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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
52 lines
1.5 KiB
Plaintext
52 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("Weighted Moving Average (WMA)", "WMA", overlay=true)
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//@function Calculates WMA using circular buffer with O(1) complexity
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//@param source Series to calculate WMA from
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//@param period Lookback period - FIR window size
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//@returns WMA value, calculates from first bar using available data
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//@optimized Uses dual running sums with cached denominator for O(1) complexity per bar
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wma(series float source, simple int period) =>
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if period <= 0
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runtime.error("Period must be greater than 0")
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var array<float> buffer = array.new_float(period, na)
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var int head = 0
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var float sum = 0.0
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var float weighted_sum = 0.0
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var int count = 0
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var float norm = 0.0
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float oldest = array.get(buffer, head)
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float current = nz(source)
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if not na(oldest)
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float old_sum = sum
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sum -= oldest
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sum += current
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weighted_sum := weighted_sum - old_sum + (period * current)
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else
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count += 1
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sum += current
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weighted_sum := weighted_sum + (count * current)
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norm := count * (count + 1) * 0.5
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array.set(buffer, head, current)
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head := (head + 1) % period
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weighted_sum / norm
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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_source = input.source(close, "Source")
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// Calculation
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wma_value = wma(i_source, i_period)
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// Plot
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plot(wma_value, "WMA", color=color.yellow, linewidth=2)
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