Average Absolute Error Normalization

Intel CorporationNASDAQ

描述

⋅ 2019年11月15日下午4點17分

Normalization often involve the ratio of a quantity over a variable in order to bring that quantity in a specific scale (fixed/non-fixed). Normalized oscillators are common types of oscillators used in technical analysis.

The proposed indicator is a normalized oscillator in a scale (-1,1) and is based on the average error between the price and a specific moving average divided by the average absolute error. The indicator can be smoother by checking the "smoother" option.

The interpretation is the same as any other type of oscillators, overbought/sold levels are also provided (-0.8,0.8) by default.

Oscillators

評論

ICEKI

⋅ 2019年11月17日早上12點02分

Appreciated for your work and sharing Alex =D

GensisAlgo

⋅ 2019年11月16日晚上9點42分

This is amazing , thanks for sharing

sudhir.mehta

⋅ 2019年11月16日下午2點33分

Hi Alex,

Thanks for sharing Great Work!!!!!!!!! It is Great, love it!!!!!!

Jabba01

⋅ 2019年11月15日晚上10點09分

thanks for blowing our mind in 3 lines, you're amazing at that game!

Pratik_4Clover

⋅ 2019年11月15日晚上7點12分

Thanks! :)

DannyBaker

⋅ 2019年11月15日晚上6點16分

Great alex!

Here is my modification with an auto length adjustment base on the cycle.

tradingview.com/script/r1YJQ1yH-AAEN-With-Auto-Length-Adjust-to-Cycle/

syrinxflunki

⋅ 2019年11月15日晚上6點13分

GOODY !

dpanday

⋅ 2019年11月15日下午5點23分

Nice

Gornidah

⋅ 2019年11月15日下午5點02分

Excellent Work! ( as always) thank you ;)

DannyBaker

⋅ 2019年11月21日下午4點57分

hi alex i'm trying to use you quadratic regression ma instead of a sma in your average absolute error normalization, but it is not acting as i expected. i have used a zlema and it works great. i am just trying to take a little more lag out of it. any suggestions?

//@version=4 study("Average Absolute Error Normalization","AEN") length = input(18, step = 1) tol = input(0.8, title = "Tolerance", step = 0.01) smo = input(false,"Smoother") src = close //---- quadReg(y,length)=> x1 = bar_index x2 = pow(x1, 2) S11 = sum(x2, length) - pow(sum(x1, length), 2) / length S12 = sum(x1 * x2, length) - sum(x1, length) * sum(x2, length) / length S22 = sum(pow(x2, 2), length) - pow(sum(x2, length), 2) / length Sy1 = sum(y * x1, length) - sum(y, length) * sum(x1, length) / length Sy2 = sum(y * x2, length) - sum(y, length) * sum(x2, length) / length max1 = sma(x1, length) max2 = sma(x2, length) may = sma(y, length) b2 = (Sy1 * S22 - Sy2 * S12) / (S22 * S11 - pow(S12, 2)) b3 = (Sy2 * S11 - Sy1 * S12) / (S22 * S11 - pow(S12, 2)) b1 = may - b2 * max1 - b3 * max2 Y = b1 + b2 * x1 + b3 * x2 //---- y = 0. e = quadReg(abs(src - nz(y[1])),length) a = quadReg(src - nz(y[1],src),length)/e y := quadReg(src + iff(smo,a*e,0),length) + iff(smo,0,a*e) //---- //col = rising(a,1)? color.blue : falling(a,1) ? color.red : color.white col = a >= tol ? color.red : a <= tol*-1 ? color.green : color.yellow bgcolor(a > 0 ? color.new(color.green,80): a < 0 ? color.new(color.red,80) : color.yellow) plot(a,"Plot",color=col, transp=20, linewidth = 2) hline(tol,color = color.new(color.orange,50),linewidth=1, linestyle = hline.style_dotted) hline(tol*-1,color= color.new(color.orange,50),linewidth=1, linestyle = hline.style_dotted) hline(0,color= color.new(color.orange,50),linewidth=1, linestyle = hline.style_dotted)