多种均线方法

日期：2018-2-7 天泓评测 函数 浏览：1820次 评论：0条 



// MA_Method=0: SMA - Simple Moving Average

double SMA(int price,int per,int bar)

{

   double Sum = 0;

   for(int i = 0;i < per;i++) Sum += iMA(NULL,0,1,0,0,price,bar+i);

   

   return(Sum/per);

}



double SMAOnArray(double& array[],int per,int bar)

{

   double Sum = 0;

   for(int i = 0;i < per;i++) Sum += array[bar+i];

   

   return(Sum/per);

}

                           

// MA_Method=1: EMA - Exponential Moving Average

double EMA(int price,double prev,int per,int bar)

{

   if(bar >= Bars - 2) double ema = iMA(NULL,0,1,0,0,price,bar);

   else

   ema = prev + 2.0/(1+per)*(iMA(NULL,0,1,0,0,price,bar) - prev); 

   

   return(ema);

}



// MA_Method=2: Wilder - Wilder Exponential Moving Average

double Wilder(int price,double prev,int per,int bar)

{

   if(bar >= Bars - 2) double wilder = iMA(NULL,0,1,0,0,price,bar); //SMA(array1,per,bar);

   else

   wilder = prev + (iMA(NULL,0,1,0,0,price,bar) - prev)/per; 

   

   return(wilder);

}



// MA_Method=3: LWMA - Linear Weighted Moving Average

double LWMA(int price,int per,int bar)

{

   double Sum = 0;

   double Weight = 0;

   

      for(int i = 0;i < per;i++)

      { 

      Weight+= (per - i);

      Sum += iMA(NULL,0,1,0,0,price,bar+i)*(per - i);

      }

   if(Weight>0) double lwma = Sum/Weight;

   else lwma = 0; 

   return(lwma);

} 



double LWMAOnArray(double& array[],int per,int bar)

{

   double Sum = 0;

   double Weight = 0;

   

      for(int i = 0;i < per;i++)

      { 

      Weight+= (per - i);

      Sum += array[bar+i]*(per - i);

      }

   if(Weight>0) double lwma = Sum/Weight;

   else lwma = 0; 

   return(lwma);

}



 

// MA_Method=4: SineWMA - Sine Weighted Moving Average

double SineWMA(int price,int per,int bar)

{

   double pi = 3.1415926535;

   double Sum = 0;

   double Weight = 0;

  

      for(int i = 0;i < per;i++)

      { 

      Weight+= MathSin(pi*(i+1)/(per+1));

      Sum += iMA(NULL,0,1,0,0,price,bar+i)*MathSin(pi*(i+1)/(per+1)); 

      }

   if(Weight>0) double swma = Sum/Weight;

   else swma = 0; 

   return(swma);

}



// MA_Method=5: TriMA - Triangular Moving Average

double TriMA(int price,int per,int bar)

{

   double sma;

   int len = MathCeil((per+1)*0.5);

   

   double sum=0;

   for(int i = 0;i < len;i++) 

   {

   sma = SMA(price,len,bar+i);

   sum += sma;

   } 

   double trima = sum/len;

   

   return(trima);

}



// MA_Method=6: LSMA - Least Square Moving Average (or EPMA, Linear Regression Line)

double LSMA(int price,int per,int bar)

{   

   double Sum=0;

   for(int i=per; i>=1; i--) Sum += (i-(per+1)/3.0)*iMA(NULL,0,1,0,0,price,bar+per-i);

   double lsma = Sum*6/(per*(per+1));

   return(lsma);

}



// MA_Method=7: SMMA - Smoothed Moving Average

double SMMA(int price,double prev,int per,int bar)

{

   if(bar == Bars - per) double smma = SMA(price,per,bar);

   else

   if(bar < Bars - per)

   {

   double Sum = 0;

   for(int i = 0;i < per;i++) Sum += iMA(NULL,0,1,0,0,price,bar+i+1);

   smma = (Sum - prev + iMA(NULL,0,1,0,0,price,bar))/per;

   }

   

   return(smma);

}



// MA_Method=8: HMA - Hull Moving Average by Alan Hull

double HMA(int price,int per,int bar)

{

   double _tmp[];

   int len = MathSqrt(per);

   

   ArrayResize(_tmp,len);

   

   if(bar == Bars - per) double hma = iMA(NULL,0,1,0,0,price,bar); 

   else

   if(bar < Bars - per)

