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https://github.com/mihakralj/QuanTAlib.git
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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.
46 lines
1.6 KiB
Plaintext
46 lines
1.6 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("Inertia Oscillator (INERTIA)", "INERTIA", overlay=false)
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//@function Calculates Inertia oscillator measuring trend strength based on distance from linear regression
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//@param source Source series to calculate Inertia for
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//@param length Period for linear regression calculation
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//@returns Inertia value measuring trend strength
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inertia(series float source, simple int length) =>
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if length <= 0
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runtime.error("Length must be positive")
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if na(source)
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na
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else
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available_bars = bar_index + 1
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effective_length = math.min(length, available_bars)
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sum_x = 0.0, sum_y = 0.0, sum_xy = 0.0, sum_x2 = 0.0
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for i = 0 to effective_length - 1
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x = effective_length - 1 - i
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y = nz(source[i])
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sum_x += x, sum_y += y
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sum_xy += x * y, sum_x2 += x * x
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n = effective_length
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denominator = n * sum_x2 - sum_x * sum_x
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if denominator == 0
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0.0
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else
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slope = (n * sum_xy - sum_x * sum_y) / denominator
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intercept = (sum_y - slope * sum_x) / n
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regression_value = slope * (effective_length - 1) + intercept
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source - regression_value
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// ---------- Main loop ----------
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// Inputs
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i_length = input.int(20, "Length", minval=1, maxval=500, tooltip="Period for linear regression calculation")
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i_source = input.source(close, "Source", tooltip="Price series to analyze")
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// Calculation
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inertia_value = inertia(i_source, i_length)
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// Plots
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plot(inertia_value, "Inertia", color=color.yellow, linewidth=2)
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