Price Data Components
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vwap_bands
ÿþ//------------------------------------------------------------------
#property copyright "© mladen, 2016, MetaQuotes Software Corp."
#property link "www.forex-tsd.com, www.mql5.com"
#property version "1.00"
//------------------------------------------------------------------
#property indicator_chart_window
#property indicator_buffers 8
#property indicator_plots 7
#property indicator_type1 DRAW_LINE
#property indicator_color1 clrLimeGreen
#property indicator_width1 2
#property indicator_type2 DRAW_LINE
#property indicator_color2 clrLimeGreen
#property indicator_type3 DRAW_LINE
#property indicator_color3 clrLimeGreen
#property indicator_style3 STYLE_DOT
#property indicator_type4 DRAW_LINE
#property indicator_color4 clrSilver
#property indicator_style4 STYLE_DOT
#property indicator_type5 DRAW_LINE
#property indicator_color5 clrSandyBrown
#property indicator_style5 STYLE_DOT
#property indicator_type6 DRAW_LINE
#property indicator_color6 clrSandyBrown
#property indicator_type7 DRAW_LINE
#property indicator_color7 clrSandyBrown
#property indicator_width7 2
//
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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
};
input int AvgPeriod = 20; // Volume weighted average period
input enPrices Price = pr_close; // Price
input bool UseRealVolume = false; // Use real volume?
input bool DeviationSample = false; // Deviation with sample correction?
input double DeviationMuliplier1 = 1; // First band(s) deviation
input double DeviationMuliplier2 = 2; // Second band(s) deviation
input double DeviationMuliplier3 = 2.5; // Third band(s) deviation
double bandm[],bandu1[],bandu2[],bandu3[],bandd1[],bandd2[],bandd3[],prices[];
//------------------------------------------------------------------
//
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void OnInit()
{
SetIndexBuffer(0,bandu3 ,INDICATOR_DATA);
SetIndexBuffer(1,bandu2 ,INDICATOR_DATA);
SetIndexBuffer(2,bandu1 ,INDICATOR_DATA);
SetIndexBuffer(3,bandm ,INDICATOR_DATA);
SetIndexBuffer(4,bandd1 ,INDICATOR_DATA);
SetIndexBuffer(5,bandd2 ,INDICATOR_DATA);
SetIndexBuffer(6,bandd3 ,INDICATOR_DATA);
SetIndexBuffer(7,prices ,INDICATOR_CALCULATIONS);
IndicatorSetString(INDICATOR_SHORTNAME,"VWAP bands ("+(string)AvgPeriod+")");
}
//------------------------------------------------------------------
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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& real_volume[],
const int& spread[])
{
if (Bars(_Symbol,_Period)<rates_total) return(-1);
//
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int i=(int)MathMax(prev_calculated-1,0); for (; i<rates_total && !_StopFlag; i++)
{
prices[i] = getPrice(Price,open,close,high,low,i,rates_total);
double sum1=0,sum2=0, deviation = iDeviation(prices[i],AvgPeriod,DeviationSample,i,rates_total);
for (int k=0; k<AvgPeriod && (i-k)>=0; k++)
{
double volume = (UseRealVolume) ? (double)real_volume[i-k] : (double)tick_volume[i-k];
sum1 += volume*prices[i-k];
sum2 += volume;
}
bandm[i] = (sum2!=0) ? sum1/sum2 : prices[i];
bandu1[i] = (DeviationMuliplier1>0) ? bandm[i]+DeviationMuliplier1*deviation : EMPTY_VALUE;
bandd1[i] = (DeviationMuliplier1>0) ? bandm[i]-DeviationMuliplier1*deviation : EMPTY_VALUE;
bandu2[i] = (DeviationMuliplier2>0) ? bandm[i]+DeviationMuliplier2*deviation : EMPTY_VALUE;
bandd2[i] = (DeviationMuliplier2>0) ? bandm[i]-DeviationMuliplier2*deviation : EMPTY_VALUE;
bandu3[i] = (DeviationMuliplier3>0) ? bandm[i]+DeviationMuliplier3*deviation : EMPTY_VALUE;
bandd3[i] = (DeviationMuliplier3>0) ? bandm[i]-DeviationMuliplier3*deviation : EMPTY_VALUE;
}
return(i);
}
//------------------------------------------------------------------
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double workDev[];
double iDeviation(double value, int length, bool isSample, int i, int bars)
{
if (ArraySize(workDev)!=bars) ArrayResize(workDev,bars); workDev[i] = value;
//
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double oldMean = value;
double newMean = value;
double squares = 0; int k;
for (k=1; k<length && (i-k)>=0; k++)
{
newMean = (workDev[i-k]-oldMean)/(k+1)+oldMean;
squares += (workDev[i-k]-oldMean)*(workDev[i-k]-newMean);
oldMean = newMean;
}
return(MathSqrt(squares/MathMax(k-isSample,1)));
}
//------------------------------------------------------------------
//
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#define _pricesInstances 1
#define _pricesSize 4
double workHa[][_pricesInstances*_pricesSize];
double getPrice(int tprice, const double& open[], const double& close[], const double& high[], const double& low[], int i,int _bars, int instanceNo=0)
{
if (tprice>=pr_haclose)
{
if (ArrayRange(workHa,0)!= _bars) ArrayResize(workHa,_bars); instanceNo*=_pricesSize;
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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;
//
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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);
}
}
//
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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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