feat(kevin-exec): size from target_dollars, propagate price, bracket entries

Kevin signals never placed orders: the executor sized only from
sentiment_context["current_price"] (None for Kevin) so qty=0, and orders
were always built SIMPLE (stop/take pcts ignored).

- TradeSignal gains `current_price`; the bridge now sets it on publish
- risk_manager honors `target_dollars` directly (no strength re-scale) and
  resolves price from current_price then sentiment_context
- executor builds BRACKET orders for LONG entries carrying stop/take pcts;
  EXIT/SELL signals stay SIMPLE (the bridge sets pcts even on exits)

[ci skip]

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

services/trade_executor/risk_manager.py

@@ -8,7 +8,6 @@ from __future__ import annotations
 
 import logging
 from datetime import datetime, timedelta
-from decimal import Decimal
 from zoneinfo import ZoneInfo
 
 from redis.asyncio import Redis
@@ -16,7 +15,7 @@ from redis.asyncio import Redis
 from services.trade_executor.config import TradeExecutorConfig
 from shared.broker.base import BaseBroker
 from shared.constants.kevin import KEVIN_STRATEGY_UUID
-from shared.schemas.trading import AccountInfo, PositionInfo, SignalDirection, TradeSignal
+from shared.schemas.trading import AccountInfo, TradeSignal
 
 logger = logging.getLogger(__name__)
 
@@ -185,14 +184,22 @@ class RiskManager:
     ) -> 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.
+        Two sizing modes:
+
+        * **Pre-computed (Kevin)** — when ``signal.target_dollars`` is set,
+          honor it directly as the position notional. The bridge has already
+          applied conviction-weighting and per-ticker headroom, so we do NOT
+          re-scale by strength.
+        * **Fixed-fractional (legacy)** — ``equity * max_position_pct`` gives
+          the max dollar value per position, then scales by signal strength.
+
+        Price is resolved from ``signal.current_price`` first, falling back to
+        ``signal.sentiment_context["current_price"]``.
 
         Parameters
         ----------
         signal:
-            The trade signal (includes current price via strength).
+            The trade signal carrying the price and (optionally) sizing.
         account:
             Current account info (equity, buying power).
 
@@ -201,26 +208,34 @@ class RiskManager:
         float
             Number of shares (whole shares).
         """
-        if signal.strength <= 0 or account.equity <= 0:
+        if 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:
+        price = self._resolve_price(signal)
+        if 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)
+        if signal.target_dollars is not None and signal.target_dollars > 0:
+            position_value = float(signal.target_dollars)
+        else:
+            if signal.strength <= 0:
+                return 0.0
+            position_value = account.equity * self.config.max_position_pct * signal.strength
+
+        return max(int(position_value / price), 0)
+
+    @staticmethod
+    def _resolve_price(signal: TradeSignal) -> float:
+        """Resolve the sizing/entry price: prefer the dedicated
+        ``current_price`` field, fall back to ``sentiment_context``."""
+        if signal.current_price is not None and signal.current_price > 0:
+            return float(signal.current_price)
+        if signal.sentiment_context and "current_price" in signal.sentiment_context:
+            ctx_price = float(signal.sentiment_context["current_price"])
+            if ctx_price > 0:
+                return ctx_price
+        return 0.0
 
     # ------------------------------------------------------------------
     # Internal helpers