Developing Gauss indicator
- This topic has 16 replies, 3 voices, and was last updated 2 years ago by
.
-
All,
12345678<span class="Y2IQFc" lang="en">I have modified the "Quino Statistics Plotter" indicator created last August,to map the theoretical Gaussian curve to a distribution of "Close" on a defined number of bars.This allows to have an idea if this distribution (Price) has the contours of a Gaussian curve<a class="gdbbx-bbcode-attachment" target="_blank" title="Quino-Statistics-Plotter-V3" href="https://a2a3f5h6.rocketcdn.me/wp-content/uploads/2021/12/Quino-Statistics-Plotter-V3.itf">Quino-Statistics-Plotter-V3</a>.See the old version in the indicator library for more information on the other functionalities.</span>// Quino Statistics Plotter
// By Quino
// version of 05/12/2021
//===================================================================================
// NbrOfSamples : Number of consecutive close
// NbrOfClasses : Number of intervals of values in which we store the values of “close”
// InformationDisplay :
// – false : display of the histogram only
// – true : display of limit values for each class and % of occurrence
// ClassTracer :
// – false : indicator that can be used stand-alone (curve and information)
// – true : indicator usable in the price indicator. By locating the class of the last “close” or another class. Class boundaries are represented by two horizontal lines on the price chart.
// ClassIndex : manual search for the class number corresponding to the last “close” or another class. Alignment of the cue point under the value of the last close (in red)
// GaussianShape
// – false : No Gaussian curve drawn
// – true : Gaussian curve drawn from avrerage and standard deviation of the selected number of consecutive close//Typical use : NbrOfSamples=150 ; NbrOfClasses=30 (5 samples per class minimum)
//===================================================================================
NbrMaxFrequency=1000 // Number max of occurency per class
AdjustA=30 // Scale calibration
AdjustB=4 // Position calibration
//———————————-
if islastbarupdate then
for k =0 to NbrOfSamples-1 do
$v[k]=close[k]
next
for i= NbrOfSamples-1 downto 0 do
$d[i]=arraymax($v)
for j=NbrOfSamples-1 downto 0 do
if $v[j]=$d[i] then
$v[j]=0
break
endif
next
next
Bin=(arraymax($d)-arraymin($d))/(NbrOfClasses)
For i=0 to NbrOfClasses do
$r[i]=0
next
BinA=arraymin($d)
for j=0 to NbrOfClasses-1 do
Dtemp=0
for i=0 to NbrOfSamples-1 do
if j < NbrOfClasses then
if $d[i]>=BinA+ j*Bin and $d[i] <BinA+(j+1)*Bin then
Dtemp=Dtemp+1
else
if $d[i]>=BinA+ j*Bin and $d[i] =<BinA+(j+1)*Bin then
Dtemp=Dtemp+1
endif
endif
endif
next
$r[j]=Dtemp
next
Vmoy=average[NbrOfSamples](close)
Vect=std[NbrOfSamples](close)
for k =0 to NbrOfClasses-1 do
$Vg[k]=((exp(-0.5*square(((BinA+ k*Bin)-Vmoy)/Vect)))/Vect*sqr(6.18))
next
if GaussianShape Then
Scale=max(arraymax($r),arraymax($Vg))+12
else
Scale=arraymax($r)+12
endif
If scale < AdjustA then
CorrecYY=1
CorrecY=1
endif
For i=1 to (NbrMaxFrequency/AdjustA) do
