mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-27 17:27:43 +00:00
Miha Kralj
56 lines
2.1 KiB
Plaintext
56 lines
2.1 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("Gaussian-Weighted Moving Average (GWMA)", "GWMA", overlay=true)
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//@function Calculates GWMA using Gaussian window weighting
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//@param source Series to calculate GWMA from
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//@param period Lookback period - FIR window size
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//@param sigma Controls the width of the Gaussian bell curve (default: 0.4)
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//@returns GWMA value, calculates from first bar using available data
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//@optimized Uses Gaussian window coefficients with O(n) complexity per bar due to lookback loop
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gwma(series float source, simple int period, simple float sigma=0.4) =>
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if period <= 0
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runtime.error("Period must be greater than 0")
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int p = math.min(bar_index + 1, period)
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var array<float> weights = array.new_float(1, 1.0)
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var int last_p = 1
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var float last_sigma = sigma
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if last_p != p or last_sigma != sigma
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weights := array.new_float(p, 0.0)
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float center = (p - 1) / 2.0
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float inv_sigmap = 1.0 / (sigma * p)
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float total = 0.0
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for i = 0 to p - 1
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float x = (i - center) * inv_sigmap
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float w = math.exp(-0.5 * x * x)
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array.set(weights, i, w)
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total += w
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float inv_total = 1.0 / total
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for i = 0 to p - 1
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array.set(weights, i, array.get(weights, i) * inv_total)
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last_p := p
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last_sigma := sigma
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float sum = 0.0
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float weight_sum = 0.0
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for i = 0 to p - 1
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float price = source[i]
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if not na(price)
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float w = array.get(weights, i)
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sum += price * w
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weight_sum += w
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nz(sum / weight_sum, source)
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(10, "Period", minval=1)
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i_sigma = input.float(0.4, "Sigma", minval=0.1, maxval=1.0, step=0.1, tooltip="Controls the width of the Gaussian bell curve. Lower values make the curve narrower.")
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i_source = input.source(close, "Source")
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// Calculation
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gwma_value = gwma(i_source, i_period, i_sigma)
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// Plot
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plot(gwma_value, "GWMA", color=color.yellow, linewidth=2)
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