-wmmm-GaussianRainbow
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This script functions as a sophisticated visual tool designed to smooth out market price movements, making it easier for traders to identify underlying trends by filtering out "market noise."
Core Logic and Methodology
The indicator utilizes a multi-layered mathematical approach known as a Gaussian Filter. In plain terms, rather than just taking a simple average of past prices (which can often be "jittery" and react too quickly to minor fluctuations), this script applies several successive layers of smoothing.
1. The Layered Smoothing Process The logic operates like a series of sieves. The raw market price is passed through the first filter, and the result of that calculation is then fed into a second filter, which is then fed into a third, and so on, until it reaches eight different layers.
- By stacking these calculations, the script progressively removes short-term "noise" while attempting to preserve the long-term direction of the price.
- This creates a much smoother, more organic-looking line that represents the "true" momentum of the asset.
2. Dynamic Customization The behavior of the script is governed by two primary settings:
- Rainbow Period: This determines the fundamental cycle of the smoothing. It affects how the indicator perceives time and frequency within the data.
- Gaussian Order: This dictates the mathematical complexity of each individual filter layer. A higher order allows for a more refined and specialized curve, determining how many past data points influence the current calculation.
3. Visual Representation To make the data easy to interpret, the script generates eight distinct output lines. These lines represent the results of the various smoothing stages. Because these lines are plotted simultaneously, they create a "rainbow" effect on your chart. This allows a trader to visually perceive the difference between immediate price reactions and the broader, more stable trend.
Summary for the User
Instead of looking at a jagged, erratic price line, this script provides a smoothed "flow." It essentially tells the story of where the price is heading by stripping away the distractions of minute-by-minute volatility. It is designed for traders who prefer to see the "big picture" and want a visual representation of momentum that feels fluid and consistent.
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-wmmm-GaussianRainbow
//+------------------------------------------------------------------+
//| GaussianRainbow.mq4 |
//| when-money-makes-money.com |
//| when-money-makes-money.com |
//+------------------------------------------------------------------+
#property copyright "when-money-makes-money.com"
#property link "when-money-makes-money.com"
#property indicator_chart_window
#property indicator_buffers 8
#property indicator_color1 PowderBlue
#property indicator_color2 LightSkyBlue
#property indicator_color3 DeepSkyBlue
#property indicator_color4 Blue
#property indicator_color5 SlateBlue
