VWAP bands Indicator For MT5
Table Of Contents:
- VWAP bands Indicator For MT5
- Installing the VWAP bands Indicator For MT5
- Parameters of the VWAP bands Indicator For MT5
- Buffers of the VWAP bands Indicator For MT5
- Main Parts Of The Code
The VWAP bands Indicator For MT5 is similar to the bollinger bands indicator but instead of the EMA as the middle line the VWAP bands uses the volume weighted moving average. This approach with the volume can produce some leading information which you would not get by simply looking at the price. You can trade the strong moving zones and the squeezes as with the original bollinger bands indicator.
Partially Automated Trading Besides Your Day Job
Alerts In Real-Time When Divergences Occur
Installing the VWAP bands Indicator For MT5
After you downloaded the indicator via the form above you need to unzip the zip-file. Then you need to copy the file vwap_bands.mq5 into the folder MQL5\Indicators of your MT5 installation. After that please restart MT5 and then you will be able to see the indicator in the list of indicators.
Parameters of the VWAP bands Indicator For MT5
The VWAP bands Indicator For MT5 has 7 parameters to configure.
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 Buffers of the VWAP bands Indicator For MT5
The VWAP bands Indicator For MT5 provides 8 buffers.
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); Main Parts Of The Code
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) lt rates_total) return(-1); // // // // // int i=(int)MathMax(prev_calculated-1,0); for (; i lt 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 lt AvgPeriod && (i-k) gt =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 gt 0) ? bandm[i]+DeviationMuliplier1*deviation : EMPTY_VALUE; bandd1[i] = (DeviationMuliplier1 gt 0) ? bandm[i]-DeviationMuliplier1*deviation : EMPTY_VALUE; bandu2[i] = (DeviationMuliplier2 gt 0) ? bandm[i]+DeviationMuliplier2*deviation : EMPTY_VALUE; bandd2[i] = (DeviationMuliplier2 gt 0) ? bandm[i]-DeviationMuliplier2*deviation : EMPTY_VALUE; bandu3[i] = (DeviationMuliplier3 gt 0) ? bandm[i]+DeviationMuliplier3*deviation : EMPTY_VALUE; bandd3[i] = (DeviationMuliplier3 gt 0) ? bandm[i]-DeviationMuliplier3*deviation : EMPTY_VALUE; } return(i); } //------------------------------------------------------------------ // //------------------------------------------------------------------ // // // // // double workDev[]; double iDeviation(double value, int length, bool isSample, int i, int bars) { if (ArraySize(workDev)!=bars) ArrayResize(workDev,bars); workDev[i] = value; // // // // // double oldMean = value; double newMean = value; double squares = 0; int k; for (k=1; k lt length && (i-k) gt =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))); } //------------------------------------------------------------------ // //------------------------------------------------------------------ // // // // // // #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 gt =pr_haclose) { if (ArrayRange(workHa,0)!= _bars) ArrayResize(workHa,_bars); instanceNo*=_pricesSize; // // // // // double haOpen; if (i gt 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 lt 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 gt haOpen) return((haHigh+haClose)/2.0); else return((haLow+haClose)/2.0); case pr_hatbiased2: if (haClose gt haOpen) return(haHigh); if (haClose lt 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] gt open[i]) return((high[i]+close[i])/2.0); else return((low[i]+close[i])/2.0); case pr_tbiased2: if (close[i] gt open[i]) return(high[i]); if (close[i] lt open[i]) return(low[i]); return(close[i]); } return(0); }
