feat: add NewsEvent, DB methods for news/sentiment/selections

- Add NEWS to EventType enum and NewsEvent class to events.py
- Add insert_news_item, get_recent_news, upsert_symbol_score,
  get_top_symbol_scores, upsert_market_sentiment,
  get_latest_market_sentiment, insert_stock_selection,
  get_stock_selections methods to Database class in db.py
- Add test_news_events.py and test_db_news.py with full coverage

2 files changed, 136 insertions, 0 deletions

diff --git a/shared/tests/test_db_news.py b/shared/tests/test_db_news.py
new file mode 100644
index 0000000..f13cf1e
--- /dev/null
+++ b/shared/tests/test_db_news.py
@@ -0,0 +1,80 @@
+"""Tests for database news/sentiment methods. Uses in-memory SQLite."""
+
+import json
+import uuid
+import pytest
+from datetime import datetime, date, timezone
+
+from shared.db import Database
+from shared.models import NewsItem, NewsCategory
+from shared.sentiment_models import SymbolScore, MarketSentiment
+
+
+@pytest.fixture
+async def db():
+    database = Database("sqlite+aiosqlite://")
+    await database.connect()
+    yield database
+    await database.close()
+
+
+async def test_insert_and_get_news_items(db):
+    item = NewsItem(
+        source="finnhub",
+        headline="AAPL earnings beat",
+        published_at=datetime(2026, 4, 2, 12, 0, tzinfo=timezone.utc),
+        sentiment=0.8,
+        category=NewsCategory.EARNINGS,
+        symbols=["AAPL"],
+    )
+    await db.insert_news_item(item)
+    items = await db.get_recent_news(hours=24)
+    assert len(items) == 1
+    assert items[0]["headline"] == "AAPL earnings beat"
+
+
+async def test_upsert_symbol_score(db):
+    score = SymbolScore(
+        symbol="AAPL",
+        news_score=0.5,
+        news_count=10,
+        social_score=0.3,
+        policy_score=0.0,
+        filing_score=0.2,
+        composite=0.3,
+        updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc),
+    )
+    await db.upsert_symbol_score(score)
+    scores = await db.get_top_symbol_scores(limit=5)
+    assert len(scores) == 1
+    assert scores[0]["symbol"] == "AAPL"
+
+
+async def test_upsert_market_sentiment(db):
+    ms = MarketSentiment(
+        fear_greed=55,
+        fear_greed_label="Neutral",
+        vix=18.2,
+        fed_stance="neutral",
+        market_regime="neutral",
+        updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc),
+    )
+    await db.upsert_market_sentiment(ms)
+    result = await db.get_latest_market_sentiment()
+    assert result is not None
+    assert result["fear_greed"] == 55
+
+
+async def test_insert_stock_selection(db):
+    await db.insert_stock_selection(
+        trade_date=date(2026, 4, 2),
+        symbol="NVDA",
+        side="BUY",
+        conviction=0.85,
+        reason="CHIPS Act",
+        key_news=["Trump signs CHIPS expansion"],
+        sentiment_snapshot={"composite": 0.8},
+    )
+    selections = await db.get_stock_selections(date(2026, 4, 2))
+    assert len(selections) == 1
+    assert selections[0]["symbol"] == "NVDA"
diff --git a/shared/tests/test_news_events.py b/shared/tests/test_news_events.py
new file mode 100644
index 0000000..384796a
--- /dev/null
+++ b/shared/tests/test_news_events.py
@@ -0,0 +1,56 @@
+"""Tests for NewsEvent."""
+
+from datetime import datetime, timezone
+
+from shared.models import NewsCategory, NewsItem
+from shared.events import NewsEvent, EventType, Event
+
+
+def test_news_event_to_dict():
+    item = NewsItem(
+        source="finnhub",
+        headline="Test",
+        published_at=datetime(2026, 4, 2, tzinfo=timezone.utc),
+        sentiment=0.5,
+        category=NewsCategory.MACRO,
+    )
+    event = NewsEvent(data=item)
+    d = event.to_dict()
+    assert d["type"] == EventType.NEWS
+    assert d["data"]["source"] == "finnhub"
+
+
+def test_news_event_from_raw():
+    raw = {
+        "type": "NEWS",
+        "data": {
+            "id": "abc",
+            "source": "rss",
+            "headline": "Test headline",
+            "published_at": "2026-04-02T00:00:00+00:00",
+            "sentiment": 0.3,
+            "category": "earnings",
+            "symbols": ["AAPL"],
+            "raw_data": {},
+        },
+    }
+    event = NewsEvent.from_raw(raw)
+    assert event.data.source == "rss"
+    assert event.data.symbols == ["AAPL"]
+
+
+def test_event_dispatcher_news():
+    raw = {
+        "type": "NEWS",
+        "data": {
+            "id": "abc",
+            "source": "finnhub",
+            "headline": "Test",
+            "published_at": "2026-04-02T00:00:00+00:00",
+            "sentiment": 0.0,
+            "category": "macro",
+            "raw_data": {},
+        },
+    }
+    event = Event.from_dict(raw)
+    assert isinstance(event, NewsEvent)