mirror of
https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
58 lines
2.0 KiB
Plaintext
58 lines
2.0 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("Ehlers Fractal Adaptive Moving Average (FRAMA)", "FRAMA", overlay=true)
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//@function Calculates Ehlers Fractal Adaptive Moving Average
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//@param period Lookback period (forced to even, >= 2)
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//@returns FRAMA value with fractal-adaptive smoothing
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//@optimized Uses fractal dimension for adaptive alpha with O(n) complexity per bar
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frama_strict(simple int period) =>
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int p = math.max(2, period)
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int pe = (p % 2 == 0) ? p : (p + 1)
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int h = int(pe / 2)
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// Price series per Ehlers FRAMA (commonly HL2)
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float price = hl2
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// Require enough history and non-NA ranges over the needed windows
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bool ready =
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bar_index >= pe - 1 and
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not na(price) and
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not na(ta.highest(high, pe)) and not na(ta.lowest(low, pe)) and
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not na(ta.highest(high, h)) and not na(ta.lowest(low, h)) and
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not na(ta.highest(high[h], h)) and not na(ta.lowest(low[h], h))
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var float fr = na
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if ready
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// Ranges per Ehlers:
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// N1: first half range / half
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// N2: second half range / half (shifted by half)
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// N3: full range / full
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float n1 = (ta.highest(high, h) - ta.lowest(low, h)) / h
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float n2 = (ta.highest(high[h], h) - ta.lowest(low[h], h)) / h
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float n3 = (ta.highest(high, pe) - ta.lowest(low, pe)) / pe
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float alpha = 1.0
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if n1 > 0 and n2 > 0 and n3 > 0
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float dimen = (math.log(n1 + n2) - math.log(n3)) / math.log(2.0)
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alpha := math.exp(-4.6 * (dimen - 1.0))
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alpha := math.max(0.01, math.min(1.0, alpha))
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// Warm-start: first computed value seeds to price
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float prev = nz(fr[1], price)
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fr := alpha * price + (1.0 - alpha) * prev
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else
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fr := na
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fr
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// -------- Main --------
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i_period = input.int(16, "Period (even enforced)", minval=2)
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frama_value = frama_strict(i_period)
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plot(frama_value, "FRAMA (strict)", color=color.yellow, linewidth=2)
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