feat: pydantic schemas for all service message types

- shared/schemas/trading.py: OrderRequest, OrderResult, PositionInfo,
  AccountInfo, TradeSignal, TradeExecution, MarketSnapshot, SentimentContext
- shared/schemas/news.py: RawArticle, ScoredArticle
- shared/schemas/learning.py: TradeOutcomeSchema, WeightAdjustment
- shared/schemas/auth.py: RegisterRequest, LoginRequest, TokenResponse
- 49 schema tests covering validation constraints, serialization round-trips,
  required fields, and range checks

shared/schemas/trading.py

@@ -0,0 +1,163 @@
+"""Trading-related Pydantic schemas for Redis Streams messages and API payloads."""
+
+from datetime import datetime
+from enum import Enum
+from typing import Any
+from uuid import UUID
+
+from pydantic import BaseModel, Field
+
+
+class OrderType(str, Enum):
+    MARKET = "market"
+    LIMIT = "limit"
+    STOP = "stop"
+
+
+class OrderSide(str, Enum):
+    BUY = "BUY"
+    SELL = "SELL"
+
+
+class OrderStatus(str, Enum):
+    PENDING = "PENDING"
+    FILLED = "FILLED"
+    CANCELLED = "CANCELLED"
+    REJECTED = "REJECTED"
+
+
+class SignalDirection(str, Enum):
+    LONG = "LONG"
+    SHORT = "SHORT"
+    NEUTRAL = "NEUTRAL"
+
+
+# ---------------------------------------------------------------------------
+# API request / response schemas
+# ---------------------------------------------------------------------------
+
+
+class OrderRequest(BaseModel):
+    """Submitted by the trade executor or the API to place an order."""
+
+    ticker: str
+    side: OrderSide
+    qty: float = Field(gt=0)
+    order_type: OrderType = OrderType.MARKET
+    limit_price: float | None = None
+    stop_price: float | None = None
+
+    model_config = {"from_attributes": True}
+
+
+class OrderResult(BaseModel):
+    """Returned after order submission or status query."""
+
+    order_id: str
+    ticker: str
+    side: OrderSide
+    qty: float
+    filled_price: float | None = None
+    status: OrderStatus
+    timestamp: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class PositionInfo(BaseModel):
+    """Current position state — used in API responses and portfolio views."""
+
+    ticker: str
+    qty: float
+    avg_entry: float
+    current_price: float
+    unrealized_pnl: float
+    market_value: float
+
+    model_config = {"from_attributes": True}
+
+
+class AccountInfo(BaseModel):
+    """Account-level summary from the brokerage."""
+
+    equity: float
+    cash: float
+    buying_power: float
+    portfolio_value: float
+
+    model_config = {"from_attributes": True}
+
+
+# ---------------------------------------------------------------------------
+# Redis Stream message schemas
+# ---------------------------------------------------------------------------
+
+
+class TradeSignal(BaseModel):
+    """Published to ``signals:generated`` by the signal generator."""
+
+    ticker: str
+    direction: SignalDirection
+    strength: float = Field(ge=0.0, le=1.0)
+    strategy_sources: list[str]
+    sentiment_context: dict[str, Any] | None = None
+    timestamp: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class TradeExecution(BaseModel):
+    """Published to ``trades:executed`` by the trade executor."""
+
+    trade_id: UUID
+    ticker: str
+    side: OrderSide
+    qty: float
+    price: float
+    status: OrderStatus
+    signal_id: UUID | None = None
+    strategy_id: UUID | None = None
+    timestamp: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class OHLCVBar(BaseModel):
+    """Single OHLCV bar."""
+
+    timestamp: datetime
+    open: float
+    high: float
+    low: float
+    close: float
+    volume: float
+
+
+class MarketSnapshot(BaseModel):
+    """Snapshot of market data for a single ticker — used by strategies."""
+
+    ticker: str
+    current_price: float
+    open: float
+    high: float
+    low: float
+    close: float
+    volume: float
+    sma_20: float | None = None
+    sma_50: float | None = None
+    rsi: float | None = None
+    bars: list[dict[str, Any]] = Field(default_factory=list)
+
+    model_config = {"from_attributes": True}
+
+
+class SentimentContext(BaseModel):
+    """Aggregated sentiment for a ticker — passed to strategies."""
+
+    ticker: str
+    avg_score: float = Field(ge=-1.0, le=1.0)
+    article_count: int = Field(ge=0)
+    recent_scores: list[float] = Field(default_factory=list)
+    avg_confidence: float = Field(ge=0.0, le=1.0)
+
+    model_config = {"from_attributes": True}