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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
59 lines
1.9 KiB
Plaintext
59 lines
1.9 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("Linear Regression (LINREG)", "LINREG", overlay=false, precision=8)
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//@function Calculates linear regression and slope over the specified period
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//@param src Source series to calculate linear regression from
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//@param len Lookback period for the calculation
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//@returns Tuple containing [intercept, slope]
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linreg(series float src, simple int len) =>
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if len < 2
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[na, na]
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else
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var float lastValid = na
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var array<float> buf = array.new_float(len, 0.0)
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var int count = 0
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var int head = 0
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float curr = src
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if na(curr) and not na(lastValid)
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curr := lastValid
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if not na(curr)
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lastValid := curr
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if not na(curr)
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array.set(buf, head, curr)
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if count < len
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count := count + 1
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head := (head + 1) % len
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float n = count
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if n < 2
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[na, na]
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else
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int start = count < len ? 0 : head
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float sumY = 0.0, sumXY = 0.0
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for i = 0 to int(n) - 1
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int idx = (start + i) % len
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float y_val = array.get(buf, idx)
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sumY += y_val
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sumXY += i * y_val
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float sumX = 0.5 * (n - 1) * n
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float sumX2 = (n - 1) * n * (2 * n - 1) / 6.0
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float D = n * sumX2 - sumX * sumX
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float s = D != 0 ? (n * sumXY - sumX * sumY) / D : na
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float intercept = (sumY / n) - s * ((n - 1) / 2)
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float lr = intercept + s * (n - 1)
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[lr, s]
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(14, "Period", minval=2)
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i_source = input.source(close, "Source")
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// Calculation: Assign tuple elements.
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[lr, slope] = linreg(i_source, i_period)
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// Plot
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plot(lr, "LinReg", color=color.yellow, linewidth=2)
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// plot(slope, "Slope", color=color.orange, linewidth=2, plot.style_histogram)
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