   {

   for(int i=0;i<len;i++) _tmp[i] = 2*LWMA(price,per/2,bar+i) - LWMA(price,per,bar+i);  

   hma = LWMAOnArray(_tmp,len,0); 

   }  



   return(hma);

}



// MA_Method=9: ZeroLagEMA - Zero-Lag Exponential Moving Average

double ZeroLagEMA(int price,double prev,int per,int bar)

{

   double alfa = 2.0/(1+per); 

   int lag = 0.5*(per - 1); 

   

   if(bar >= Bars - lag) double zema = iMA(NULL,0,1,0,0,price,bar);

   else

   zema = alfa*(2*iMA(NULL,0,1,0,0,price,bar) - iMA(NULL,0,1,0,0,price,bar+lag)) + (1-alfa)*prev;

   

   return(zema);

}



// MA_Method=10: DEMA - Double Exponential Moving Average by Patrick Mulloy

double DEMA(int index,int num,int price,double per,double v,int bar)

{

   double alpha = 2.0/(1+per);

   if(bar == Bars - 2) {double dema = iMA(NULL,0,1,0,0,price,bar); tmp[num][index][0] = dema; tmp[num+1][index][0] = dema;}

   else

   if(bar <  Bars - 2) 

   {

   tmp[num  ][index][0] = tmp[num  ][index][1] + alpha*(iMA(NULL,0,1,0,0,price,bar) - tmp[num  ][index][1]); 

   tmp[num+1][index][0] = tmp[num+1][index][1] + alpha*(tmp[num][index][0]          - tmp[num+1][index][1]); 

   dema                 = tmp[num  ][index][0]*(1+v) - tmp[num+1][index][0]*v;

   }

   

   return(dema);

}



double DEMAOnArray(int index,int num,double price,double per,double v,int bar)

{

   double alpha = 2.0/(1+per);

   if(bar == Bars - 2) {double dema = price; tmp[num][index][0] = dema; tmp[num+1][index][0] = dema;}

   else

   if(bar <  Bars - 2) 

   {

   tmp[num  ][index][0] = tmp[num  ][index][1] + alpha*(price              - tmp[num  ][index][1]); 

   tmp[num+1][index][0] = tmp[num+1][index][1] + alpha*(tmp[num][index][0] - tmp[num+1][index][1]); 

   dema                 = tmp[num  ][index][0]*(1+v) - tmp[num+1][index][0]*v;

   }

   

   return(dema);

}



// MA_Method=11: T3 by T.Tillson

double T3_basic(int index,int num,int price,int per,double v,int bar)

{

   double dema1, dema2;

   

   if(bar == Bars - 2) 

   {

   double T3 = iMA(NULL,0,1,0,0,price,bar); 

   for(int k=0;k<6;k++) tmp[num+k][index][0] = T3;

   }

   else

   if(bar < Bars - 2) 

   {

   T3    = iMA(NULL,0,1,0,0,price,bar); 

   dema1 = DEMAOnArray(index,num  ,T3   ,per,v,bar); 

   dema2 = DEMAOnArray(index,num+2,dema1,per,v,bar); 

   T3    = DEMAOnArray(index,num+4,dema2,per,v,bar);

   }

   

   return(T3);

}



// MA_Method=12: ITrend - Instantaneous Trendline by J.Ehlers

double ITrend(int price,double& array[],int per,int bar)

{

   double alfa = 2.0/(per + 1);

   if(bar < Bars - 7)

   double it = (alfa - 0.25*alfa*alfa)*iMA(NULL,0,1,0,0,price,bar) + 0.5*alfa*alfa*iMA(NULL,0,1,0,0,price,bar+1) 

             - (alfa - 0.75*alfa*alfa)*iMA(NULL,0,1,0,0,price,bar+2) + 2*(1-alfa)*array[1] - (1-alfa)*(1-alfa)*array[2];

   else

   it = (iMA(NULL,0,1,0,0,price,bar) + 2*iMA(NULL,0,1,0,0,price,bar+1) + iMA(NULL,0,1,0,0,price,bar)+2)/4;

   

   return(it);

}



// MA_Method=13: Median - Moving Median

double Median(int price,int per,int bar)

{

   double array[];

   ArrayResize(array,per);

   

   for(int i = 0; i < per;i++) array[i] = iMA(NULL,0,1,0,0,price,bar+i);

   ArraySort(array);

   

   int num = MathRound((per-1)/2); 

   if(MathMod(per,2) > 0) double median = array[num]; else median = 0.5*(array[num]+array[num+1]);

