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Composite_RSI_1_5
//------------------------------------------------------------------
#property copyright "mladen"
#property link "www.forex-tsd.com"
//------------------------------------------------------------------
#property indicator_separate_window
#property indicator_buffers 7
#property indicator_plots 5
#property indicator_label1 "Composite RSI"
#property indicator_type1 DRAW_FILLING
#property indicator_color1 clrDeepSkyBlue,clrSandyBrown
#property indicator_label2 "CompositeRSI level up"
#property indicator_type2 DRAW_LINE
#property indicator_color2 clrDodgerBlue
#property indicator_style2 STYLE_DOT
#property indicator_label3 "Composite RSI middle level"
#property indicator_type3 DRAW_LINE
#property indicator_color3 clrSilver
#property indicator_style3 STYLE_DOT
#property indicator_label4 "Composite RSI level down"
#property indicator_type4 DRAW_LINE
#property indicator_color4 clrSandyBrown
#property indicator_style4 STYLE_DOT
#property indicator_label5 "Composite RSI"
#property indicator_type5 DRAW_COLOR_LINE
#property indicator_color5 clrDeepSkyBlue,clrSandyBrown,clrSilver
#property indicator_style5 STYLE_SOLID
#property indicator_width5 2
//
//
//
//
//
enum enPrices
{
pr_close, // Close
pr_open, // Open
pr_high, // High
pr_low, // Low
pr_median, // Median
pr_typical, // Typical
pr_weighted, // Weighted
pr_average, // Average (high+low+open+close)/4
pr_medianb, // Average median body (open+close)/2
pr_tbiased, // Trend biased price
pr_tbiased2, // Trend biased (extreme) price
pr_haclose, // Heiken ashi close
pr_haopen , // Heiken ashi open
pr_hahigh, // Heiken ashi high
pr_halow, // Heiken ashi low
pr_hamedian, // Heiken ashi median
pr_hatypical, // Heiken ashi typical
pr_haweighted, // Heiken ashi weighted
pr_haaverage, // Heiken ashi average
pr_hamedianb, // Heiken ashi median body
pr_hatbiased, // Heiken ashi trend biased price
pr_hatbiased2 // Heiken ashi trend biased (extreme) price
};
enum enumAveragesType
{
avgSma, // Simple moving average
avgEma, // Exponential moving average
avgSmma, // Smoothed MA
avgLwma // Linear weighted MA
};
input int RsiPeriod = 14; // Rsi calculation period
input int RsiDepth = 10; // Rsi calculation depth
input bool RsiFast = false; // Use "fast" claculation
input enPrices Price = pr_close; // Price to use
input int PriceSmooth = 9; // Price smoothing period
input enumAveragesType PriceSmoothMethod = avgLwma; // Price smoothing method
input int flLookBack = 25; // Floating levels look back period
input double flLevelUp = 90; // Floating levels up level %
input double flLevelDown = 10; // Floating levels down level %
//
//
//
//
//
double rsi[],fillup[],filldn[],levelup[],levelmi[],leveldn[];
double colorBuffer[];
//------------------------------------------------------------------
//
//------------------------------------------------------------------
//
//
//
//
//
int OnInit()
{
SetIndexBuffer(0,fillup, INDICATOR_DATA);
SetIndexBuffer(1,filldn, INDICATOR_DATA);
SetIndexBuffer(2,levelup,INDICATOR_DATA);
SetIndexBuffer(3,levelmi,INDICATOR_DATA);
SetIndexBuffer(4,leveldn,INDICATOR_DATA);
SetIndexBuffer(5,rsi , INDICATOR_DATA);
SetIndexBuffer(6,colorBuffer,INDICATOR_COLOR_INDEX);
IndicatorSetString(INDICATOR_SHORTNAME,"Composite RSI ("+string(RsiPeriod)+","+string(RsiDepth)+","+string(PriceSmooth)+")");
return(0);
}
//------------------------------------------------------------------
//
//------------------------------------------------------------------
//
//
//
//
//
int OnCalculate(const int rates_total,
