fix: rank-based allocator + momentum signal (reversal->momentum flip)

strategies/alpha_strategy.py

@@ -4,23 +4,49 @@ import pandas as pd
 
 
 class AlphaStrategy(bt.Strategy):
-    """Trade each feed based on its precomputed ``signal`` line.
+    """Trade feeds based on precomputed ``signal`` line.
 
-    The strategy delegates the buy/sell/hold decision to a portfolio builder
-    (e.g. ``ThresholdBuilder``) and sizes entries with ``order_target_percent``.
+    Supports two builder modes:
+    - ThresholdBuilder: per-stock threshold (passed ``(signal_value, in_position)``)
+    - RankEqualWeightBuilder: cross-sectional ranking (passed ``{symbol: signal}`` dict)
     """
 
     def __init__(self, builder):
         self.builder = builder
 
     def next(self):
+        # Collect all signals
+        signals: dict[str, float] = {}
         for data in self.datas:
             sig = data.signal[0]
-            if pd.isna(sig):
-                continue
-            in_position = bool(self.getposition(data).size)
-            action = self.builder.build(float(sig), in_position)
-            if action.action == "buy":
-                self.order_target_percent(data=data, target=action.size_pct)
-            elif action.action == "sell":
-                self.close(data=data)
+            if not pd.isna(sig):
+                signals[data._name] = float(sig)
+
+        if not signals:
+            return
+
+        # Detect builder type: if RankEqualWeightBuilder, use cross-sectional mode
+        from portfolio.builder import RankEqualWeightBuilder
+        if isinstance(self.builder, RankEqualWeightBuilder):
+            actions = self.builder.build(signals)
+            for data in self.datas:
+                name = data._name
+                if name not in actions:
+                    continue
+                action = actions[name]
+                if action.action == "buy":
+                    self.order_target_percent(data=data, target=action.size_pct)
+                elif action.action == "sell":
+                    self.close(data=data)
+        else:
+            # Legacy per-stock ThresholdBuilder
+            for data in self.datas:
+                name = data._name
+                if name not in signals:
+                    continue
+                in_position = bool(self.getposition(data).size)
+                action = self.builder.build(signals[name], in_position)
+                if action.action == "buy":
+                    self.order_target_percent(data=data, target=action.size_pct)
+                elif action.action == "sell":
+                    self.close(data=data)