RL10 - Regression Line in Python

Python

import numpy as np

def rl10(values, n=10):
    """RL10 - the fitted value of an n-bar linear regression at the most
    recent bar (the regression-line 'endpoint'). Canonical Owl Group Trading
    implementation; vectorized with np.correlate for O(N) speed.

    Returns an array the same length as `values`; the first n-1 entries are
    NaN (not enough lookback). n defaults to 10, hence 'RL10'.
    """
    values = np.asarray(values, dtype=float)
    out = np.full(len(values), np.nan)
    if n <= 0 or len(values) < n:
        return out
    # Fixed regression weights for x = [0, 1, ..., n-1] so the endpoint value
    # equals sum(w_i * y_i) for each sliding window.
    x = np.arange(n)
    x_mean = (n - 1) / 2.0
    x_diff = x - x_mean
    denom = float(np.sum(x_diff ** 2))
    if denom == 0:
        return out
    w = 1.0 / n + x_mean * x_diff / denom
    out[n - 1:] = np.correlate(values, w, mode="valid")
    return out