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QuanTAlib/lib/oscillators/fosc/fosc.pine
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// The MIT License (MIT)
// © mihakralj
//@version=6
indicator("Forecast Oscillator (FOSC)", "FOSC", overlay=false)
//@function Calculates Forecast Oscillator — percentage deviation from linear regression forecast
//@param source Series to calculate from
//@param period Lookback period for linear regression
//@returns FOSC value: 100 * (source - LinReg) / source
//@optimized O(1) complexity using incremental running sums for linear regression
fosc(series float source, simple int period) =>
if period <= 0
runtime.error("Period must be greater than 0")
if period > 5000
runtime.error("Period exceeds maximum of 5000")
var int count = 0
var int head = 0
var float sumY = 0.0
var float sumXY = 0.0
var array<float> buffer = array.new_float(period, na)
if na(source)
na
else
float oldest = array.get(buffer, head)
if not na(oldest)
sumY -= oldest
sumXY -= sumY
sumXY += (period - 1) * source
else
sumXY += count * source
count += 1
sumY += source
array.set(buffer, head, source)
head := (head + 1) % period
if count < 2
0.0
else
float n = float(count)
float sumX = n * (n - 1.0) / 2.0
float sumX2 = n * (n - 1.0) * (2.0 * n - 1.0) / 6.0
float denomX = n * sumX2 - sumX * sumX
if denomX == 0.0
0.0
else
float slope = (n * sumXY - sumX * sumY) / denomX
float intercept = (sumY - slope * sumX) / n
float forecast = slope * (n - 1.0) + intercept
source != 0.0 ? (source - forecast) / source * 100.0 : 0.0
// ---------- Main loop ----------
// Inputs
i_source = input.source(close, "Source")
i_period = input.int(14, "Period", minval=2, maxval=5000)
// Calculation
float result = fosc(i_source, i_period)
// Plot
plot(result, "FOSC", color=color.yellow, linewidth=2)
hline(0, "Zero", color=color.gray, linestyle=hline.style_dotted)