Conversion d'indicateurs vers ProBuilder

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05/08/2017 at 3:27 PM #34835

laurenzo

Plutôt que d’ouvrir plein de topics pour la conversion d’indicateurs (comme j’ai déjà fait :o)), je préfère créer un thread ici pour centraliser les indicateurs que j’aimerais convertir sous PRT.

Merci d’avance à tous pour votre aide!

laurenzo

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05/08/2017 at 3:29 PM #34836

laurenzo

Du code MT4 pour un filtre Kalman de Jurik

double jkalman(int index,double price,int len,int bar)
{
   double alpha = (Phase*Order)/(len + Phase*Order-1); 
   double beta  = 1 - alpha;
   
   if(jk_prevtime[index] != Time[bar])
   {
   for(int k=0;k<2*Order;k++) jk_tmp[k][index][1] = jk_tmp[k][index][0];
   jk_prevtime[index] = Time[bar];
   }
   
   if(bar==Bars-2)
   {
   ArrayInitialize(jk_tmp,price);
   }
   
   for(k=0;k<Order;k++)
   {
   int j=2*k;
   jk_tmp[j][index][0]   = beta*jk_tmp[j][index][1]   + alpha*price;
   jk_tmp[j+1][index][0] = beta*jk_tmp[j+1][index][1] + alpha*jk_tmp[j][index][0];   
   price                 = jk_tmp[j][index][0] + Amplitude *(jk_tmp[j][index][0] - jk_tmp[j+1][index][0]);
   }
   
   return(price); 
}

double jkalman(int index,double price,int len,int bar)

{

double alpha = (Phase*Order)/(len + Phase*Order-1);

double beta = 1 - alpha;

if(jk_prevtime[index] != Time[bar])

{

for(int k=0;k<2*Order;k++) jk_tmp[k][index][1] = jk_tmp[k][index][0];

jk_prevtime[index] = Time[bar];

}

if(bar==Bars-2)

{

ArrayInitialize(jk_tmp,price);

}

for(k=0;k<Order;k++)

{

int j=2*k;

jk_tmp[j][index][0] = beta*jk_tmp[j][index][1] + alpha*price;

jk_tmp[j+1][index][0] = beta*jk_tmp[j+1][index][1] + alpha*jk_tmp[j][index][0];

price = jk_tmp[j][index][0] + Amplitude *(jk_tmp[j][index][0] - jk_tmp[j+1][index][0]);

}

return(price);

}

laurenzo

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05/08/2017 at 3:30 PM #34837

laurenzo

Du code MultiCharts (pareil que Tradestation) pour un Filtre Médian

// MF - Median Filter by John Ehlers

// Series
// Len

MF = Median(Series, 2 * Len + 1);

RETURN MF

// MF - Median Filter by John Ehlers

// Series

// Len

MF = Median(Series, 2 * Len + 1);

RETURN MF

Et un autre filtre Median d’Ehlers

// MMADF - Median-MA Difference Filter by John Ehlers

Inputs:
        Series ( NumericSeries ),
        Len ( NumericSimple ),
        Threshold ( NumericSimple );

Variables:
        Alpha ( 0 ),
        Length ( 0 ),
        Smooth ( 0 );

Length = Len;

Smooth = (Series + 2 * Series[1] + 2 * Series[2] + Series[3]) / 6;

Value3 = 1;

while Value3 > Threshold
begin
      Alpha = 2 / (Length + 1);
      Value1 = Median(Smooth, Length);
      Value2 = Alpha * Smooth + (1 - Alpha) * Value2[1];
      if Value1 <> 0 then
         Value3 = AbsValue(Value1 - Value2) / Value1;
      Length = Length - 2;
end;

if Length < 3 then
   Length = 3;

Alpha = 2 / (Length + 1);

if CurrentBar < 4 then
   MMADF = Series
else
   MMADF = Alpha * Smooth + (1 - Alpha) * MMADF[1];

// MMADF - Median-MA Difference Filter by John Ehlers

Inputs:

Series ( NumericSeries ),

Len ( NumericSimple ),

Threshold ( NumericSimple );

