Update

backtesting/MT5/indicator_utils.py

@@ -0,0 +1,54 @@
+"""
+Indicator calculation utilities for backtesting.
+
+These functions calculate indicators directly from price data,
+without requiring MT5 indicator handles.
+"""
+
+import numpy as np
+import pandas as pd
+
+
+def calculate_rsi(prices: pd.Series, period: int = 14) -> pd.Series:
+    """Calculate RSI indicator."""
+    delta = prices.diff()
+    gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
+    loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
+    rs = gain / loss
+    rsi = 100 - (100 / (1 + rs))
+    return rsi
+
+
+def calculate_ema(prices: pd.Series, period: int = 50) -> pd.Series:
+    """Calculate EMA indicator."""
+    return prices.ewm(span=period, adjust=False).mean()
+
+
+def calculate_sma(prices: pd.Series, period: int = 50) -> pd.Series:
+    """Calculate SMA indicator."""
+    return prices.rolling(window=period).mean()
+
+
+def calculate_atr(df: pd.DataFrame, period: int = 14) -> pd.Series:
+    """Calculate ATR indicator."""
+    high_low = df['high'] - df['low']
+    high_close = np.abs(df['high'] - df['close'].shift())
+    low_close = np.abs(df['low'] - df['close'].shift())
+    tr = pd.concat([high_low, high_close, low_close], axis=1).max(axis=1)
+    atr = tr.rolling(window=period).mean()
+    return atr
+
+
+def calculate_macd(prices: pd.Series, fast: int = 12, slow: int = 26, signal: int = 9) -> pd.DataFrame:
+    """Calculate MACD indicator."""
+    ema_fast = prices.ewm(span=fast, adjust=False).mean()
+    ema_slow = prices.ewm(span=slow, adjust=False).mean()
+    macd = ema_fast - ema_slow
+    signal_line = macd.ewm(span=signal, adjust=False).mean()
+    histogram = macd - signal_line
+    
+    return pd.DataFrame({
+        'macd': macd,
+        'signal': signal_line,
+        'histogram': histogram
+    })