R10 / Range Stat in Python

Python

import numpy as np


def r10(high, low):
    """R10 / Range Stat: one-tenth of the typical daily range.

    R10 = (mean(range) + population_stddev(range)) / 10 computed over the 30
    EOD bars STRICTLY BEFORE the current bar (the current bar is excluded so the
    value is safe for no-look-ahead sizing). ``range`` is high - low per bar.

    This is the standard minimum-manageable-risk box used for position sizing:
    a risk unit of one-tenth of the typical daily range.

    Faithful to edge-scan ``_rangestat_from_window`` / ``compute_rangestat_for_date``
    (n_div=10, fixed 30-bar strictly-before lookback).

    Args:
        high: sequence of bar highs, ascending by date.
        low:  sequence of bar lows, ascending by date.

    Returns:
        list aligned to the input: r10[i] uses the 30 bars before index i;
        None where fewer than 2 prior bars are available.
    """
    high = np.asarray(high, dtype=float)
    low = np.asarray(low, dtype=float)
    ranges = high - low
    out = []
    for i in range(len(ranges)):
        window = ranges[max(0, i - 30):i]   # 30 bars STRICTLY BEFORE bar i
        if len(window) < 2:
            out.append(None)
            continue
        mean = float(np.mean(window))
        std_pop = float(np.std(window, ddof=0))   # population stddev
        out.append((mean + std_pop) / 10.0)
    return out