#property indicator_color6 IndianRed
#property indicator_color7 Salmon
#property indicator_color8 Red
//---- buffers
double rb1[];
double rb2[];
double rb3[];
double rb4[];
double rb5[];
double rb6[];
double rb7[];
double rb8[];
//+------------------------------------------------------------------+
//| Custom indicator initialization function |
//+------------------------------------------------------------------+
extern int RainbowPeriod=10;
extern int GaussianOrder=3;
double pi = 3.1415926535, w, alfa, beta;
color lc[]={Yellow,Gold,Orange,DarkOrange,OrangeRed,Red,OrangeRed,DarkOrange,Orange,Gold};
int init()
{
ObjectCreate("logo",OBJ_LABEL,0,0,0);
ObjectSetText("logo","when-money-makes-money.com",20);
ObjectSet("logo",OBJPROP_XDISTANCE,0);
ObjectSet("logo",OBJPROP_YDISTANCE,30);
w = 2*pi/RainbowPeriod;
beta = (1 - MathCos(w))/(MathPow(1.414,2.0/GaussianOrder) - 1);
alfa = -beta + MathSqrt(beta*beta + 2*beta);
//---- indicators
SetIndexStyle(0,DRAW_LINE);
SetIndexBuffer(0,rb1);
SetIndexStyle(1,DRAW_LINE);
SetIndexBuffer(1,rb2);
SetIndexStyle(2,DRAW_LINE);
SetIndexBuffer(2,rb3);
SetIndexStyle(3,DRAW_LINE);
SetIndexBuffer(3,rb4);
SetIndexStyle(4,DRAW_LINE);
SetIndexBuffer(4,rb5);
SetIndexStyle(5,DRAW_LINE);
SetIndexBuffer(5,rb6);
SetIndexStyle(6,DRAW_LINE);
SetIndexBuffer(6,rb7);
SetIndexStyle(7,DRAW_LINE);
SetIndexBuffer(7,rb8);
//----
return(0);
}
//+------------------------------------------------------------------+
//| Custom indicator deinitialization function |
//+------------------------------------------------------------------+
int deinit()
{
//----
ObjectDelete("logo");
//----
return(0);
}
//+------------------------------------------------------------------+
//| Custom indicator iteration function |
//+------------------------------------------------------------------+
int start()
{
static int currc=0;
ObjectSet("logo",OBJPROP_COLOR,lc[currc]);
currc++;
if(currc>=ArraySize(lc))currc=0;
int counted_bars=IndicatorCounted();
//----
int i=0;
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb1[i] = alfa*Close[i] + (1-alfa)*rb1[i+1];
break;
}
case 2:{
rb1[i] = MathPow(alfa,2)*Close[i] + 2*(1-alfa)*rb1[i+1] - MathPow(1-alfa,2)*rb1[i+2];
break;
}
case 3:{
rb1[i] = MathPow(alfa,3)*Close[i] + 3*(1-alfa)*rb1[i+1] - 3*MathPow(1-alfa,2)*rb1[i+2] + MathPow(1-alfa,3)*rb1[i+3];
break;
}
case 4:{
rb1[i] = MathPow(alfa,4)*Close[i] + 4*(1-alfa)*rb1[i+1] - 6*MathPow(1-alfa,2)*rb1[i+2] + 4*MathPow(1-alfa,3)*rb1[i+3] - MathPow(1-alfa,4)*rb1[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb2[i] = alfa*rb1[i] + (1-alfa)*rb2[i+1];
break;
}
case 2:{
rb2[i] = MathPow(alfa,2)*rb1[i] + 2*(1-alfa)*rb2[i+1] - MathPow(1-alfa,2)*rb2[i+2];
break;
}
case 3:{
rb2[i] = MathPow(alfa,3)*rb1[i] + 3*(1-alfa)*rb2[i+1] - 3*MathPow(1-alfa,2)*rb2[i+2] + MathPow(1-alfa,3)*rb2[i+3];
break;
}
case 4:{
rb2[i] = MathPow(alfa,4)*rb1[i] + 4*(1-alfa)*rb2[i+1] - 6*MathPow(1-alfa,2)*rb2[i+2] + 4*MathPow(1-alfa,3)*rb2[i+3] - MathPow(1-alfa,4)*rb2[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb3[i] = alfa*rb2[i] + (1-alfa)*rb3[i+1];
