new indicator: GaussTrendChannels

• 02/25/2025 at 2:37 PM #244343
  micha2012

  Dear All,

  today i would like to presend an interesting indicator, which I use frequently for Furures (5min.,1min.) gaining good result.

  AS alqways, my coding skills are basic..I could not solve last 3x lines for PLOt / DRAWLINE..

  {{

  DEFPARAM CalculateonLastBars = 500

  Length = 200 // Standardlänge

  // Gaussian Kernel Berechnung ohne Funktion
  currentWeight = 0
  cumulativeWeight = 0
  FOR i = 0 TO Length – 1 DO
  weight = EXP(- (i * i) / (2 * ((Length / 3) * (Length / 3))))
  currentWeight = currentWeight + close[i] * weight
  cumulativeWeight = cumulativeWeight + weight
  NEXT
  Ghat = currentWeight / cumulativeWeight

  // Rolling Standard Deviation Berechnung ohne Funktion
  sumVal = 0
  sumSq = 0
  FOR i = 0 TO Length – 1 DO
  sumVal = sumVal + close[i]
  sumSq = sumSq + (close[i] * close[i])
  NEXT
  mean = sumVal / Length
  variance = (sumSq / Length) – (mean * mean)
  Deviation = SQRT(MAX(variance, 0))

  // Berechnungen
  Upper = Ghat + Deviation
  Lower = Ghat – Deviation

  // Plots (Linien)
  DRAWHLINE(Upper, RGB(0, 120, 255)) // Zeichnet die Linie für Upper
  DRAWHLINE(Lower, RGB(0, 120, 255)) // Zeichnet die Linie für Lower
  DRAWHLINE(Ghat, RGB(0, 255, 0)) // Zeichnet die Linie für Ghat

  RETURN}}

  Please, could you support me in solving graphical problems?

  Below, please find a screenshot on trading ideas with this indicator.

  (5min. channel= blue, yellow / 1min. channel=pink, green) / 1h channel= orange dotted line)

  Thank you very much.

  Regards to all!

  

  micha2012

  Participant

  Topics: 13

  Replies: 21

  Been thanked: 6 times
  02/25/2025 at 9:37 PM #244359
  JS

  Here is the adjusted indicator:

  Gaussische Kernel

  DEFPARAM CalculateonLastBars = 500 Length = 200 // Standardlänge // Gaussian Kernel Berechnung ohne Funktion CurrentWeight = 0 CumulativeWeight = 0 FOR i = 0 TO Length - 1 DO Weight = EXP(- (i * i) / (2 * ((Length / 3) * (Length / 3)))) currentWeight = currentWeight + close[i] * weight cumulativeWeight = cumulativeWeight + weight NEXT Ghat = currentWeight / cumulativeWeight // Rolling Standard Deviation Berechnung ohne Funktion sumVal = 0 sumSq = 0 FOR i = 0 TO Length - 1 DO sumVal = sumVal + close[i] sumSq = sumSq + (close[i] * close[i]) NEXT mean = sumVal / Length variance = (sumSq / Length) - (mean * mean) Deviation = SQRT(MAX(variance, 0)) // Berechnungen Upper = Ghat + Deviation Lower = Ghat - Deviation RETURN Ghat as "Ghat" Coloured(0,255,0), Upper as "Upper" Coloured(0,120,255),Lower as "Lower" Coloured(0,120,255)

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  DEFPARAM CalculateonLastBars = 500   Length = 200 // Standardlänge   // Gaussian Kernel Berechnung ohne Funktion CurrentWeight = 0 CumulativeWeight = 0   FOR i = 0 TO Length - 1 DO Weight = EXP(- (i * i) / (2 * ((Length / 3) * (Length / 3)))) currentWeight = currentWeight + close[i] * weight cumulativeWeight = cumulativeWeight + weight NEXT Ghat = currentWeight / cumulativeWeight   // Rolling Standard Deviation Berechnung ohne Funktion sumVal = 0 sumSq = 0 FOR i = 0 TO Length - 1 DO sumVal = sumVal + close[i] sumSq = sumSq + (close[i] * close[i]) NEXT mean = sumVal / Length variance = (sumSq / Length) - (mean * mean) Deviation = SQRT(MAX(variance, 0))   // Berechnungen Upper = Ghat + Deviation Lower = Ghat - Deviation   RETURN Ghat as "Ghat" Coloured(0,255,0), Upper as "Upper" Coloured(0,120,255),Lower as "Lower" Coloured(0,120,255)

  3 users thanked author for this post.

  robertogozzi, micha2012, Iván

  

  JS

  Participant

  Topics: 27

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  Been thanked: 1004 times
  02/27/2025 at 4:11 PM #244417
  micha2012

  @JS

  Hello JS,

  thank you very much – merci beaucoup – bedankt.

