mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 01:37:43 +00:00
Miha Kralj
52 lines
2.4 KiB
Plaintext
52 lines
2.4 KiB
Plaintext
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0
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// https://mozilla.org/MPL/2.0/
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// © QuanTAlib
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//@version=6
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indicator("WINS: Winsorized Mean Moving Average", shorttitle="WINS", overlay=true)
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// @function Calculates the Winsorized Mean Moving Average.
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// Sorts the lookback window, then replaces (not discards) the lowest and
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// highest winPct% of values with the boundary values at the trim point.
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// This robust estimator reduces outlier influence while retaining the
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// full sample size (unlike trimmed mean which discards).
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// winPct=0 → SMA, winPct=50 → all values equal the median pair.
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// @param src Series to smooth.
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// @param period Window length. Must be >= 3.
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// @param winPct Percentage of values to winsorize from each tail (0-49). Default 10.
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// @returns The winsorized mean value.
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wins(series float src, simple int period, simple int winPct) =>
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// Number of values to winsorize from each end
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int winCount = math.max(int(period * winPct / 100.0), 0)
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if winCount >= period / 2
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winCount := (period - 1) / 2
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// Collect values into array and sort
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float[] vals = array.new_float(period)
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for i = 0 to period - 1
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array.set(vals, i, nz(src[i]))
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array.sort(vals, order.ascending)
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// Replace tail values with boundary values
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float lowerBound = array.get(vals, winCount)
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float upperBound = array.get(vals, period - 1 - winCount)
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for i = 0 to winCount - 1
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array.set(vals, i, lowerBound)
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array.set(vals, period - 1 - i, upperBound)
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// Average all values (including replaced ones)
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float sum = 0.0
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for i = 0 to period - 1
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sum += array.get(vals, i)
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sum / period
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// ── Inputs ──────────────────────────────────────────────
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p = input.int(20, "Period", minval=3)
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w = input.int(10, "Winsorize %", minval=0, maxval=49, tooltip="Percentage winsorized from each tail. 0=SMA")
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// ── Calculation ─────────────────────────────────────────
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result = wins(close, p, w)
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// ── Plot ────────────────────────────────────────────────
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plot(result, "WINS", color=color.yellow, linewidth=2)
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