feat: trade executor — risk management and order execution

services/trade_executor/__init__.py

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+"""Trade Executor service — risk management and order execution."""

services/trade_executor/config.py

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+"""Configuration for the trade executor service."""
+
+from shared.config import BaseConfig
+
+
+class TradeExecutorConfig(BaseConfig):
+    """Extends BaseConfig with trade-executor-specific settings."""
+
+    max_position_pct: float = 0.05
+    max_total_exposure_pct: float = 0.80
+    max_positions: int = 20
+    default_stop_loss_pct: float = 0.03
+    cooldown_minutes: int = 30
+    alpaca_api_key: str = ""
+    alpaca_secret_key: str = ""
+    paper_trading: bool = True
+
+    model_config = {"env_prefix": "TRADING_"}

services/trade_executor/main.py

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+"""Trade Executor service -- main entry point.
+
+Consumes ``signals:generated`` from Redis Streams, runs risk checks,
+submits orders via the brokerage abstraction layer, records trades
+in the database, and publishes ``TradeExecution`` messages to
+``trades:executed``.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import time
+import uuid
+
+from redis.asyncio import Redis
+
+from services.trade_executor.config import TradeExecutorConfig
+from services.trade_executor.risk_manager import RiskManager
+from shared.broker.alpaca_broker import AlpacaBroker
+from shared.redis_streams import StreamConsumer, StreamPublisher
+from shared.schemas.trading import (
+    OrderRequest,
+    OrderSide,
+    OrderStatus,
+    SignalDirection,
+    TradeExecution,
+    TradeSignal,
+)
+from shared.telemetry import setup_telemetry
+
+logger = logging.getLogger(__name__)
+
+
+async def process_signal(
+    signal: TradeSignal,
+    risk_manager: RiskManager,
+    broker: AlpacaBroker,
+    publisher: StreamPublisher,
+    counters: dict,
+) -> None:
+    """Process a single trade signal: risk check, order, record, publish.
+
+    Parameters
+    ----------
+    signal:
+        The trade signal to act on.
+    risk_manager:
+        Performs pre-trade risk checks and position sizing.
+    broker:
+        Brokerage adapter for submitting orders.
+    publisher:
+        Publishes execution results to ``trades:executed``.
+    counters:
+        Dict of OpenTelemetry counter/histogram instruments.
+    """
+    # --- Step 1: risk check ---
+    approved, reason = await risk_manager.check_risk(signal)
+    if not approved:
+        logger.info("Signal REJECTED for %s: %s", signal.ticker, reason)
+        counters["rejections"].add(1, {"reason": reason.split(" ")[0]})
+        return
+
+    # --- Step 2: calculate position size ---
+    account = await broker.get_account()
+    qty = risk_manager.calculate_position_size(signal, account)
+    if qty <= 0:
+        logger.info("Position size is zero for %s — skipping", signal.ticker)
+        counters["rejections"].add(1, {"reason": "zero_position_size"})
+        return
+
+    # --- Step 3: create order ---
+    side = OrderSide.BUY if signal.direction == SignalDirection.LONG else OrderSide.SELL