Variables:

Alpha ( 0 ),

Length ( 0 ),

Smooth ( 0 );

Length = Len;

Smooth = (Series + 2 * Series[1] + 2 * Series[2] + Series[3]) / 6;

Value3 = 1;

while Value3 > Threshold

begin

Alpha = 2 / (Length + 1);

Value1 = Median(Smooth, Length);

Value2 = Alpha * Smooth + (1 - Alpha) * Value2[1];

if Value1 <> 0 then

Value3 = AbsValue(Value1 - Value2) / Value1;

Length = Length - 2;

end;

if Length < 3 then

Length = 3;

Alpha = 2 / (Length + 1);

if CurrentBar < 4 then

MMADF = Series

else

MMADF = Alpha * Smooth + (1 - Alpha) * MMADF[1];

laurenzo

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05/08/2017 at 3:34 PM #34838

laurenzo

Un autre filtre d’Ehlers!

// DCEF - Distance Coefficient Ehlers Filter by John Ehlers

Inputs:
        Series ( NumericSeries ), 
        Len ( NumericSimple );

Variables:
        j ( 0 ),
        Smooth ( 0 ),
        LookBack ( 0 ),
        Num ( 0 ),
        SumCoef ( 0 );

Array:
        Coef[50](0),
        Distance2[50](0);

Smooth = (Series + 2 * Series[1] + 2 * Series[2] + Series[3]) / 6;

for j = 0 to Len - 1
begin
    Distance2[j] = 0;
    for Lookback = 1 to Len-1
    begin
        Distance2[j] = Distance2[j] + (Smooth[j] - Smooth[j + Lookback]) * (Smooth[j] - Smooth[j + Lookback]);
    end;
    Coef[j] = Distance2[j];
end;

Num = 0;
SumCoef = 0;

for j = 0 to Len - 1
begin
        Num = Num + Coef[j] * Smooth[j];
        SumCoef = Sumcoef + Coef[j];
end;

if SumCoef <> 0 then
   DCEF = Num / SumCoef
else
   DCEF = Series;

// DCEF - Distance Coefficient Ehlers Filter by John Ehlers

Inputs:

Series ( NumericSeries ),

Len ( NumericSimple );

Variables:

j ( 0 ),

Smooth ( 0 ),

LookBack ( 0 ),

Num ( 0 ),

SumCoef ( 0 );

Array:

Coef[50](0),

Distance2[50](0);

Smooth = (Series + 2 * Series[1] + 2 * Series[2] + Series[3]) / 6;

for j = 0 to Len - 1

begin

Distance2[j] = 0;

for Lookback = 1 to Len-1

begin

Distance2[j] = Distance2[j] + (Smooth[j] - Smooth[j + Lookback]) * (Smooth[j] - Smooth[j + Lookback]);

end;

Coef[j] = Distance2[j];

end;

Num = 0;

SumCoef = 0;

for j = 0 to Len - 1

begin

Num = Num + Coef[j] * Smooth[j];

SumCoef = Sumcoef + Coef[j];

end;

if SumCoef <> 0 then

DCEF = Num / SumCoef

else

DCEF = Series;

laurenzo

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05/08/2017 at 3:35 PM #34839

laurenzo

C’est déjà pas mal pour le moment :o)

laurenzo

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05/08/2017 at 3:42 PM #34840

Nicolas

Ces indicateurs te sont utiles pour quelles applications stp ? Des exemples d’utilisations peut être ? Merci.

Nicolas

Keymaster

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Replies: 20863

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05/08/2017 at 4:41 PM #34843

laurenzo

jkalman = Un filtre Kalman fait par Jurik. Tu peux t’en servir comme filtre sur les prix et ça te fait une moyenne mobile super réactive et lisse. C’est sûrement un des meilleurs filtres (un peu comme jsmooth).

