feat: add new indicators (Decay, Edecay, MinusDi, MinusDm, PlusDi, PlusDm, Maxindex, Minindex, Sarext) and update pine scripts, core libs, validation tests, and python bindings
2026-03-09 13:45:46 -07:00
// Licensed under the Apache License, Version 2.0
2026-01-18 19:02:03 -08:00
// © mihakralj
//@version=6
indicator("Garman-Klass Volatility (GKV)", "GKV", overlay=false)
//@function Calculates Garman-Klass Volatility.
//@param length The period length for smoothing the Garman-Klass estimator.
//@param annualize Boolean to indicate if the volatility should be annualized. Default is true.
//@param annualPeriods Number of periods in a year for annualization. Default is 252 for daily data.
//@returns float The Garman-Klass Volatility value.
//@optimized for performance and dirty data
gkv(simple int length, simple bool annualize = true, simple int annualPeriods = 252) =>
float lnH = math.log(high), float lnL = math.log(low), float lnO = math.log(open), float lnC = math.log(close)
float C_2LN2_1 = 0.3862941611 // 2 * math.log(2) - 1
float term1 = 0.5 * math.pow(lnH - lnL, 2)
float term2 = C_2LN2_1 * math.pow(lnC - lnO, 2)
float gkEstimator = term1 - term2
var float raw_rma_gk = 0.0, var float e_rma = 1.0
float rma_alpha = 1.0 / float(length)
if not na(gkEstimator)
raw_rma_gk := na(raw_rma_gk[1]) ? gkEstimator : (nz(raw_rma_gk[1], gkEstimator) * (length - 1) + gkEstimator) / length
e_rma := na(e_rma[1]) ? (1.0 - rma_alpha) : (1.0 - rma_alpha) * nz(e_rma[1], 1.0)
float EPSILON = 1e-10
float corrected_rma_gk = e_rma > EPSILON and not na(raw_rma_gk) ? raw_rma_gk / (1.0 - e_rma) : raw_rma_gk
float smoothedGkEstimator = nz(corrected_rma_gk, gkEstimator)
float volatility = smoothedGkEstimator < 0 ? na : math.sqrt(smoothedGkEstimator)
annualize and not na(volatility) ? volatility * math.sqrt(float(annualPeriods)) : volatility
// ---------- Main loop ----------
// Inputs
i_length = input.int(20, "Length", minval=1, tooltip="Period for smoothing the Garman-Klass estimator")
i_annualize = input.bool(true, "Annualize Volatility", tooltip="Annualize the volatility output")
i_annualPeriods = input.int(252, "Annual Periods", minval=1, tooltip="Number of periods in a year for annualization (e.g., 252 for daily, 52 for weekly)")
// Calculation
gkvValue = gkv(i_length, i_annualize, i_annualPeriods)
// Plot
plot(gkvValue, "GKV", color=color.yellow, linewidth=2)