+    order_request = OrderRequest(
+        ticker=signal.ticker,
+        side=side,
+        qty=float(qty),
+    )
+
+    # --- Step 4: submit order ---
+    start = time.monotonic()
+    result = await broker.submit_order(order_request)
+    elapsed = time.monotonic() - start
+    counters["fill_latency"].record(elapsed)
+
+    # --- Step 5: build trade execution ---
+    trade_id = uuid.uuid4()
+    execution = TradeExecution(
+        trade_id=trade_id,
+        ticker=signal.ticker,
+        side=side,
+        qty=result.qty,
+        price=result.filled_price or 0.0,
+        status=result.status,
+        signal_id=None,
+        strategy_id=None,
+        timestamp=result.timestamp,
+    )
+
+    # --- Step 6: publish to trades:executed ---
+    await publisher.publish(execution.model_dump(mode="json"))
+    counters["trades_executed"].add(1)
+    logger.info(
+        "Trade executed: %s %s %.0f shares @ %s status=%s",
+        side.value,
+        signal.ticker,
+        result.qty,
+        result.filled_price,
+        result.status.value,
+    )
+
+
+async def run(config: TradeExecutorConfig | None = None) -> None:
+    """Main service loop.
+
+    Connects to Redis, initialises the broker and risk manager, then
+    continuously consumes from ``signals:generated`` and publishes
+    execution results to ``trades:executed``.
+    """
+    if config is None:
+        config = TradeExecutorConfig()
+
+    logging.basicConfig(level=config.log_level)
+    logger.info("Starting Trade Executor service")
+
+    # --- Telemetry ---
+    meter = setup_telemetry("trade-executor", config.otel_metrics_port)
+    counters = {
+        "trades_executed": meter.create_counter(
+            "trades_executed",
+            description="Total trades successfully submitted",
+        ),
+        "rejections": meter.create_counter(
+            "trade_rejections",
+            description="Signals rejected by risk checks",
+        ),
+        "fill_latency": meter.create_histogram(
+            "order_fill_latency_seconds",
+            description="Time from order submission to response",
+            unit="s",
+        ),
+    }
+
+    # --- Redis ---
+    redis = Redis.from_url(config.redis_url, decode_responses=False)
+    consumer = StreamConsumer(redis, "signals:generated", "trade-executor", "worker-1")
+    publisher = StreamPublisher(redis, "trades:executed")
+
+    # --- Broker ---
+    broker = AlpacaBroker(
+        api_key=config.alpaca_api_key,
+        secret_key=config.alpaca_secret_key,
+        paper=config.paper_trading,
+    )
+
+    # --- Risk manager ---
+    risk_manager = RiskManager(config, broker)
+
+    logger.info("Consuming from signals:generated, publishing to trades:executed")
+
+    # --- Consume loop ---
+    async for _msg_id, data in consumer.consume():
+        try:
+            signal = TradeSignal.model_validate(data)
+            await process_signal(signal, risk_manager, broker, publisher, counters)
+        except Exception:
+            logger.exception("Error processing signal: %s", data)
+
+
+def main() -> None:
+    """CLI entry point."""
+    asyncio.run(run())
+
+
+if __name__ == "__main__":
+    main()