    

   return(median); 

}



// MA_Method=14: GeoMean - Geometric Mean

double GeoMean(int price,int per,int bar)

{

   if(bar < Bars - per)

   { 

   double gmean = MathPow(iMA(NULL,0,1,0,0,price,bar),1.0/per); 

   for(int i = 1; i < per;i++) gmean *= MathPow(iMA(NULL,0,1,0,0,price,bar+i),1.0/per); 

   }

   

   return(gmean);

}



// MA_Method=15: REMA - Regularized EMA by Chris Satchwell

double REMA(int price,double& array[],int per,double lambda,int bar)

{

   double alpha =  2.0/(per + 1);

   if(bar >= Bars - 3) double rema = iMA(NULL,0,1,0,0,price,bar);

   else

   rema = (array[1]*(1+2*lambda) + alpha*(iMA(NULL,0,1,0,0,price,bar) - array[1]) - lambda*array[2])/(1+lambda); 

   

   return(rema);

}



// MA_Method=16: ILRS - Integral of Linear Regression Slope

double ILRS(int price,int per,int bar)

{

   double sum = per*(per-1)*0.5;

   double sum2 = (per-1)*per*(2*per-1)/6.0;

     

   double sum1 = 0;

   double sumy = 0;

      for(int i=0;i<per;i++)

      { 

      sum1 += i*iMA(NULL,0,1,0,0,price,bar+i);

      sumy += iMA(NULL,0,1,0,0,price,bar+i);

      }

   double num1 = per*sum1 - sum*sumy;

   double num2 = sum*sum - per*sum2;

   

   if(num2 != 0) double slope = num1/num2; else slope = 0; 

   double ilrs = slope + SMA(price,per,bar);

   

   return(ilrs);

}



// MA_Method=17: IE/2 - Combination of LSMA and ILRS

double IE2(int price,int per,int bar)

{

   double ie = 0.5*(ILRS(price,per,bar) + LSMA(price,per,bar));

      

   return(ie); 

}



// MA_Method=18: TriMAgen - Triangular Moving Average Generalized by J.Ehlers

double TriMA_gen(int price,int per,int bar)

{

   int len1 = MathFloor((per+1)*0.5);

   int len2 = MathCeil((per+1)*0.5);

   double sum=0;

   for(int i = 0;i < len2;i++) sum += SMA(price,len1,bar+i);

   double trimagen = sum/len2;

   

   return(trimagen);

}



double TriMA_genOnArray(double& array[],int per,int bar)

{

   int len1 = MathFloor((per+1)*0.5);

   int len2 = MathCeil((per+1)*0.5);

   double sum=0;

   for(int i = 0;i < len2;i++) sum += SMAOnArray(array,len1,bar+i);

   double trimagen = sum/len2;

   

   return(trimagen);

}



// MA_Method=19: VWMA - Volume Weighted Moving Average

double VWMA(int price,int per,int bar)

{

   double Sum = 0;

   double Weight = 0;

   

      for(int i = 0;i < per;i++)

      { 

      Weight+= Volume[bar+i];

      Sum += iMA(NULL,0,1,0,0,price,bar+i)*Volume[bar+i];

      }

   if(Weight>0) double vwma = Sum/Weight;

   else vwma = 0; 

   return(vwma);

} 



// MA_Method=20: JSmooth - Smoothing by Mark Jurik

double JSmooth(int index,int num,int price,int per,double pow,int bar)

{

   double beta  = 0.45*(per-1)/(0.45*(per-1)+2);

double alpha = MathPow(beta,pow);

double _ma   = iMA(NULL,0,1,0,0,price,bar); 

if(bar == Bars - 2) 

{

tmp[num+4][index][0] = _ma; 

tmp[num+0][index][0] = _ma; 

tmp[num+2][index][0] = _ma;

}

else

   if(bar <  Bars - 2) 

   {

tmp[num+0][index][0] = (1-alpha)*_ma + alpha*tmp[num+0][index][1];

tmp[num+1][index][0] = (_ma - tmp[num+0][index][0])*(1-beta) + beta*tmp[num+1][index][1];

tmp[num+2][index][0] = tmp[num+0][index][0] + tmp[num+1][index][0];

tmp[num+3][index][0] = (tmp[num+2][index][0] - tmp[num+4][index][1])*MathPow((1-alpha),2) + MathPow(alpha,2)*tmp[num+3][index][1];

tmp[num+4][index][0] = tmp[num+4][index][1] + tmp[num+3][index][0]; 