Le filtre médian, c’est pas trop utile en tant que tel, mais c’est utilisé par d’autres filtres comme le Median-MA Difference Filter de John Ehlers. Un lien pour avoir une idée d’à quoi ça ressemble http://www.stockspotter.com/Files/whatsthedifference.pdf
Ca peut servir de filtre encore une fois, de moyenne mobile et de STOP 😉

Même genre pour DCEF, https://www.mesasoftware.com/papers/EhlersFilters.pdf

laurenzo

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05/09/2017 at 1:54 PM #34943

laurenzo

Dans le genre sexy de chez sexy qui peut s’utiliser pour lisser des prix, des filtres Butterworth, Bessel, Critically Damped de 1 à 5 pôles :

http://unicorn.us.com/trading/src/_filter2pole.txt

A traduire de TradeStation. A mon avis ça doit être vraiment sympa 🙂

laurenzo

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05/09/2017 at 4:03 PM #34955

Nicolas

J’ai trouvé 2 versions du filtre Kalman sur le blog de HK-Lisse, les voici:

///////////// Kalman Filter ///////////////////
pr=medianprice
once pred=pr
if barindex>0 then
    dk=pr-pred
    smooth=pred+dk*SQRT((gain/10000)*2)
    velo=velo+((gain/10000)*dk)
    pred=smooth+velo
    kf=pred
endif
return kf

///////////// Kalman Filter ///////////////////

pr=medianprice

once pred=pr

if barindex>0 then

dk=pr-pred

smooth=pred+dk*SQRT((gain/10000)*2)

velo=velo+((gain/10000)*dk)

pred=smooth+velo

kf=pred

endif

return kf

////////////// Kalman version Ehlers ///////////////////
prix=totalprice
once kil=prix
if barindex>4 then
    kil=.33*(prix+.5*(prix-prix[3]))+.67*kil[1]
endif
return  kil

////////////// Kalman version Ehlers ///////////////////

prix=totalprice

once kil=prix

if barindex>4 then

kil=.33*(prix+.5*(prix-prix[3]))+.67*kil[1]

endif

return kil

1 user thanked author for this post.

laurenzo

Nicolas

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Topics: 81

Replies: 20863

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05/10/2017 at 12:11 PM #35050

laurenzo

Quelques indicateurs du jour 😀

Double smoothed EMA

Je suppose que ça doit être une DEMA plus lisse.

double workDsema[][_maWorkBufferx2];
#define _ema1 0
#define _ema2 1

double iDsema(double price, double period, int r, int instanceNo=0)
{
   if (ArraySize(workDsema)!= Bars) ArrayResize(workDsema,Bars); instanceNo*=2;

   double alpha = 2.0 /(1.0+MathSqrt(period));
          workDsema[r][_ema1+instanceNo] = workDsema[r-1][_ema1+instanceNo]+alpha*(price                         -workDsema[r-1][_ema1+instanceNo]);
          workDsema[r][_ema2+instanceNo] = workDsema[r-1][_ema2+instanceNo]+alpha*(workDsema[r][_ema1+instanceNo]-workDsema[r-1][_ema2+instanceNo]);
   return(workDsema[r][_ema2+instanceNo]);
}

double workDsema[][_maWorkBufferx2];

#define _ema1 0

#define _ema2 1

double iDsema(double price, double period, int r, int instanceNo=0)

{

if (ArraySize(workDsema)!= Bars) ArrayResize(workDsema,Bars); instanceNo*=2;

double alpha = 2.0 /(1.0+MathSqrt(period));

workDsema[r][_ema1+instanceNo] = workDsema[r-1][_ema1+instanceNo]+alpha*(price -workDsema[r-1][_ema1+instanceNo]);

workDsema[r][_ema2+instanceNo] = workDsema[r-1][_ema2+instanceNo]+alpha*(workDsema[r][_ema1+instanceNo]-workDsema[r-1][_ema2+instanceNo]);

return(workDsema[r][_ema2+instanceNo]);

}

Smoothed MA

Une simple MA plus lisse?

double workSmma[][_maWorkBufferx1];
double iSmma(double price, double period, int r, int instanceNo=0)
{
   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 workSmma[][_maWorkBufferx1];

double iSmma(double price, double period, int r, int instanceNo=0)

