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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
47 lines
1.9 KiB
Plaintext
47 lines
1.9 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Kurtosis, tailedness (KURTOSIS)", "KURTOSIS", overlay=false, precision=8)
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//@function Calculates the excess kurtosis 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 excess kurtosis value.
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kurtosis(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, var float sumY3 = 0.0, var float sumY4 = 0.0
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var int validCount = 0, var array<float> y_values = array.new_float(len), var int head = 0, 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, sumY3 -= oldY * oldY * oldY, sumY4 -= oldY * oldY * 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, sumY3 += currentY * currentY * currentY, sumY4 += currentY * currentY * 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 excessKurtosis = na
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if validCount >= 4
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float n = float(validCount), mean = sumY / n, m2 = sumY2 / n, m3 = sumY3 / n, m4 = sumY4 / n
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float variance = math.max(m2 - mean * mean, 0.0)
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if variance > 1e-10
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float moment4 = m4 - 4 * mean * m3 + 6 * mean * mean * m2 - 3 * mean * mean * mean * mean
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excessKurtosis := moment4 / (variance * variance) - 3.0
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else
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excessKurtosis := 0.0
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excessKurtosis
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(14, "Period", minval=4) // Minval 4 for kurtosis
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i_source = input.source(close, "Source")
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// Calculation
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k = kurtosis(i_source, i_period)
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// Plot
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plot(k, "Kurtosis", color=color.yellow, linewidth=2)
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