PineScript/[Library] - Bands at main · dgfctr/PineScript · GitHub

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// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © dg_factor

// EXECUTION :
// https://www.tradingview.com/script/kPfdNHh6-Library-Bands/

//@version=6
library("lib_bands", overlay=true)

// Donchian Bands - Richard Donchian
export f_donchian(series float data_high, series float data_low, simple int length) =>
    ust = ta.highest(data_high, length)
    alt = ta.lowest(data_low, length)
    [ust, alt]
//

// Envelope Bands
export f_envelope(series float data, simple int ma_length, series float multiplier) =>
    ortalama = ta.sma(data, ma_length)
    ust = ortalama * (1 + multiplier / 100.)
    alt = ortalama * (1 - multiplier / 100.)
    [ust, alt]
//

// Keltner Bands - Chester Keltner
export f_keltner(series float data, simple int ma_length, simple int atr_length, series float multiplier) =>
    ortalama = ta.sma(data, ma_length)
    ust = ortalama + multiplier * ta.atr(atr_length)
    alt = ortalama - multiplier * ta.atr(atr_length)
    [ust, alt]
//

// Bollinger Bands - John Bollinger
export f_bollinger(series float data, simple int length, series float multiplier) =>
    ortalama = ta.sma(data, length)
    ust = ortalama + multiplier * ta.stdev(close, length)
    alt = ortalama - multiplier * ta.stdev(close, length)
    [ust, alt]
//

// Linear Regression Bands
export f_linreg(simple int length, series float multiplier) =>
    a = bar_index
    b = close
    c = math.sum(a, length)
    d = math.sum(b, length)
    e = math.sum(a * b, length)
    f = math.sum(a * a, length)
    g = (length * e - c * d) / (length * f - c * c)
    h = (d - g * c) / length
    j = 0.0
    for i = 0 to length - 1
        j += math.pow(b[i] - (g * (a - i) + h), 2)
        j
    k = math.sqrt(j / length) * multiplier
    l = ta.linreg(close, length, 0)
    ust = l + k
    alt = l - k
    [ust, alt]
//

// Median Bands
export f_median(simple int length, series float multiplier) =>
    a = ta.median(close, length)
    b = array.new_float(0)
    for i = 0 to length - 1
        array.push(b, math.abs(close[i] - a))
    c = array.median(b)
    d = 1.4826 * c   // Gaussian için tutarlı ölçek (Standart normal dağılımda %75’lik dilime karşılık gelen z-skoru)
    ust = a + multiplier * d
    alt = a - multiplier * d
    [ust, alt]
//

// Parkinson Volatility Bands
export f_parkinson(series float data, simple int length, series float multiplier) =>
    ortalama = ta.sma(data, length)
    a = 0.0
    for i = 0 to length - 1
        a += math.pow(math.log(high[i] / low[i]), 2)
    b = math.sqrt(a / length) / (2 * math.sqrt(math.log(2)))
    ust = ortalama * (1 + multiplier * b)
    alt = ortalama * (1 - multiplier * b)
    [ust, alt]
//

// // Theil–Sen Regression Channel (Robust Trend)
// export f_theilsen(simple int length, series float multiplier) =>
//     a = array.new_float(0)
//     for i = 0 to length - 2
//         for j = i + 1 to length - 1
//             b = (close[i] - close[j]) / (i - j)
//             array.push(a, b)
//     c = array.median(a)
//     d = array.new_float(0)
//     for i = 0 to length - 1
//         array.push(d, close[i] - c * i)
//     e = array.median(d)
//     f = c * (length - 1) + e
//     g = array.new_float(0)
//     for i = 0 to length - 1
//         fit = c * i + e
//         array.push(g, math.abs(close[i] - fit))
//     h = array.median(g)
//     ust = f + multiplier * h
//     alt = f - multiplier * h
//     [ust, alt]
// //


// Bitti :)
plotshape(barstate.isfirst, "@ dg_factor", shape.flag, location.bottom, #00000000, precision=1, editable=false)