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strategies/ma_cross_strategy.py

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+import pandas as pd
+from strategies.base_strategy import BaseStrategy
+import logging
+
+class MaCrossStrategy(BaseStrategy):
+    """
+    A strategy based on a fast Simple Moving Average (SMA) crossing
+    a slow SMA.
+    """
+    def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame:
+        # Support multiple naming conventions: some configs use 'fast'/'slow'
+        # while others use 'short_ma'/'long_ma'. Normalize here so both work.
+        fast_ma_period = self.params.get('short_ma') or self.params.get('fast') or 0
+        slow_ma_period = self.params.get('long_ma') or self.params.get('slow') or 0
+        
+        # If parameters are missing, return a neutral signal frame.
+        if not fast_ma_period or not slow_ma_period:
+            logging.warning(f"Missing MA period parameters (fast={fast_ma_period}, slow={slow_ma_period}).")
+            df['signal'] = 0
+            return df
+
+        if len(df) < slow_ma_period:
+            logging.warning(f"Not enough data for MA periods {fast_ma_period}/{slow_ma_period}. Need {slow_ma_period}, have {len(df)}.")
+            df['signal'] = 0
+            return df
+            
+        df['fast_sma'] = df['close'].rolling(window=fast_ma_period).mean()
+        df['slow_sma'] = df['close'].rolling(window=slow_ma_period).mean()
+        
+        # Signal is 1 for Golden Cross (fast > slow), -1 for Death Cross
+        df['signal'] = 0
+        df.loc[df['fast_sma'] > df['slow_sma'], 'signal'] = 1
+        df.loc[df['fast_sma'] < df['slow_sma'], 'signal'] = -1
+        
+        return df