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2026-08-17 19:08:06 +00:00 · 2025-11-14 22:56:44 +00:00
parent cf1944a688
commit ef6e1e278d
96 changed files with 3300 additions and 0 deletions
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+from typing import List, Optional
+import pandas as pd
+from datetime import datetime
+
+from .base import Strategy, SignalEvent
+from .base import Position
+from ..data.base import MarketDataEvent
+
+class MACrossoverStrategy(Strategy):
+    """
+    简单移动平均交叉策略
+    快线上穿慢线做多，下穿做空
+    """
+    def __init__(self, instrument: str, fast_period: int = 50, slow_period: int = 200, position_size: float = 1.0):
+        super().__init__(instrument, position_size)
+        self.fast_period = fast_period
+        self.slow_period = slow_period
+
+    async def on_data(self, event: MarketDataEvent) -> Optional[SignalEvent]:
+        if self.historical_data is None:
+            return None
+        # 更新收盘价
+        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.slow_period:
+            return None
+
+        fast = self.historical_data['close'].rolling(self.fast_period).mean()
+        slow = self.historical_data['close'].rolling(self.slow_period).mean()
+
+        if fast.iloc[-2] <= slow.iloc[-2] and fast.iloc[-1] > slow.iloc[-1]:
+            return SignalEvent(
+                instrument=self.instrument,
+                timestamp=event.timestamp,
+                signal_type="LONG",
+                direction="BUY",
+                strength=self.position_size
+            )
+        if fast.iloc[-2] >= slow.iloc[-2] and fast.iloc[-1] < slow.iloc[-1]:
+            return SignalEvent(
+                instrument=self.instrument,
+                timestamp=event.timestamp,
+                signal_type="SHORT",
+                direction="SELL",
+                strength=self.position_size
+            )
+        return None
+
+    async def calculate_signals(self, data: pd.DataFrame) -> List[SignalEvent]:
+        signals = []
+        self.historical_data = data.copy()
+        fast = data['close'].rolling(self.fast_period).mean()
+        slow = data['close'].rolling(self.slow_period).mean()
+        for i in range(self.slow_period, len(data)):
+            ts = data.index[i]
+            if fast.iloc[i-1] <= slow.iloc[i-1] and fast.iloc[i] > slow.iloc[i]:
+                signals.append(SignalEvent(instrument=self.instrument, timestamp=ts, signal_type="LONG", direction="BUY", strength=self.position_size))
+            if fast.iloc[i-1] >= slow.iloc[i-1] and fast.iloc[i] < slow.iloc[i]:
+                signals.append(SignalEvent(instrument=self.instrument, timestamp=ts, signal_type="SHORT", direction="SELL", strength=self.position_size))
+        return signals