  Great job and support from you…works perfect!

  One questions: is it possible to display (and code) 5min- channel displayed in 1min- period???

  All the best.

  Thanx

  Micha

  1 user thanked author for this post.

  JS

  

  micha2012

  Participant

  Topics: 13

  Replies: 21

  Been thanked: 6 times
  02/27/2025 at 4:43 PM #244423
  JS

  When you use this indicator, based on a 5-minute timeframe, you can display it in a graph with a 1-minute timeframe…

  Gaussian Kernel TF5min

  DEFPARAM CalculateonLastBars = 500 TimeFrame(5 minutes,UpdateOnClose) Length = 200 // Standard Period // Gaussian Kernel Calculation CurrentWeight = 0 CumulativeWeight = 0 FOR i = 0 TO Length - 1 DO Weight = EXP(- (i * i) / (2 * ((Length / 3) * (Length / 3)))) currentWeight = currentWeight + close[i] * weight cumulativeWeight = cumulativeWeight + weight NEXT Ghat = currentWeight / cumulativeWeight // Rolling Standard Deviation Calculation sumVal = 0 sumSq = 0 FOR i = 0 TO Length - 1 DO sumVal = sumVal + close[i] sumSq = sumSq + (close[i] * close[i]) NEXT mean = sumVal / Length variance = (sumSq / Length) - (mean * mean) Deviation = SQRT(MAX(variance, 0)) // Band Calculations Upper = Ghat + Deviation Lower = Ghat - Deviation TimeFrame(Default) //Plotting RETURN Ghat as "Ghat" Coloured(0,255,0), Upper as "Upper" Coloured(0,120,255),Lower as "Lower" Coloured(0,120,255)

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  DEFPARAM CalculateonLastBars = 500   TimeFrame(5 minutes,UpdateOnClose) Length = 200 // Standard Period   // Gaussian Kernel Calculation CurrentWeight = 0 CumulativeWeight = 0   FOR i = 0 TO Length - 1 DO Weight = EXP(- (i * i) / (2 * ((Length / 3) * (Length / 3)))) currentWeight = currentWeight + close[i] * weight cumulativeWeight = cumulativeWeight + weight NEXT Ghat = currentWeight / cumulativeWeight   // Rolling Standard Deviation Calculation sumVal = 0 sumSq = 0 FOR i = 0 TO Length - 1 DO sumVal = sumVal + close[i] sumSq = sumSq + (close[i] * close[i]) NEXT mean = sumVal / Length variance = (sumSq / Length) - (mean * mean) Deviation = SQRT(MAX(variance, 0))   // Band Calculations Upper = Ghat + Deviation Lower = Ghat - Deviation   TimeFrame(Default)   //Plotting RETURN Ghat as "Ghat" Coloured(0,255,0), Upper as "Upper" Coloured(0,120,255),Lower as "Lower" Coloured(0,120,255)

  1 user thanked author for this post.

  micha2012

  

  JS

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  Been thanked: 1004 times
  02/27/2025 at 5:18 PM #244428
  micha2012

  Hello JS,

  wow..you are the best..great!

  You saved me a lot of coding (“try and error”).. 🙂

  Thank you once again for your fast support and coding.

  Bedankt!

  Thanx,

  Micha

  1 user thanked author for this post.

  JS

  

  micha2012

  Participant

  Topics: 13

  Replies: 21

  Been thanked: 6 times
  02/27/2025 at 5:37 PM #244431
  JS

  Thanks, Micha! Hope it works out for you…

  

  JS

  Participant

  Topics: 27

  Replies: 1923

  Been thanked: 1004 times
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