xel_arjona

Standard Error Bands by @XeL_arjona

Standard Error Bands - Code by @XeL_arjona
Original implementation by:
Traders issue: Stocks & Commodities V. 14:9 (375-379):
Standard Error Bands by Jon Andersen
Version 1



For a quick and publicly open explanation of this Statistical indicator, you can refer at Here!

Extract from the former URL:
Standard Error bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The error bands measure the standard error of the estimate around the linear regression line. Therefore, as a price series follows the course of the regression line the bands will narrow, showing little error in the estimate. As the market gets noisy and random, the error will be greater resulting in wider bands.


Skrip open-source

Dalam semangat TradingView, penulis dari skrip ini telah mempublikasikannya ke sumber-terbuka, maka trader dapat mengerti dan memverifikasinya. Semangat untuk penulis! Anda dapat menggunakannya secara gratis, namun penggunaan kembali kode ini dalam publikasi diatur oleh Tata Tertib. Anda dapat memfavoritkannya untuk digunakan pada chart

Pernyataan Penyangkalan

Informasi dan publikasi tidak dimaksudkan untuk menjadi, dan bukan merupakan saran keuangan, investasi, perdagangan, atau rekomendasi lainnya yang diberikan atau didukung oleh TradingView. Baca selengkapnya di Persyaratan Penggunaan.

Inggin menggunakan skrip ini pada chart?
// Standard Error Bands - Code by @XeL_arjona
// Original implementation by:
//     Traders issue: Stocks & Commodities V. 14:9 (375-379): 
//                    Standard Error Bands by Jon Andersen
// Ver 1
study(title="Standard Error Bands by @XeL_arjona", shorttitle="StDeBands", overlay=true)
len = input(defval=21, minval=1, title="Linear Regression Window:")
sm = input(true, title="Use Jon Andersen's Smooth of Median:")
src = close
// Standard Error Band Function
stdeB(array,p,mult,dir) =>
    lr = sm ? sma(linreg(array,p,0),1) : linreg(array,p,0)
    stde = stdev(lr,p)/sqrt(p)
    d = dir ? 1 : -1
    eband = lr + d * mult * stde
lrc = sma(linreg(src, len, 0),1)
m = plot(lrc, color = blue, title = "OLS Regression Curve", style = line, linewidth = 2)
ub = plot(stdeB(close,len,2,true), color = green, title = 'StdEu', style = line, linewidth = 1)
bb = plot(stdeB(close,len,2,false), color = red, title = 'StdEb', style = line, linewidth = 1)
fill(m,ub, color=olive, title="StdE_U", transp=81)
fill(m,bb, color=orange, title="StdE_B", transp=81)