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QuanTAlib/lib/statistics/zscore/zscore.pine
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Miha Kralj 86fe32a682 SIMD Refactor: Merge simd-dev into dev (#55)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>
2026-01-18 19:02:03 -08:00

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// The MIT License (MIT)
// © mihakralj
//@version=6
indicator("Z-Score (ZSCORE)", "ZSCORE", overlay=false)
//@function Calculates the Z-Score of a series over a lookback period.
//@doc https://github.com/mihakralj/pinescript/blob/main/indicators/statistics/zscore.md
//@param src Source series.
//@param len Lookback period. Must be greater than 1.
//@returns The Z-Score value.
zscore(series float src, simple int len) =>
if len <= 1
runtime.error("Length must be greater than 1")
var float sumY = 0.0, var float sumY2 = 0.0
var int validCount = 0
var array<float> y_values = array.new_float(len)
var int head = 0
var bool filled = false
float oldY = filled ? array.get(y_values, head) : na
if not na(oldY)
sumY -= oldY, sumY2 -= oldY * oldY, validCount -= 1
float currentY = src
array.set(y_values, head, currentY)
if not na(currentY)
sumY += currentY, sumY2 += currentY * currentY, validCount += 1
head := (head + 1) % len
if not filled and head == 0
filled := true
float zScoreValue = na
if validCount >= 2
float n = float(validCount), mean = sumY / n
float variance = math.max(sumY2 / n - mean * mean, 0.0)
float stdDev = math.sqrt(variance)
if stdDev > 1e-10
zScoreValue := (currentY - mean) / stdDev
else
zScoreValue := 0.0
zScoreValue
// ---------- Main loop ----------
// Inputs
i_period = input.int(14, "Period", minval=2)
i_source = input.source(close, "Source")
// Calculation
z = zscore(i_source, i_period)
// Plot
plot(z, "Z-Score", color=color.yellow, linewidth=2)