Initial project structure: MarketScanner - Fear-to-Fortune Trading Intelligence

Features:
- FastAPI backend with stocks, news, signals, watchlist, analytics endpoints
- React frontend with TailwindCSS dark mode trading dashboard
- Celery workers for news fetching, sentiment analysis, pattern detection
- TimescaleDB schema for time-series stock data
- Docker Compose setup for all services
- OpenAI integration for sentiment analysis

backend/app/schemas/signal.py

@@ -0,0 +1,39 @@
+"""Signal schemas."""
+
+from typing import Optional
+from datetime import datetime
+from uuid import UUID
+from pydantic import BaseModel
+
+
+class SignalBase(BaseModel):
+    """Base signal schema."""
+    stock_id: UUID
+    signal_price: float
+    confidence_score: float
+
+
+class SignalResponse(SignalBase):
+    """Schema for signal response."""
+    id: UUID
+    signal_time: datetime
+    status: str
+    current_drawdown_percent: Optional[float] = None
+    current_sentiment_score: Optional[float] = None
+    expected_recovery_percent: Optional[float] = None
+    expected_recovery_days: Optional[int] = None
+    created_at: datetime
+    
+    class Config:
+        from_attributes = True
+
+
+class SignalWithDetails(SignalResponse):
+    """Signal response with full details."""
+    panic_event_id: Optional[UUID] = None
+    pattern_id: Optional[UUID] = None
+    triggered_at: Optional[datetime] = None
+    outcome_price: Optional[float] = None
+    outcome_percent: Optional[float] = None
+    outcome_days: Optional[int] = None
+    updated_at: datetime