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QuantTrader/core/strategy/momentum.py

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+from typing import List, Optional
+import pandas as pd
+from datetime import datetime
+
+from .base import Strategy, SignalEvent
+from ..data.base import MarketDataEvent
+
+class MomentumStrategy(Strategy):
+    """
+    简单动量策略：当价格高于N日均线时做多，低于时做空
+    """
+    def __init__(self, instrument: str, lookback: int = 20, position_size: float = 1.0):
+        super().__init__(instrument, position_size)
+        self.lookback = lookback
+
+    async def on_data(self, event: MarketDataEvent) -> Optional[SignalEvent]:
+        if self.historical_data is None:
+            return None
+        close = event.data.get('close') or event.data.get('mid')
+        self.historical_data.loc[event.timestamp] = {
+            'open': event.data.get('open', close),
+            'high': event.data.get('high', close),
+            'low': event.data.get('low', close),
+            'close': close
+        }
+        if len(self.historical_data) < self.lookback:
+            return None
+        ma = self.historical_data['close'].rolling(self.lookback).mean()
+        if close > ma.iloc[-1] and self.can_open_position():
+            return SignalEvent(self.instrument, event.timestamp, "LONG", "BUY", strength=self.position_size)
+        if close < ma.iloc[-1] and self.can_open_position():
+            return SignalEvent(self.instrument, event.timestamp, "SHORT", "SELL", strength=self.position_size)
+        return None
+
+    async def calculate_signals(self, data: pd.DataFrame) -> List[SignalEvent]:
+        signals = []
+        self.historical_data = data.copy()
+        ma = data['close'].rolling(self.lookback).mean()
+        for i in range(self.lookback, len(data)):
+            ts = data.index[i]
+            price = data['close'].iloc[i]
+            if price > ma.iloc[i-1]:
+                signals.append(SignalEvent(self.instrument, ts, "LONG", "BUY", strength=self.position_size))
+            elif price < ma.iloc[i-1]:
+                signals.append(SignalEvent(self.instrument, ts, "SHORT", "SELL", strength=self.position_size))
+        return signals