const int prev_calculated,
const datetime& time[],
const double& open[],
const double& high[],
const double& low[],
const double& close[],
const long& tick_volume[],
const long& volume[],
const int& spread[])
{
//
//
//
//
//
for (int i=(int)MathMax(prev_calculated-1,0); i<rates_total; i++)
{
rsi[i] = iCompRsi(iCustomMa(PriceSmoothMethod,getPrice(Price,open,close,high,low,i,rates_total),PriceSmooth,rates_total,i),RsiPeriod,RsiDepth,RsiFast,rates_total,i,0);
double min = rsi[i];
double max = rsi[i];
for (int k=1; k<flLookBack && i-k>=0; k++)
{
min = MathMin(rsi[i-k],min);
max = MathMax(rsi[i-k],max);
}
double range = max-min;
levelup[i] = min+flLevelUp*range/100.0;
leveldn[i] = min+flLevelDown*range/100.0;
levelmi[i] = min+0.5*range;
fillup[i] = rsi[i];
filldn[i] = MathMin(MathMax(rsi[i],leveldn[i]),levelup[i]);
if (i>0)
{
colorBuffer[i]=2;
if (rsi[i]>levelup[i] || rsi[i]<leveldn[i])
{
if (rsi[i]>rsi[i-1]) colorBuffer[i]=0;
if (rsi[i]<rsi[i-1]) colorBuffer[i]=1;
}
}
}
return(rates_total);
}
//------------------------------------------------------------------
//
//------------------------------------------------------------------
//
//
//
//
//
double workCompRsi[][26];
double iCompRsi(double price, double period, int depth, bool fast, int total, int i, int instanceNo=0)
{
if (ArrayRange(workCompRsi,0) !=total) ArrayResize(workCompRsi,total);
double alpha = 2.0/(1.0 + period);
if (fast) alpha = 2.0/(2.0 + (period-1.0)/2.0);
instanceNo *= 26; depth = (int)MathMin(depth,25);
//
//
//
//
//
double CU = 0;
double CD = 0;
for (int k=0; k<=depth; k++)
{
if (i == 0)
workCompRsi[i][instanceNo+k] = price;
else workCompRsi[i][instanceNo+k] = workCompRsi[i-1][instanceNo+k]+alpha*(price-workCompRsi[i-1][instanceNo+k]);
//
//
//
//
//
price = workCompRsi[i][k+instanceNo];
if (k>0)
if (workCompRsi[i][instanceNo+k-1] >= workCompRsi[i][instanceNo+k])
CU += workCompRsi[i][instanceNo+k-1] - workCompRsi[i][instanceNo+k ];
else CD += workCompRsi[i][instanceNo+k ] - workCompRsi[i][instanceNo+k-1];
}
double trsi = 0; if (CU + CD != 0) trsi = CU / (CU + CD);
return(trsi);
}
//------------------------------------------------------------------
//
//------------------------------------------------------------------
//
//
//
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//
#define _maInstances 2
#define _maWorkBufferx1 1*_maInstances
#define _maWorkBufferx2 2*_maInstances
#define _maWorkBufferx3 3*_maInstances
#define _maWorkBufferx4 4*_maInstances
#define _maWorkBufferx5 5*_maInstances
double iCustomMa(int mode, double price, double length, int bars, int r, int instanceNo=0)
{
switch (mode)
{
case avgSma : return(iSma(price,(int)length,r,bars,instanceNo));
case avgEma : return(iEma(price,length,r,bars,instanceNo));
case avgSmma : return(iSmma(price,(int)length,r,bars,instanceNo));
case avgLwma : return(iLwma(price,(int)length,r,bars,instanceNo));
default : return(price);
}
}
//
//
//
//
//
double workSma[][_maWorkBufferx2];
double iSma(double price, int period, int r, int _bars, int instanceNo=0)
{
if (period<=1) return(price);
if (ArrayRange(workSma,0)!= _bars) ArrayResize(workSma,_bars); instanceNo *= 2; int k;
//
//
//
//
//
workSma[r][instanceNo+0] = price;
workSma[r][instanceNo+1] = price; for(k=1; k<period && (r-k)>=0; k++) workSma[r][instanceNo+1] += workSma[r-k][instanceNo+0];
workSma[r][instanceNo+1] /= 1.0*k;
return(workSma[r][instanceNo+1]);
}
//
//
//
//
//
double workEma[][_maWorkBufferx1];
double iEma(double price, double period, int r, int _bars, int instanceNo=0)
{
if (period<=1) return(price);
