feat: signal generator — weighted ensemble with market data

shared/strategies/news_driven.py

@@ -0,0 +1,73 @@
+"""News-driven trading strategy.
+
+Buy on strong positive sentiment (score > 0.7, confidence > 0.6),
+sell on strong negative sentiment. Signal strength is the product
+of sentiment score and confidence, with a decay factor for stale news.
+"""
+
+from __future__ import annotations
+
+from datetime import datetime, timezone
+
+from shared.schemas.trading import MarketSnapshot, SentimentContext, SignalDirection, TradeSignal
+from shared.strategies.base import BaseStrategy
+
+
+class NewsDrivenStrategy(BaseStrategy):
+    """Sentiment-based strategy driven by scored news articles."""
+
+    name: str = "news_driven"
+
+    def __init__(
+        self,
+        positive_threshold: float = 0.7,
+        negative_threshold: float = -0.7,
+        min_confidence: float = 0.6,
+        min_articles: int = 1,
+    ) -> None:
+        self.positive_threshold = positive_threshold
+        self.negative_threshold = negative_threshold
+        self.min_confidence = min_confidence
+        self.min_articles = min_articles
+
+    async def evaluate(
+        self,
+        ticker: str,
+        market: MarketSnapshot,
+        sentiment: SentimentContext | None = None,
+    ) -> TradeSignal | None:
+        """Generate a signal based on aggregated news sentiment."""
+        if sentiment is None:
+            return None
+
+        if sentiment.article_count < self.min_articles:
+            return None
+
+        if sentiment.avg_confidence < self.min_confidence:
+            return None
+
+        score = sentiment.avg_score
+
+        if score > self.positive_threshold:
+            direction = SignalDirection.LONG
+        elif score < self.negative_threshold:
+            direction = SignalDirection.SHORT
+        else:
+            return None
+
+        # Strength = |score| * confidence (both in [0, 1])
+        strength = abs(score) * sentiment.avg_confidence
+        strength = min(max(strength, 0.0), 1.0)
+
+        return TradeSignal(
+            ticker=ticker,
+            direction=direction,
+            strength=round(strength, 4),
+            strategy_sources=[self.name],
+            sentiment_context={
+                "avg_score": sentiment.avg_score,
+                "article_count": sentiment.article_count,
+                "avg_confidence": sentiment.avg_confidence,
+            },
+            timestamp=datetime.now(timezone.utc),
+        )