break;
}
case 2:{
rb3[i] = MathPow(alfa,2)*rb2[i] + 2*(1-alfa)*rb3[i+1] - MathPow(1-alfa,2)*rb3[i+2];
break;
}
case 3:{
rb3[i] = MathPow(alfa,3)*rb2[i] + 3*(1-alfa)*rb3[i+1] - 3*MathPow(1-alfa,2)*rb3[i+2] + MathPow(1-alfa,3)*rb3[i+3];
break;
}
case 4:{
rb3[i] = MathPow(alfa,4)*rb2[i] + 4*(1-alfa)*rb3[i+1] - 6*MathPow(1-alfa,2)*rb3[i+2] + 4*MathPow(1-alfa,3)*rb3[i+3] - MathPow(1-alfa,4)*rb3[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb4[i] = alfa*rb3[i] + (1-alfa)*rb4[i+1];
break;
}
case 2:{
rb4[i] = MathPow(alfa,2)*rb3[i] + 2*(1-alfa)*rb4[i+1] - MathPow(1-alfa,2)*rb4[i+2];
break;
}
case 3:{
rb4[i] = MathPow(alfa,3)*rb3[i] + 3*(1-alfa)*rb4[i+1] - 3*MathPow(1-alfa,2)*rb4[i+2] + MathPow(1-alfa,3)*rb4[i+3];
break;
}
case 4:{
rb4[i] = MathPow(alfa,4)*rb3[i] + 4*(1-alfa)*rb4[i+1] - 6*MathPow(1-alfa,2)*rb4[i+2] + 4*MathPow(1-alfa,3)*rb4[i+3] - MathPow(1-alfa,4)*rb4[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb5[i] = alfa*rb4[i] + (1-alfa)*rb5[i+1];
break;
}
case 2:{
rb5[i] = MathPow(alfa,2)*rb4[i] + 2*(1-alfa)*rb5[i+1] - MathPow(1-alfa,2)*rb5[i+2];
break;
}
case 3:{
rb5[i] = MathPow(alfa,3)*rb4[i] + 3*(1-alfa)*rb5[i+1] - 3*MathPow(1-alfa,2)*rb5[i+2] + MathPow(1-alfa,3)*rb5[i+3];
break;
}
case 4:{
rb5[i] = MathPow(alfa,4)*rb4[i] + 4*(1-alfa)*rb5[i+1] - 6*MathPow(1-alfa,2)*rb5[i+2] + 4*MathPow(1-alfa,3)*rb5[i+3] - MathPow(1-alfa,4)*rb5[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb6[i] = alfa*rb5[i] + (1-alfa)*rb6[i+1];
break;
}
case 2:{
rb6[i] = MathPow(alfa,2)*rb5[i] + 2*(1-alfa)*rb6[i+1] - MathPow(1-alfa,2)*rb6[i+2];
break;
}
case 3:{
rb6[i] = MathPow(alfa,3)*rb5[i] + 3*(1-alfa)*rb6[i+1] - 3*MathPow(1-alfa,2)*rb6[i+2] + MathPow(1-alfa,3)*rb6[i+3];
break;
}
case 4:{
rb6[i] = MathPow(alfa,4)*rb5[i] + 4*(1-alfa)*rb6[i+1] - 6*MathPow(1-alfa,2)*rb6[i+2] + 4*MathPow(1-alfa,3)*rb6[i+3] - MathPow(1-alfa,4)*rb6[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb7[i] = alfa*rb6[i] + (1-alfa)*rb7[i+1];
break;
}
case 2:{
rb7[i] = MathPow(alfa,2)*rb6[i] + 2*(1-alfa)*rb7[i+1] - MathPow(1-alfa,2)*rb7[i+2];
break;
}
case 3:{
rb7[i] = MathPow(alfa,3)*rb6[i] + 3*(1-alfa)*rb7[i+1] - 3*MathPow(1-alfa,2)*rb7[i+2] + MathPow(1-alfa,3)*rb7[i+3];
break;
}
case 4:{
rb7[i] = MathPow(alfa,4)*rb6[i] + 4*(1-alfa)*rb7[i+1] - 6*MathPow(1-alfa,2)*rb7[i+2] + 4*MathPow(1-alfa,3)*rb7[i+3] - MathPow(1-alfa,4)*rb7[i+4];
break;
}
}
}
for(i=Bars-counted_bars-1;i>=0;i--){
switch(GaussianOrder){
case 1:{
rb8[i] = alfa*rb7[i] + (1-alfa)*rb8[i+1];
break;
}
case 2:{
rb8[i] = MathPow(alfa,2)*rb7[i] + 2*(1-alfa)*rb8[i+1] - MathPow(1-alfa,2)*rb8[i+2];
break;
}
case 3:{
rb8[i] = MathPow(alfa,3)*rb7[i] + 3*(1-alfa)*rb8[i+1] - 3*MathPow(1-alfa,2)*rb8[i+2] + MathPow(1-alfa,3)*rb8[i+3];
break;
}
case 4:{
rb8[i] = MathPow(alfa,4)*rb7[i] + 4*(1-alfa)*rb8[i+1] - 6*MathPow(1-alfa,2)*rb8[i+2] + 4*MathPow(1-alfa,3)*rb8[i+3] - MathPow(1-alfa,4)*rb8[i+4];
break;
}
}
}
//----
return(0);
}
//+------------------------------------------------------------------+
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