if scale>=i*AdjustA and scale<(i+1)*AdjustA then
CorrecYY=i+1
CorrecY=(i+1)*AdjustA/AdjustB
endif
next
for i= 0 to NbrOfClasses-1 do
if ClassTracer then
ValCaseMax=(BinA+ClassIndex*Bin)
ValCaseMin=(BinA+(ClassIndex-1)*Bin)
drawsegment(barindex[NbrOfSamples-1-i],ValCaseMax,barindex[NbrOfClasses-i-1],ValCaseMax)coloured (51,153,255)
drawsegment(barindex[NbrOfSamples-1-i],ValCaseMin,barindex[NbrOfClasses-i-1],ValCaseMin)coloured (0,51,153)
if i=ClassIndex then
tag=1
else
tag=undefined
endif
else
drawsegment(barindex[NbrOfClasses-i],$r[i],barindex[NbrOfClasses-i],0)coloured (0,0,0)
drawsegment(barindex[NbrOfClasses-i],$r[i],barindex[NbrOfClasses-i+1],$r[i])coloured (0,0,0)
drawsegment(barindex[NbrOfClasses-i+1],0,barindex[NbrOfClasses-i+1],$r[i]) coloured (0,0,0)
drawpoint(barindex[NbrOfClasses-ClassIndex+1],tag)coloured (0,0,50)
if GaussianShape then
drawsegment(barindex[NbrOfClasses-i+1],$Vg[i],barindex[NbrOfClasses-i],$Vg[i+1])coloured (255,0,0)
endif
if InformationDisplay then
for i= 0 to NbrOfClasses-1 do
temp=round(($r[i]/(NbrOfSamples))*10000)/100
temp1=round((BinA+(i)*Bin),2)
temp2=round((BinA+(i+1)*Bin),2)
drawtext(“%= #temp#”,barindex[NbrOfClasses-i],Scale+CorrecY-2*CorrecYY)coloured (0,0,255)
if close >= temp1 and close < temp2 then
drawtext(“#temp1#”,barindex[NbrOfClasses-i],Scale+CorrecY-6*CorrecYY)coloured (255,0,0)
drawtext(“#temp2#”,barindex[NbrOfClasses-i],Scale+CorrecY-4*CorrecYY)coloured (255,0,0)
else
drawtext(“#temp1#”,barindex[NbrOfClasses-i],Scale+CorrecY-6*CorrecYY)coloured (0,0,0)
drawtext(“#temp2#”,barindex[NbrOfClasses-i],Scale+CorrecY-4*CorrecYY)coloured (0,0,0)
endif
next
drawtext(“Average= #Vmoy#”,barindex-4,Scale-8*CorrecYY)coloured (0,0,0)
drawtext(“STD= #Vect#”,barindex-4,Scale-10*CorrecYY)coloured (0,0,0)
endif
endif
next
endif
if GaussianShape Then
Scale=max(arraymax($r),arraymax($Vg))+12+CorrecY
else
Scale=arraymax($r)+12+CorrecY
endif
if not ClassTracer then
zero=0
else
zero=undefined
Scale=undefined
endif
return Scale as “Vertical Reference”,zero as “Zero”123<span class="Y2IQFc" lang="en"><a class="gdbbx-bbcode-attachment" target="_blank" title="Quino-Statistics-Plotter-V3" href="https://a2a3f5h6.rocketcdn.me/wp-content/uploads/2021/12/Quino-Statistics-Plotter-V3.itf">Quino-Statistics-Plotter-V3</a></span>1 user thanked author for this post.
Hi JS,
Maybe it’s possible to do it.
It calls a new developement. Not easy to do it.
If I undersand your need, I suggest to use the Bollinger Bands indicator that perform a price analysis from the mean and the SD.
This indicator don’t care if the price curve is a Gausssian distribution or not.
As it is popular in the trading world, il has some interesting properties.1 user thanked author for this post.
123456789a=(high+low)/2aa=Average[24](a)b=STD[10](a)cl=closey1=a+1/(b*SQRT(44/7))*exp(-1*(SQUARE((cl[n]-aa)))/2*square(b))y2=a-1/(b*SQRT(44/7))*exp(-1*(SQUARE((cl[n]-aa)))/2*square(b))return y1, y21 user thanked author for this post.
Find exclusive trading pro-tools on 