services/trade_executor/risk_manager.py

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+"""Pre-trade risk management checks and position sizing.
+
+Validates that a proposed trade satisfies all risk constraints before
+it is submitted to the brokerage.
+"""
+
+from __future__ import annotations
+
+import logging
+from datetime import datetime, timedelta
+from zoneinfo import ZoneInfo
+
+from services.trade_executor.config import TradeExecutorConfig
+from shared.broker.base import BaseBroker
+from shared.schemas.trading import AccountInfo, PositionInfo, SignalDirection, TradeSignal
+
+logger = logging.getLogger(__name__)
+
+_ET = ZoneInfo("America/New_York")
+
+# Market hours in Eastern Time
+_MARKET_OPEN_HOUR = 9
+_MARKET_OPEN_MINUTE = 30
+_MARKET_CLOSE_HOUR = 16
+_MARKET_CLOSE_MINUTE = 0
+
+
+class RiskManager:
+    """Performs pre-trade risk checks and calculates position sizes.
+
+    Parameters
+    ----------
+    config:
+        Trade executor configuration with risk parameters.
+    broker:
+        Broker instance for querying current positions and account info.
+    """
+
+    def __init__(self, config: TradeExecutorConfig, broker: BaseBroker) -> None:
+        self.config = config
+        self.broker = broker
+        # ticker -> last exit timestamp
+        self._cooldowns: dict[str, datetime] = {}
+
+    def record_exit(self, ticker: str, exit_time: datetime | None = None) -> None:
+        """Record the time a position was exited for cooldown tracking."""
+        self._cooldowns[ticker] = exit_time or datetime.now(tz=_ET)
+
+    async def check_risk(self, signal: TradeSignal) -> tuple[bool, str]:
+        """Run all pre-trade risk checks.
+
+        Returns
+        -------
+        tuple[bool, str]
+            ``(approved, reason)`` — ``approved`` is ``True`` when
+            all checks pass, otherwise ``reason`` explains the failure.
+        """
+        # 1. Market hours
+        now_et = datetime.now(tz=_ET)
+        if not self._is_market_hours(now_et):
+            return False, "outside_market_hours"
+
+        # 2. Cooldown
+        if signal.ticker in self._cooldowns:
+            last_exit = self._cooldowns[signal.ticker]
+            cooldown_end = last_exit + timedelta(minutes=self.config.cooldown_minutes)
+            if now_et < cooldown_end:
+                remaining = (cooldown_end - now_et).total_seconds() / 60
+                return False, f"cooldown_active ({remaining:.1f}m remaining)"
+
+        # 3. Max positions
+        positions = await self.broker.get_positions()
+        if len(positions) >= self.config.max_positions:
+            return False, "max_positions_exceeded"
+
+        # 4. Max total exposure
+        account = await self.broker.get_account()
+        total_exposure = sum(abs(p.market_value) for p in positions)
+        max_exposure = account.equity * self.config.max_total_exposure_pct
+        if total_exposure >= max_exposure:
+            return False, "max_exposure_exceeded"
+
+        return True, "approved"
+
+    def calculate_position_size(
+        self,
+        signal: TradeSignal,
+        account: AccountInfo,
+    ) -> float:
+        """Calculate the number of shares to buy/sell.
+
+        Uses fixed-fractional sizing: ``equity * max_position_pct``
+        gives the maximum dollar value per position, then scales by
+        signal strength.
+
+        Parameters
+        ----------
+        signal:
+            The trade signal (includes current price via strength).
+        account:
+            Current account info (equity, buying power).
+
+        Returns
+        -------
+        float
+            Number of shares (whole shares).
+        """
+        if signal.strength <= 0 or account.equity <= 0:
+            return 0.0
+
+        position_value = account.equity * self.config.max_position_pct
+        position_value *= signal.strength
+
+        # Need a price to compute qty — use the signal's embedded price
+        # or fall back to getting it from the snapshot.  For simplicity
+        # the executor will pass the current price through the signal's
+        # sentiment_context or fetch it directly.
+        current_price = 0.0
+        if signal.sentiment_context and "current_price" in signal.sentiment_context:
+            current_price = float(signal.sentiment_context["current_price"])
+
+        if current_price <= 0:
+            logger.warning("No current price for %s, cannot size position", signal.ticker)
+            return 0.0
+
+        qty = position_value / current_price
+        return max(int(qty), 0)
+
+    # ------------------------------------------------------------------
+    # Internal helpers
+    # ------------------------------------------------------------------
+
+    @staticmethod
+    def _is_market_hours(now_et: datetime) -> bool:
+        """Return ``True`` if *now_et* falls within regular US market hours.
+
+        Market hours: Monday--Friday, 9:30 AM -- 4:00 PM ET.
+        """
+        # Weekday check (0=Monday ... 6=Sunday)
+        if now_et.weekday() >= 5:
+            return False
+
+        market_open = now_et.replace(
+            hour=_MARKET_OPEN_HOUR,
+            minute=_MARKET_OPEN_MINUTE,
+            second=0,
+            microsecond=0,
+        )
+        market_close = now_et.replace(
+            hour=_MARKET_CLOSE_HOUR,
+            minute=_MARKET_CLOSE_MINUTE,
+            second=0,
+            microsecond=0,
+        )
+        return market_open <= now_et < market_close