Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5
The Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5
Partially Automated Trading Besides Your Day Job
Alerts In Real-Time When Divergences Occur
Installing the Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels 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 Corr Wilder EMA (fl)(vra).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 Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5
The Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5 has 7 parameters to configure.
input int inpPeriod = 14; // Average period input ENUM_APPLIED_PRICE inpPrice = PRICE_CLOSE; // Price input int inpCorrectionPeriod = 0; // "Correction" period (<0 no correction,0 to 1 same as average) input chgColor inpColorOn = chg_onLevel; // Color change on : input int inpFlPeriod = 25; // Period for finding floating levels input double inpFlUp = 90; // Upper level % input double inpFlDown = 10; // Lower level % Buffers of the Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5
The Corrected volatility ratio adaptive double smoothed Wilders EMA with floating levels Indicator For MT5 provides 8 buffers.
SetIndexBuffer(0,fup ,INDICATOR_DATA); SetIndexBuffer(1,fdn ,INDICATOR_DATA); SetIndexBuffer(2,mid ,INDICATOR_DATA); SetIndexBuffer(3,avg ,INDICATOR_DATA); SetIndexBuffer(4,avgc,INDICATOR_COLOR_INDEX); SetIndexBuffer(5,val ,INDICATOR_DATA); SetIndexBuffer(6,valc,INDICATOR_COLOR_INDEX); SetIndexBuffer(7,avgw,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& volume[], const int& spread[]) { static int prev_i=-1; static double prev_max,prev_min; // //--- // int i= prev_calculated-1; if (i lt 0) i=0; for (; i lt rates_total && !_StopFlag; i++) { double _price; _setPrice(inpPrice,_price,i); double _ratio = iVolatilityRatio.calculate(_price,i,rates_total); _alpha = 1.0 /MathSqrt(ª_maPeriod/_ratio); if (i gt 0) { avgw[i] = avgw[i-1] + _alpha*(_price-avgw[i-1]); avg[i] = avg[i-1] + _alpha*(avgw[i]-avg[i-1]); } else avg[i] = avgw[i] = _price; val[i] = iCorrMa(_price,avg[i],ª_corrPeriod,i,rates_total); // // // if (prev_i!=i) { prev_i = i; int start = i-inpFlPeriod+1; if (start lt 0) start=0; prev_max = val[ArrayMaximum(val,start,inpFlPeriod-1)]; prev_min = val[ArrayMinimum(val,start,inpFlPeriod-1)]; } double max = (val[i] gt prev_max) ? val[i] : prev_max; double min = (val[i] lt prev_min) ? val[i] : prev_min; double range = (max-min)/100.0; fup[i] = min+inpFlUp *range; fdn[i] = min+inpFlDown*range; mid[i] = min+ 50.0*range; // //--- // avgc[i] = (avg[i] gt val[i]) ? 1 : (avg[i] lt val[i]) ? 2 : 0; switch (ª_colorOn) { case chg_onOrig : valc[i] = avgc[i]; break; case chg_onLevel : valc[i] = (val[i] gt fup[i]) ? 1 : (val[i] lt fdn[i]) ? 2 : (i gt 0) ? (val[i]==val[i-1]) ? valc[i-1] : 0 : 0; break; case chg_onMiddle : valc[i] = (val[i] gt mid[i]) ? 1 : (val[i] lt mid[i]) ? 2 : (i gt 0) ? (val[i]==val[i-1]) ? valc[i-1] : 0 : 0; break; default : valc[i] = (i gt 0) ? (val[i] gt val[i-1]) ? 1 : (val[i] lt val[i-1]) ? 2 : valc[i-1] : 0; } } return(i); } //------------------------------------------------------------------ // Custom function(s) //------------------------------------------------------------------ // // // class cStdDevVolatilityRatio { private : int m_period; int m_arraySize; struct sStdDevVolatilityRatioStruct { public : double price; double price2; double sum; double sum2; double sumd; double deviation; }; sStdDevVolatilityRatioStruct m_array[]; public: cStdDevVolatilityRatio() : m_arraySize(-1) { } ~cStdDevVolatilityRatio() { ArrayFree(m_array); } // //--- // void init(int period) { m_period = (period gt 1) ? period : 1; } double calculate(double price, int i, int bars) { if (m_arraySize lt bars) { m_arraySize = ArrayResize(m_array,bars+500); if (m_arraySize lt bars) return(0); } m_array[i].price =price; m_array[i].price2=price*price; // //--- // if (i gt m_period) { m_array[i].sum = m_array[i-1].sum +m_array[i].price -m_array[i-m_period].price; m_array[i].sum2 = m_array[i-1].sum2+m_array[i].price2-m_array[i-m_period].price2; } else { m_array[i].sum = m_array[i].price; m_array[i].sum2 = m_array[i].price2; for(int k=1; k lt m_period && i gt =k; k++) { m_array[i].sum += m_array[i-k].price; m_array[i].sum2 += m_array[i-k].price2; } } m_array[i].deviation = (MathSqrt((m_array[i].sum2-m_array[i].sum*m_array[i].sum/(double)m_period)/(double)m_period)); if (i gt m_period) m_array[i].sumd = m_array[i-1].sumd +m_array[i].deviation -m_array[i-m_period].deviation; else { m_array[i].sumd = m_array[i].deviation; for(int k=1; k lt m_period && i gt =k; k++) m_array[i].sumd += m_array[i-k].deviation; } double deviationAverage = m_array[i].sumd/(double)m_period; return(deviationAverage != 0 ? m_array[i].deviation/deviationAverage : 1); } }; cStdDevVolatilityRatio iVolatilityRatio; // //--- // double iCorrMa(double price, double average, int period, int i, int bars, int instance=0) { #define ¤ instance #define _functionInstances 1 struct sCorrMaStruct { double corrected; double price; double price2; double summ; double summ2; }; static sCorrMaStruct m_array[][_functionInstances]; static int m_arraySize=0; if (m_arraySize lt bars) { m_arraySize = ArrayResize(m_array,bars+500); if (m_arraySize lt =bars) return(0); } // //--- // m_array[i][¤].price = price; m_array[i][¤].price2 = price*price; if (i gt period) { m_array[i][¤].summ = m_array[i-1][¤].summ +price -m_array[i-period][¤].price; m_array[i][¤].summ2 = m_array[i-1][¤].summ2+m_array[i][¤].price2-m_array[i-period][¤].price2; } else { m_array[i][¤].summ = m_array[i][¤].price; m_array[i][¤].summ2 = m_array[i][¤].price2; for(int k=1; k lt period && i gt =k; k++) { m_array[i][¤].summ += m_array[i-k][¤].price; m_array[i][¤].summ2 += m_array[i-k][¤].price2; } } // //--- // if (i gt 0) { double v1 = (m_array[i][¤].summ2-m_array[i][¤].summ*m_array[i][¤].summ/(double)period)/(double)period; double v2 = (m_array[i-1][¤].corrected-average)*(m_array[i-1][¤].corrected-average); double c = (v2 lt v1 || v2==0) ? 0 : 1.0-v1/v2; m_array[i][¤].corrected = m_array[i-1][¤].corrected + c*(average-m_array[i-1][¤].corrected); } else m_array[i][¤].corrected = average; return (m_array[i][¤].corrected); // //--- // #undef ¤ #undef _functionInstances } //------------------------------------------------------------------
