// 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 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)