feat: implement SentimentAggregator with freshness decay and composite scoring

1 files changed, 69 insertions, 0 deletions

diff --git a/shared/tests/test_sentiment_aggregator.py b/shared/tests/test_sentiment_aggregator.py
new file mode 100644
index 0000000..f9277e7
--- /dev/null
+++ b/shared/tests/test_sentiment_aggregator.py
@@ -0,0 +1,69 @@
+"""Tests for sentiment aggregator."""
+import pytest
+from datetime import datetime, timezone, timedelta
+from shared.sentiment import SentimentAggregator
+
+
+@pytest.fixture
+def aggregator():
+    return SentimentAggregator()
+
+
+def test_freshness_decay_recent():
+    a = SentimentAggregator()
+    now = datetime.now(timezone.utc)
+    assert a._freshness_decay(now, now) == 1.0
+
+
+def test_freshness_decay_3_hours():
+    a = SentimentAggregator()
+    now = datetime.now(timezone.utc)
+    assert a._freshness_decay(now - timedelta(hours=3), now) == 0.7
+
+
+def test_freshness_decay_12_hours():
+    a = SentimentAggregator()
+    now = datetime.now(timezone.utc)
+    assert a._freshness_decay(now - timedelta(hours=12), now) == 0.3
+
+
+def test_freshness_decay_old():
+    a = SentimentAggregator()
+    now = datetime.now(timezone.utc)
+    assert a._freshness_decay(now - timedelta(days=2), now) == 0.0
+
+
+def test_compute_composite():
+    a = SentimentAggregator()
+    composite = a._compute_composite(news_score=0.5, social_score=0.3, policy_score=0.8, filing_score=0.2)
+    expected = 0.5 * 0.3 + 0.3 * 0.2 + 0.8 * 0.3 + 0.2 * 0.2
+    assert abs(composite - expected) < 0.001
+
+
+def test_aggregate_news_by_symbol(aggregator):
+    now = datetime.now(timezone.utc)
+    news_items = [
+        {"symbols": ["AAPL"], "sentiment": 0.8, "category": "earnings", "published_at": now},
+        {"symbols": ["AAPL"], "sentiment": 0.3, "category": "macro", "published_at": now - timedelta(hours=2)},
+        {"symbols": ["MSFT"], "sentiment": -0.5, "category": "policy", "published_at": now},
+    ]
+    scores = aggregator.aggregate(news_items, now)
+    assert "AAPL" in scores
+    assert "MSFT" in scores
+    assert scores["AAPL"].news_count == 2
+    assert scores["AAPL"].news_score > 0
+    assert scores["MSFT"].policy_score < 0
+
+
+def test_aggregate_empty(aggregator):
+    now = datetime.now(timezone.utc)
+    assert aggregator.aggregate([], now) == {}
+
+
+def test_determine_regime():
+    a = SentimentAggregator()
+    assert a.determine_regime(15, None) == "risk_off"
+    assert a.determine_regime(15, 35.0) == "risk_off"
+    assert a.determine_regime(50, 35.0) == "risk_off"
+    assert a.determine_regime(70, 15.0) == "risk_on"
+    assert a.determine_regime(50, 20.0) == "neutral"