if (ArrayRange(workEma,0)!= _bars) ArrayResize(workEma,_bars);
//
//
//
//
//
workEma[r][instanceNo] = price;
double alpha = 2.0 / (1.0+period);
if (r>0)
workEma[r][instanceNo] = workEma[r-1][instanceNo]+alpha*(price-workEma[r-1][instanceNo]);
return(workEma[r][instanceNo]);
}
//
//
//
//
//
double workSmma[][_maWorkBufferx1];
double iSmma(double price, double period, int r, int _bars, int instanceNo=0)
{
if (period<=1) return(price);
if (ArrayRange(workSmma,0)!= _bars) ArrayResize(workSmma,_bars);
//
//
//
//
//
if (r<period)
workSmma[r][instanceNo] = price;
else workSmma[r][instanceNo] = workSmma[r-1][instanceNo]+(price-workSmma[r-1][instanceNo])/period;
return(workSmma[r][instanceNo]);
}
//
//
//
//
//
double workLwma[][_maWorkBufferx1];
double iLwma(double price, double period, int r, int _bars, int instanceNo=0)
{
if (period<=1) return(price);
if (ArrayRange(workLwma,0)!= _bars) ArrayResize(workLwma,_bars);
//
//
//
//
//
workLwma[r][instanceNo] = price;
double sumw = period;
double sum = period*price;
for(int k=1; k<period && (r-k)>=0; k++)
{
double weight = period-k;
sumw += weight;
sum += weight*workLwma[r-k][instanceNo];
}
return(sum/sumw);
}
//------------------------------------------------------------------
//
//------------------------------------------------------------------
//
//
//
//
//
//
double workHa[][4];
double getPrice(int tprice, const double& open[], const double& close[], const double& high[], const double& low[], int i, int _tbars, int instanceNo=0)
{
if (tprice>=pr_haclose)
{
if (ArrayRange(workHa,0)!= _tbars) ArrayResize(workHa,_tbars); instanceNo*=4;
//
//
//
//
//
double haOpen;
if (i>0)
haOpen = (workHa[i-1][instanceNo+2] + workHa[i-1][instanceNo+3])/2.0;
else haOpen = (open[i]+close[i])/2;
double haClose = (open[i] + high[i] + low[i] + close[i]) / 4.0;
double haHigh = MathMax(high[i], MathMax(haOpen,haClose));
double haLow = MathMin(low[i] , MathMin(haOpen,haClose));
if(haOpen <haClose) { workHa[i][instanceNo+0] = haLow; workHa[i][instanceNo+1] = haHigh; }
else { workHa[i][instanceNo+0] = haHigh; workHa[i][instanceNo+1] = haLow; }
workHa[i][instanceNo+2] = haOpen;
workHa[i][instanceNo+3] = haClose;
//
//
//
//
//
switch (tprice)
{
case pr_haclose: return(haClose);
case pr_haopen: return(haOpen);
case pr_hahigh: return(haHigh);
case pr_halow: return(haLow);
case pr_hamedian: return((haHigh+haLow)/2.0);
case pr_hamedianb: return((haOpen+haClose)/2.0);
case pr_hatypical: return((haHigh+haLow+haClose)/3.0);
case pr_haweighted: return((haHigh+haLow+haClose+haClose)/4.0);
case pr_haaverage: return((haHigh+haLow+haClose+haOpen)/4.0);
case pr_hatbiased:
if (haClose>haOpen)
return((haHigh+haClose)/2.0);
else return((haLow+haClose)/2.0);
case pr_hatbiased2:
if (haClose>haOpen) return(haHigh);
if (haClose<haOpen) return(haLow);
return(haClose);
}
}
//
//
//
//
//
switch (tprice)
{
case pr_close: return(close[i]);
case pr_open: return(open[i]);
case pr_high: return(high[i]);
case pr_low: return(low[i]);
case pr_median: return((high[i]+low[i])/2.0);
case pr_medianb: return((open[i]+close[i])/2.0);
case pr_typical: return((high[i]+low[i]+close[i])/3.0);
case pr_weighted: return((high[i]+low[i]+close[i]+close[i])/4.0);
case pr_average: return((high[i]+low[i]+close[i]+open[i])/4.0);
case pr_tbiased:
if (close[i]>open[i])
return((high[i]+close[i])/2.0);
else return((low[i]+close[i])/2.0);
case pr_tbiased2:
if (close[i]>open[i]) return(high[i]);
if (close[i]<open[i]) return(low[i]);
return(close[i]);
}
return(0);
}
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