// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0
// https://mozilla.org/MPL/2.0/
// © QuanTAlib

//@version=6
indicator("WINS: Winsorized Mean Moving Average", shorttitle="WINS", overlay=true)

// @function Calculates the Winsorized Mean Moving Average.
//   Sorts the lookback window, then replaces (not discards) the lowest and
//   highest winPct% of values with the boundary values at the trim point.
//   This robust estimator reduces outlier influence while retaining the
//   full sample size (unlike trimmed mean which discards).
//   winPct=0 → SMA, winPct=50 → all values equal the median pair.
// @param src Series to smooth.
// @param period Window length. Must be >= 3.
// @param winPct Percentage of values to winsorize from each tail (0-49). Default 10.
// @returns The winsorized mean value.
wins(series float src, simple int period, simple int winPct) =>
    // Number of values to winsorize from each end
    int winCount = math.max(int(period * winPct / 100.0), 0)
    if winCount >= period / 2
        winCount := (period - 1) / 2

    // Collect values into array and sort
    float[] vals = array.new_float(period)
    for i = 0 to period - 1
        array.set(vals, i, nz(src[i]))
    array.sort(vals, order.ascending)

    // Replace tail values with boundary values
    float lowerBound = array.get(vals, winCount)
    float upperBound = array.get(vals, period - 1 - winCount)
    for i = 0 to winCount - 1
        array.set(vals, i, lowerBound)
        array.set(vals, period - 1 - i, upperBound)

    // Average all values (including replaced ones)
    float sum = 0.0
    for i = 0 to period - 1
        sum += array.get(vals, i)
    sum / period

// ── Inputs ──────────────────────────────────────────────
p = input.int(20, "Period", minval=3)
w = input.int(10, "Winsorize %", minval=0, maxval=49, tooltip="Percentage winsorized from each tail. 0=SMA")

// ── Calculation ─────────────────────────────────────────
result = wins(close, p, w)

// ── Plot ────────────────────────────────────────────────
plot(result, "WINS", color=color.yellow, linewidth=2)