+
+from app.database import Base
+from app.models.score import DimensionScore
+from app.models.ticker import Ticker
+from app.services import scoring_service as svc
+
+
+@pytest.fixture
+async def db():
+ engine = create_async_engine("sqlite+aiosqlite://", echo=False)
+ async with engine.begin() as conn:
+ await conn.run_sync(Base.metadata.create_all)
+ factory = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
+ async with factory() as session:
+ yield session
+ await engine.dispose()
+
+
+# Non-sentiment dims all at 78 → base = 78 at any positive weights.
+BASE_DIMS = {"technical": 78.0, "sr_quality": 78.0, "fundamental": 78.0, "momentum": 78.0}
+
+
+async def _seed(session, dims: dict[str, float]) -> None:
+ ticker = Ticker(symbol="AAA")
+ session.add(ticker)
+ await session.flush()
+ now = datetime.now(timezone.utc)
+ for dim, score in dims.items():
+ session.add(DimensionScore(
+ ticker_id=ticker.id, dimension=dim, score=score, is_stale=False, computed_at=now
+ ))
+ await session.flush()
+
+
+def test_sentiment_adjustment_formula():
+ # weight 0.10 → MAX_ADJ = 10 points
+ assert svc._sentiment_adjustment(None, 0.10) == 0.0
+ assert svc._sentiment_adjustment(50.0, 0.10) == 0.0 # neutral / coin-flip
+ assert svc._sentiment_adjustment(75.0, 0.10) == pytest.approx(5.0) # bullish 75%
+ assert svc._sentiment_adjustment(100.0, 0.10) == pytest.approx(10.0)
+ assert svc._sentiment_adjustment(25.0, 0.10) == pytest.approx(-5.0) # bearish 75%
+ assert svc._sentiment_adjustment(0.0, 0.10) == pytest.approx(-10.0)
+
+
+async def test_no_sentiment_equals_base(db):
+ await _seed(db, BASE_DIMS)
+ composite, missing = await svc.compute_composite_score(db, "AAA")
+ assert composite == pytest.approx(78.0)
+ assert "sentiment" in missing
+
+
+async def test_bullish_raises_above_base(db):
+ await _seed(db, {**BASE_DIMS, "sentiment": 75.0}) # bullish, 75% confidence
+ composite, _ = await svc.compute_composite_score(db, "AAA")
+ assert composite == pytest.approx(83.0) # 78 + 5 — the whole point
+
+
+async def test_neutral_leaves_base_unchanged(db):
+ await _seed(db, {**BASE_DIMS, "sentiment": 50.0})
+ composite, _ = await svc.compute_composite_score(db, "AAA")
+ assert composite == pytest.approx(78.0)
+
+
+async def test_bearish_lowers_base(db):
+ await _seed(db, {**BASE_DIMS, "sentiment": 25.0}) # bearish, 75% confidence
+ composite, _ = await svc.compute_composite_score(db, "AAA")
+ assert composite == pytest.approx(73.0) # 78 - 5
+
+
+async def test_only_sentiment_uses_neutral_base(db):
+ await _seed(db, {"sentiment": 75.0})
+ composite, _ = await svc.compute_composite_score(db, "AAA")
+ assert composite == pytest.approx(55.0) # base 50 + 5
+
+
+async def test_no_dimensions_returns_none(db):
+ ticker = Ticker(symbol="AAA")
+ db.add(ticker)
+ await db.flush()
+ composite, missing = await svc.compute_composite_score(db, "AAA")
+ assert composite is None
+ assert len(missing) == 5