mirror of
https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
73 lines
2.3 KiB
Plaintext
73 lines
2.3 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("Correlation Trend Indicator (CTI)", "CTI", overlay=false)
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//@function Calculates Pearson correlation between price and linear time index
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//@param source Series to calculate correlation from
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//@param period Lookback period for correlation window
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//@returns CTI value (-1 to +1) measuring linear trend strength
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//@optimized O(1) complexity using incremental running sums
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cti(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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if period > 5000
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runtime.error("Period exceeds maximum of 5000")
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var int count = 0
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var int head = 0
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var float sumY = 0.0
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var float sumY2 = 0.0
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var float sumXY = 0.0
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var array<float> buffer = array.new_float(period, na)
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if na(source)
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na
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else
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float oldest = array.get(buffer, head)
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if not na(oldest)
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sumY -= oldest
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sumY2 -= oldest * oldest
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sumXY -= sumY
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sumXY += (period - 1) * source
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else
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sumXY += count * source
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count += 1
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sumY += source
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sumY2 += source * source
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array.set(buffer, head, source)
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head := (head + 1) % period
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if count < 2
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na
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else
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float n = float(count)
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float sumX = n * (n - 1.0) / 2.0
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float sumX2 = n * (n - 1.0) * (2.0 * n - 1.0) / 6.0
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float denomX = n * sumX2 - sumX * sumX
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float denomY = n * sumY2 - sumY * sumY
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float denom = denomX * denomY
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if denom <= 0.0
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0.0
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else
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float numer = n * sumXY - sumX * sumY
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float r = numer / math.sqrt(denom)
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math.max(-1.0, math.min(1.0, r))
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// ---------- Main loop ----------
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// Inputs
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i_source = input.source(close, "Source")
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i_period = input.int(20, "Period", minval=2, maxval=5000)
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// Calculation
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cti_value = cti(i_source, i_period)
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// Plot
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plot(cti_value, "CTI", color.new(color.yellow, 0), 2)
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hline(0, "Zero", color=color.gray, linestyle=hline.style_dotted)
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hline(0.5, "Upper", color=color.gray, linestyle=hline.style_dotted)
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hline(-0.5, "Lower", color=color.gray, linestyle=hline.style_dotted)
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