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// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Percentile", "PERCENTILE", overlay=true, precision=8)
//@function Calculates the value at a given percentile for a series over a lookback period.
//@param src series float Input data series.
//@param len simple int Lookback period (must be > 0).
//@param p simple float Percentile to calculate (0-100). For example, 50 for median.
//@returns series float The value at the specified percentile, or na if insufficient data.
percentile(series float src, simple int len, simple float p) => // p is the target percentile (0-100)
if len <= 0
runtime.error("Length must be greater than 0.")
if p < 0 or p > 100
runtime.error("Percentile 'p' must be between 0 and 100.")
data_points = array.new_float()
for i = 0 to len - 1
val = src[i]
if not na(val)
array.push(data_points, val)
n_valid = array.size(data_points)
float result = na
if n_valid == 0
result := na
else if n_valid == 1
result := array.get(data_points, 0)
else
array.sort(data_points)
rank = (p / 100.0) * (n_valid - 1)
if p == 0.0
result := array.get(data_points, 0)
else if p == 100.0
result := array.get(data_points, n_valid - 1)
else
k_floor_idx = math.floor(rank)
k_ceil_idx = math.ceil(rank)
int_k_floor = int(k_floor_idx)
int_k_ceil = int(k_ceil_idx)
if int_k_floor == int_k_ceil
result := array.get(data_points, int_k_floor)
else
val_floor = array.get(data_points, int_k_floor)
val_ceil = array.get(data_points, int_k_ceil)
result := val_floor + (rank - k_floor_idx) * (val_ceil - val_floor)
result
// ---------- Main loop ----------
// Inputs
i_source = input.source(close, "Source")
i_length = input.int(14, "Period", minval=1)
i_percentile = input.float(25, "Percentile (0-100)", minval=0, maxval=100, step=0.1)
// Calculation
percentile_value = percentile(i_source, i_length, i_percentile)
// Plot
plot(percentile_value, "Percentile", color=color.new(color.yellow, 0, color=color.yellow, linewidth=2), linewidth=2)