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"""Momentum indicators: RSI, Stochastic."""
import pandas as pd
import numpy as np
def rsi(closes: pd.Series, period: int = 14) -> pd.Series:
"""RSI using Wilder's smoothing (EMA-based)."""
delta = closes.diff()
gain = delta.clip(lower=0)
loss = -delta.clip(upper=0)
avg_gain = gain.ewm(com=period - 1, min_periods=period).mean()
avg_loss = loss.ewm(com=period - 1, min_periods=period).mean()
rs = avg_gain / avg_loss
rsi_vals = pd.Series(np.where(avg_loss == 0, 100.0, 100 - (100 / (1 + rs))), index=closes.index)
# Keep NaN where we don't have enough data
rsi_vals[:period] = np.nan
return rsi_vals
def stochastic(
highs: pd.Series,
lows: pd.Series,
closes: pd.Series,
k_period: int = 14,
d_period: int = 3,
) -> tuple[pd.Series, pd.Series]:
"""Stochastic Oscillator.
Returns: (%K, %D)
"""
lowest_low = lows.rolling(window=k_period).min()
highest_high = highs.rolling(window=k_period).max()
denom = highest_high - lowest_low
k = 100 * (closes - lowest_low) / denom.replace(0, float("nan"))
d = k.rolling(window=d_period).mean()
return k, d
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