From 8b0cf4e574390738ee33f7ff334dd5f5109b7819 Mon Sep 17 00:00:00 2001
From: TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com>
Date: Wed, 1 Apr 2026 18:37:11 +0900
Subject: feat(strategy): add technical indicators library (ATR, ADX, RSI,
 MACD, Bollinger, Stochastic, OBV)

---
 .../strategies/indicators/volatility.py            | 69 ++++++++++++++++++++++
 1 file changed, 69 insertions(+)
 create mode 100644 services/strategy-engine/strategies/indicators/volatility.py

(limited to 'services/strategy-engine/strategies/indicators/volatility.py')

diff --git a/services/strategy-engine/strategies/indicators/volatility.py b/services/strategy-engine/strategies/indicators/volatility.py
new file mode 100644
index 0000000..d47eb86
--- /dev/null
+++ b/services/strategy-engine/strategies/indicators/volatility.py
@@ -0,0 +1,69 @@
+"""Volatility indicators: ATR, Bollinger Bands, Keltner Channels."""
+import pandas as pd
+import numpy as np
+
+
+def atr(
+    highs: pd.Series,
+    lows: pd.Series,
+    closes: pd.Series,
+    period: int = 14,
+) -> pd.Series:
+    """Average True Range using Wilder's smoothing."""
+    high = highs.values
+    low = lows.values
+    close = closes.values
+    n = len(close)
+
+    tr = np.zeros(n)
+    tr[0] = high[0] - low[0]
+    for i in range(1, n):
+        tr[i] = max(
+            high[i] - low[i],
+            abs(high[i] - close[i - 1]),
+            abs(low[i] - close[i - 1]),
+        )
+
+    atr_vals = np.full(n, np.nan)
+    if n >= period:
+        atr_vals[period - 1] = np.mean(tr[:period])
+        for i in range(period, n):
+            atr_vals[i] = (atr_vals[i - 1] * (period - 1) + tr[i]) / period
+
+    return pd.Series(atr_vals, index=closes.index if hasattr(closes, 'index') else None)
+
+
+def bollinger_bands(
+    closes: pd.Series,
+    period: int = 20,
+    num_std: float = 2.0,
+) -> tuple[pd.Series, pd.Series, pd.Series]:
+    """Bollinger Bands.
+
+    Returns: (upper_band, middle_band, lower_band)
+    """
+    middle = closes.rolling(window=period).mean()
+    std = closes.rolling(window=period).std()
+    upper = middle + num_std * std
+    lower = middle - num_std * std
+    return upper, middle, lower
+
+
+def keltner_channels(
+    highs: pd.Series,
+    lows: pd.Series,
+    closes: pd.Series,
+    ema_period: int = 20,
+    atr_period: int = 14,
+    atr_multiplier: float = 2.0,
+) -> tuple[pd.Series, pd.Series, pd.Series]:
+    """Keltner Channels.
+
+    Returns: (upper_channel, middle_ema, lower_channel)
+    """
+    from strategies.indicators.trend import ema as calc_ema
+    middle = calc_ema(closes, ema_period)
+    atr_vals = atr(highs, lows, closes, atr_period)
+    upper = middle + atr_multiplier * atr_vals
+    lower = middle - atr_multiplier * atr_vals
+    return upper, middle, lower
-- 
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