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"""Volatility indicators: ATR, Bollinger Bands, Keltner Channels."""
import numpy as np
import pandas as pd
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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