mirror of
https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
61 lines
2.6 KiB
Plaintext
61 lines
2.6 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("Standard Deviation Channel (SDCHANNEL)", "SDCHANNEL", overlay=true)
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//@function Calculates Standard Deviation Channel with lines N standard deviations above and below a linear regression line
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//@param period Lookback period for regression and standard deviation calculation (period > 1)
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//@param source Source series for analysis (usually close)
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//@param multiplier Standard deviation multiplier for channel distance (multiplier > 0)
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//@returns Tuple containing [upper_channel, regression_line, lower_channel]
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//@optimized Uses linear regression with O(n) complexity per bar
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sdchannel(simple int period, series float source = close, simple float multiplier = 2.0) =>
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if period <= 1
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runtime.error("Period must be > 1")
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if multiplier <= 0.0
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runtime.error("Multiplier must be > 0")
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float sumX = 0.0
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float sumY = 0.0
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float sumXY = 0.0
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float sumX2 = 0.0
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for i = 0 to period - 1
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float x = float(i)
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float y = source[period - 1 - i]
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sumX := sumX + x
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sumY := sumY + y
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sumXY := sumXY + x * y
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sumX2 := sumX2 + x * x
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float n = float(period)
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float slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX)
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float intercept = (sumY - slope * sumX) / n
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float currentX = float(period - 1)
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float regressionLine = slope * currentX + intercept
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float sumSquaredResiduals = 0.0
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for i = 0 to period - 1
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float x = float(i)
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float y = source[period - 1 - i]
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float predicted = slope * x + intercept
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float residual = y - predicted
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sumSquaredResiduals := sumSquaredResiduals + residual * residual
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float stdDev = math.sqrt(sumSquaredResiduals / n)
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float upperChannel = regressionLine + multiplier * stdDev
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float lowerChannel = regressionLine - multiplier * stdDev
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[upperChannel, regressionLine, lowerChannel]
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// ---------- Main loop ----------
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// Inputs
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i_period = input.int(20, "Period", minval=2)
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i_source = input.source(close, "Source")
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i_multiplier = input.float(2.0, "Standard Deviation Multiplier", minval=0.1, step=0.1)
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// Calculation
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[upperLine, midLine, lowerLine] = sdchannel(i_period, i_source, i_multiplier)
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// Plot
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p1 = plot(upperLine, "Upper Channel", color=color.yellow, linewidth=2)
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p2 = plot(midLine, "Regression Line", color=color.yellow, linewidth=2)
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p3 = plot(lowerLine, "Lower Channel", color=color.yellow, linewidth=2)
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fill(p1, p2, color=color.new(color.red, 90), title="Upper Fill")
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fill(p2, p3, color=color.new(color.green, 90), title="Lower Fill")
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