mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-30 10:37:44 +00:00
Miha Kralj
50 lines
1.5 KiB
Plaintext
50 lines
1.5 KiB
Plaintext
// Licensed under the Apache License, Version 2.0
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// © mihakralj
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//@version=6
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indicator("Z-Score (ZSCORE)", "ZSCORE", overlay=false)
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//@function Calculates the Z-Score of a series over a lookback period.
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//@param src Source series.
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//@param len Lookback period. Must be greater than 1.
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//@returns The Z-Score value.
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zscore(series float src, simple int len) =>
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if len <= 1
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runtime.error("Length must be greater than 1")
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var float sumY = 0.0, var float sumY2 = 0.0
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var int validCount = 0
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var array<float> y_values = array.new_float(len)
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var int head = 0
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var bool filled = false
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float oldY = filled ? array.get(y_values, head) : na
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if not na(oldY)
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sumY -= oldY, sumY2 -= oldY * oldY, validCount -= 1
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float currentY = src
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array.set(y_values, head, currentY)
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if not na(currentY)
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sumY += currentY, sumY2 += currentY * currentY, validCount += 1
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head := (head + 1) % len
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if not filled and head == 0
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filled := true
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float zScoreValue = na
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if validCount >= 2
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float n = float(validCount), mean = sumY / n
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float variance = math.max(sumY2 / n - mean * mean, 0.0)
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float stdDev = math.sqrt(variance)
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if stdDev > 1e-10
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zScoreValue := (currentY - mean) / stdDev
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else
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zScoreValue := 0.0
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zScoreValue
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(14, "Period", minval=2)
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i_source = input.source(close, "Source")
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// Calculation
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z = zscore(i_source, i_period)
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// Plot
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plot(z, "Z-Score", color=color.yellow, linewidth=2)
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