   }

   

   return(tmp[num+4][index][0]);

}



// MA_Method=21: SMA_eq     - Simplified SMA

double SMA_eq(int price,double& array[],int per,int bar)

{

   if(bar == Bars - per) double sma = SMA(price,per,bar);

   else

   if(bar <  Bars - per) sma = (iMA(NULL,0,1,0,0,price,bar) - iMA(NULL,0,1,0,0,price,bar+per))/per + array[1]; 

   

   return(sma);

}                        



// MA_Method=22: ALMA by Arnaud Legoux / Dimitris Kouzis-Loukas / Anthony Cascino

double ALMA(int price,int per,double offset,double sigma,int bar)

{

   double m = MathFloor(offset * (per - 1));

double s = per/sigma;

double w, sum =0, wsum = 0;

for (int i=0;i < per;i++) 

{

w = MathExp(-((i - m)*(i - m))/(2*s*s));

   wsum += w;

   sum += iMA(NULL,0,1,0,0,price,bar+(per-1-i))*w; 

   }

   

   if(wsum != 0) double alma = sum/wsum; 

   

   return(alma);

}   



// MA_Method=23: TEMA - Triple Exponential Moving Average by Patrick Mulloy

double TEMA(int index,int price,int per,double v,int bar)

{

   double alpha = 2.0/(per+1);

double _ma   = iMA(NULL,0,1,0,0,price,bar);

if(bar == Bars - 2) {tmp[0][index][0] = _ma; tmp[1][index][0] = _ma; tmp[2][index][0] = _ma;}

else

   if(bar <  Bars - 2) 

   {

tmp[0][index][0] = tmp[0][index][1] + alpha *(_ma               - tmp[0][index][1]);

tmp[1][index][0] = tmp[1][index][1] + alpha *(tmp[0][index][0] - tmp[1][index][1]);

tmp[2][index][0] = tmp[2][index][1] + alpha *(tmp[1][index][0] - tmp[2][index][1]);

tmp[3][index][0] = tmp[0][index][0] + v*(tmp[0][index][0] + v*(tmp[0][index][0]-tmp[1][index][0]) - tmp[1][index][0] - v*(tmp[1][index][0] - tmp[2][index][0])); 

}

   

   return(tmp[3][index][0]);

}



// MA_Method=24: T3 by T.Tillson (correct version) 

double T3(int index,int num,double price,int per,double v,int bar)

{

   double len = MathMax((per + 5.0)/3.0-1,1), dema1, dema2;

   double T3, _ma = iMA(NULL,0,1,0,0,price,bar); 

   

   if(bar == Bars - 2) for(int k=0;k<6;k++) tmp[num+k][index][0] = _ma;

   else

   if(bar < Bars - 2) 

   {

   dema1 = DEMAOnArray(index,num  ,_ma  ,len,v,bar); 

   dema2 = DEMAOnArray(index,num+2,dema1,len,v,bar); 

   T3    = DEMAOnArray(index,num+4,dema2,len,v,bar);

   }

   

   return(T3);

}



// MA_Method=25: Laguerre filter by J.Ehlers

double Laguerre(int index,int price,int per,int order,int bar)

{

   double gamma = 1-10.0/(per+9);

   double _ma   = iMA(NULL,0,1,0,0,price,bar);

   double aPrice[];

   

   ArrayResize(aPrice,order);

   

   for(int i=0;i<order;i++)

   {

      if(bar >= Bars - order) tmp[i][index][0] = _ma;

      else

      {

         if(i == 0) tmp[i][index][0] = (1 - gamma)*_ma + gamma*tmp[i][index][1];

         else

         tmp[i][index][0] = -gamma * tmp[i-1][index][0] + tmp[i-1][index][1] + gamma * tmp[i][index][1];

      

      aPrice[i] = tmp[i][index][0];

      }

   }

   double laguerre = TriMA_genOnArray(aPrice,order,0);  



   return(laguerre);

}



// MA_Method=26:  MD - McGinley Dynamic

double McGinley(int price,double prev,int per,int bar)

{

   if(bar == Bars - 2) double md = iMA(NULL,0,1,0,0,price,bar);

   else

   if(bar <  Bars - 2 && prev > 0) 

   {

   double p = iMA(NULL,0,1,0,0,price,bar);

   md = prev + (p - prev)/(per*MathPow(p/prev,4)/2); 

   }

   return(md);

}



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