refactor: migrate to US stocks with Alpaca API

- Replace Binance/ccxt with Alpaca REST client (paper + live)
- Add MOC (Market on Close) strategy for overnight gap trading
- Wire sentiment into strategy engine main loop
- Add EMA + bullish candle entry filters to Asian RSI
- Remove crypto-specific exchange factory
- Update config: Alpaca keys replace Binance keys
- 399 tests passing, lint clean

1 files changed, 44 insertions, 37 deletions

diff --git a/services/strategy-engine/strategies/moc_strategy.py b/services/strategy-engine/strategies/moc_strategy.py
index bb14e78..7eaa59e 100644
--- a/services/strategy-engine/strategies/moc_strategy.py
+++ b/services/strategy-engine/strategies/moc_strategy.py
@@ -6,6 +6,7 @@ Rules:
 - Screening: bullish candle, volume above average, RSI 30-60, positive momentum
 - Risk: -2% stop loss, max 5 positions, 20% of capital per position
 """
+
 from collections import deque
 from decimal import Decimal
 from datetime import datetime
@@ -33,9 +34,9 @@ class MocStrategy(BaseStrategy):
         self._min_volume_ratio: float = 1.0  # Volume must be above average
         # Session times (UTC hours)
         self._buy_start_utc: int = 19  # 15:00 ET = 19:00 UTC (summer) / 20:00 UTC (winter)
-        self._buy_end_utc: int = 21    # 16:00 ET = 20:00 UTC / 21:00 UTC
+        self._buy_end_utc: int = 21  # 16:00 ET = 20:00 UTC / 21:00 UTC
         self._sell_start_utc: int = 13  # 9:00 ET = 13:00 UTC / 14:00 UTC
-        self._sell_end_utc: int = 15    # 10:00 ET = 14:00 UTC / 15:00 UTC
+        self._sell_end_utc: int = 15  # 10:00 ET = 14:00 UTC / 15:00 UTC
         self._max_positions: int = 5
         # State
         self._closes: deque[float] = deque(maxlen=200)
@@ -120,7 +121,7 @@ class MocStrategy(BaseStrategy):
     def _volume_above_average(self) -> bool:
         if len(self._volumes) < self._volume_avg_period:
             return True
-        avg = sum(list(self._volumes)[-self._volume_avg_period:]) / self._volume_avg_period
+        avg = sum(list(self._volumes)[-self._volume_avg_period :]) / self._volume_avg_period
         return avg > 0 and self._volumes[-1] / avg >= self._min_volume_ratio
 
     def _positive_momentum(self) -> bool:
@@ -153,31 +154,35 @@ class MocStrategy(BaseStrategy):
                 self._sold_today = True
 
                 conv = 0.8 if pnl_pct > 0 else 0.5
-                return self._apply_filters(Signal(
-                    strategy=self.name,
-                    symbol=candle.symbol,
-                    side=OrderSide.SELL,
-                    price=candle.close,
-                    quantity=Decimal(str(self._quantity_pct)),
-                    conviction=conv,
-                    reason=f"MOC sell at open, PnL {pnl_pct:.2f}%",
-                ))
+                return self._apply_filters(
+                    Signal(
+                        strategy=self.name,
+                        symbol=candle.symbol,
+                        side=OrderSide.SELL,
+                        price=candle.close,
+                        quantity=Decimal(str(self._quantity_pct)),
+                        conviction=conv,
+                        reason=f"MOC sell at open, PnL {pnl_pct:.2f}%",
+                    )
+                )
 
         # --- STOP LOSS ---
         if self._in_position:
             pnl_pct = (close - self._entry_price) / self._entry_price * 100
             if pnl_pct <= -self._stop_loss_pct:
                 self._in_position = False
-                return self._apply_filters(Signal(
-                    strategy=self.name,
-                    symbol=candle.symbol,
-                    side=OrderSide.SELL,
-                    price=candle.close,
-                    quantity=Decimal(str(self._quantity_pct)),
-                    conviction=1.0,
-                    stop_loss=candle.close,
-                    reason=f"MOC stop loss {pnl_pct:.2f}% <= -{self._stop_loss_pct}%",
-                ))
+                return self._apply_filters(
+                    Signal(
+                        strategy=self.name,
+                        symbol=candle.symbol,
+                        side=OrderSide.SELL,
+                        price=candle.close,
+                        quantity=Decimal(str(self._quantity_pct)),
+                        conviction=1.0,
+                        stop_loss=candle.close,
+                        reason=f"MOC stop loss {pnl_pct:.2f}% <= -{self._stop_loss_pct}%",
+                    )
+                )
 
         # --- BUY LOGIC (near market close) ---
         if not self._in_position and self._is_buy_window(candle.open_time):
@@ -190,11 +195,11 @@ class MocStrategy(BaseStrategy):
                 return None
 
             checks = [
-                self._rsi_min <= rsi <= self._rsi_max,      # RSI in sweet spot
-                self._is_bullish_candle(candle),              # Bullish candle
-                self._price_above_ema(),                      # Above EMA (uptrend)
-                self._volume_above_average(),                 # Volume confirmation
-                self._positive_momentum(),                    # Short-term momentum
+                self._rsi_min <= rsi <= self._rsi_max,  # RSI in sweet spot
+                self._is_bullish_candle(candle),  # Bullish candle
+                self._price_above_ema(),  # Above EMA (uptrend)
+                self._volume_above_average(),  # Volume confirmation
+                self._positive_momentum(),  # Short-term momentum
             ]
 
             if all(checks):
@@ -209,15 +214,17 @@ class MocStrategy(BaseStrategy):
 
                 sl = candle.close * (1 - Decimal(str(self._stop_loss_pct / 100)))
 
-                return self._apply_filters(Signal(
-                    strategy=self.name,
-                    symbol=candle.symbol,
-                    side=OrderSide.BUY,
-                    price=candle.close,
-                    quantity=Decimal(str(self._quantity_pct)),
-                    conviction=conv,
-                    stop_loss=sl,
-                    reason=f"MOC buy: RSI={rsi:.1f}, bullish candle, above EMA, vol OK",
-                ))
+                return self._apply_filters(
+                    Signal(
+                        strategy=self.name,
+                        symbol=candle.symbol,
+                        side=OrderSide.BUY,
+                        price=candle.close,
+                        quantity=Decimal(str(self._quantity_pct)),
+                        conviction=conv,
+                        stop_loss=sl,
+                        reason=f"MOC buy: RSI={rsi:.1f}, bullish candle, above EMA, vol OK",
+                    )
+                )
 
         return None