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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.
89 lines
3.2 KiB
Plaintext
89 lines
3.2 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 Reflex Indicator (REFLEX)", "REFLEX", overlay = false)
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//@function Ehlers Reflex — a zero-lag oscillator that measures the reflex (reversal
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// tendency) of price by comparing the SSF-filtered price against a linear
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// extrapolation from N bars ago. Applies a 2-pole Super Smoother pre-filter
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// at half the specified period, then computes slope = (Filt[N] - Filt) / N,
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// sums deviations of the extrapolated line from actual filtered values over
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// the window, and normalizes by exponential RMS. Values above 0 suggest
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// uptrend, below 0 suggest downtrend; crossovers signal reversals.
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//@param source Series to analyze
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//@param period Lookback window / assumed cycle period (>= 2)
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//@returns Reflex oscillator value (normalized, roughly ±σ scale)
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//@reference Ehlers, J.F. (2020). "Reflex: A New Zero-Lag Indicator."
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// Technical Analysis of Stocks & Commodities, Feb 2020.
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//@optimized O(period) per bar for the summation loop; SSF is O(1) IIR
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reflex(series float source, simple int period) =>
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if period < 2
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runtime.error("Period must be at least 2")
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float price = nz(source)
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// --- 2-Pole Super Smoother Filter (half-period cutoff) ---
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float half_period = period * 0.5
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float a1 = math.exp(-1.414 * math.pi / half_period)
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float b1 = 2.0 * a1 * math.cos(1.414 * math.pi / half_period)
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float c2 = b1
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float c3 = -(a1 * a1)
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float c1 = 1.0 - c2 - c3
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var float filt = 0.0
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var float filt1 = 0.0
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var float filt2 = 0.0
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float src1 = nz(source[1])
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filt2 := filt1
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filt1 := filt
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filt := c1 * (price + src1) * 0.5 + c2 * filt1 + c3 * filt2
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// --- Circular buffer to store filtered values for lookback ---
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var array<float> buf = array.new_float(period + 1, 0.0)
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var int head = 0
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array.set(buf, head, filt)
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int count = math.min(bar_index + 1, period)
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// --- Slope: (Filt[Length] - Filt) / Length ---
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int lag_idx = (head - period + period + 1) % (period + 1)
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float filt_lag = array.get(buf, lag_idx)
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float slope = (filt_lag - filt) / period
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// --- Sum the differences ---
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// Sum = Σ(i=1..Length) [(Filt + i*Slope) - Filt[i]] / Length
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float the_sum = 0.0
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if count >= period
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for i = 1 to period
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int idx = (head - i + period + 1) % (period + 1)
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float filt_i = array.get(buf, idx)
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the_sum += (filt + float(i) * slope) - filt_i
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the_sum /= period
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// --- Advance head ---
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head := (head + 1) % (period + 1)
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// --- Normalize in terms of Standard Deviations ---
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// MS = 0.04 * Sum² + 0.96 * MS[1] (exponential RMS)
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var float ms = 0.0
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ms := 0.04 * the_sum * the_sum + 0.96 * ms
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float result = 0.0
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if ms > 0.0
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result := the_sum / math.sqrt(ms)
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result
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// ── Inputs ──
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int p_period = input.int(20, "Period", minval = 2)
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float p_src = input.source(close, "Source")
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// ── Calculation ──
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float out = reflex(p_src, p_period)
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// ── Plot ──
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plot(out, "REFLEX", color.yellow, 2)
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hline(0, "Zero", color.gray)
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hline(1.0, "+1σ", color.new(color.red, 60))
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hline(-1.0, "-1σ", color.new(color.green, 60))
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