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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
35a6702b06
Deep review of all indicator categories verified .md headers against .cs WarmupPeriod, parameters, inputs, and outputs. Fixes include warmup corrections, parameter documentation, output type accuracy, and Pine Script alignment.
65 lines
2.5 KiB
Plaintext
65 lines
2.5 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("Bollinger Band Width Normalized (BBWN)", "BBWN", overlay=false)
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//@function Calculates Bollinger Band Width Normalized to [0,1] range
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//@param source Series to calculate Bollinger Bands from
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//@param period Lookback period for BB calculations
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//@param multiplier Standard deviation multiplier for band width
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//@param lookback Historical lookback period for normalization
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//@returns BBWN value representing current BBW normalized to [0,1] range
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//@optimized for performance and dirty data
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bbwn(series float source, simple int period, simple float multiplier, simple int lookback) =>
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var int p = math.max(1, period), var int head = 0, var int count = 0
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var array<float> buffer = array.new_float(p, na)
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var float sum = 0.0, var float sumSq = 0.0
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float oldest = array.get(buffer, head)
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if not na(oldest)
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sum -= oldest
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sumSq -= oldest * oldest
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count -= 1
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float current_val = nz(source)
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sum += current_val
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sumSq += current_val * current_val
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count += 1
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array.set(buffer, head, current_val)
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head := (head + 1) % p
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float basis = nz(sum / count, source)
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float dev = count > 1 ? multiplier * math.sqrt(math.max(0.0, sumSq / count - basis * basis)) : 0.0
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float bbw = basis != 0.0 ? 2 * dev / basis : 0.0
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var int l = math.max(1, lookback), var int hist_head = 0, var int hist_count = 0
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var array<float> hist_buffer = array.new_float(l, na)
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var float min_val = bbw, var float max_val = bbw
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float hist_oldest = array.get(hist_buffer, hist_head)
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if not na(hist_oldest)
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hist_count -= 1
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if not na(bbw)
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hist_count += 1
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array.set(hist_buffer, hist_head, bbw)
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hist_head := (hist_head + 1) % l
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if hist_count >= 1
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min_val := bbw
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max_val := bbw
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for i = 0 to hist_count - 1
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float val = array.get(hist_buffer, i)
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if not na(val)
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min_val := math.min(min_val, val)
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max_val := math.max(max_val, val)
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float range_val = max_val - min_val
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range_val > 0 ? (bbw - min_val) / range_val : 0.5
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(20, "Period", minval=1)
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i_source = input.source(close, "Source")
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i_multiplier = input.float(2.0, "StdDev Multiplier", minval=0.001)
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i_lookback = input.int(252, "Lookback Period", minval=1)
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// Calculation
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bbwn_value = bbwn(i_source, i_period, i_multiplier, i_lookback)
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// Plot
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plot(bbwn_value, "BBWN", color=color.yellow, linewidth=2)
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