{

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]);

}

Parabolic weighted MA

/

double workLwmp[][_maWorkBufferx1];
double iLwmp(double price, double period, int r, int instanceNo=0)
{
   if (ArraySize(workLwmp)!= Bars) ArrayResize(workLwmp,Bars);
   
   workLwmp[r][instanceNo] = price;
      double sumw = period*period;
      double sum  = sumw*price;

      for(int k=1; k<period && (r-k)>=0; k++)
      {
         double weight = (period-k)*(period-k);
                sumw  += weight;
                sum   += weight*workLwmp[r-k][instanceNo];  
      }             
      return(sum/sumw);
}

double workLwmp[][_maWorkBufferx1];

double iLwmp(double price, double period, int r, int instanceNo=0)

{

if (ArraySize(workLwmp)!= Bars) ArrayResize(workLwmp,Bars);

workLwmp[r][instanceNo] = price;

double sumw = period*period;

double sum = sumw*price;

for(int k=1; k<period && (r-k)>=0; k++)

{

double weight = (period-k)*(period-k);

sumw += weight;

sum += weight*workLwmp[r-k][instanceNo];

}

return(sum/sumw);

}

laurenzo

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05/10/2017 at 12:19 PM #35051

laurenzo

Une zéro lag que je ne connais pas!

double workZl[][_maWorkBufferx2];
#define _price 0
#define _zlema 1

double iZeroLag(double price, double length, int r, int instanceNo=0)
{
   if (ArrayRange(workZl,0)!=Bars) ArrayResize(workZl,Bars); instanceNo *= 2;

   //
   //
   //
   //
   //

   double alpha = 2.0/(1.0+length); 
   int    per   = (length-1.0)/2.0; 

   workZl[r][_price+instanceNo] = price;
   if (r<per)
          workZl[r][_zlema+instanceNo] = price;
   else   workZl[r][_zlema+instanceNo] = workZl[r-1][_zlema+instanceNo]+alpha*(2.0*price-workZl[r-per][_price+instanceNo]-workZl[r-1][_zlema+instanceNo]);
   return(workZl[r][_zlema+instanceNo]);
}

double workZl[][_maWorkBufferx2];

#define _price 0

#define _zlema 1

double iZeroLag(double price, double length, int r, int instanceNo=0)

{

if (ArrayRange(workZl,0)!=Bars) ArrayResize(workZl,Bars); instanceNo *= 2;

double alpha = 2.0/(1.0+length);

int per = (length-1.0)/2.0;

workZl[r][_price+instanceNo] = price;

if (r<per)

workZl[r][_zlema+instanceNo] = price;

else workZl[r][_zlema+instanceNo] = workZl[r-1][_zlema+instanceNo]+alpha*(2.0*price-workZl[r-per][_price+instanceNo]-workZl[r-1][_zlema+instanceNo]);

return(workZl[r][_zlema+instanceNo]);

}

laurenzo

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05/10/2017 at 12:47 PM #35054

laurenzo

Moyenne Mobile Leader

double workLeader[][_maWorkBufferx2];
double iLeader(double price, double period, int r, int instanceNo=0)
{
if (ArrayRange(workLeader,0)!= Bars) ArrayResize(workLeader,Bars); instanceNo*=2;

period = MathMax(period,1);
double alpha = 2.0/(period+1.0);
workLeader[r][instanceNo ] = workLeader[r-1][instanceNo ]+alpha*(price -workLeader[r-1][instanceNo ]);
workLeader[r][instanceNo+1] = workLeader[r-1][instanceNo+1]+alpha*(price-workLeader[r][instanceNo]-workLeader[r-1][instanceNo+1]);

return(workLeader[r][instanceNo]+workLeader[r][instanceNo+1]);
}

Comment on traduirait instanceNo+instanceNo+1? C’est le temps? le prix? Une autre variable?

J’ai du mal à voir.

laurenzo

Participant

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Replies: 64

Been thanked: 16 times

05/10/2017 at 1:13 PM #35056

laurenzo

C’est un truc dans le genre?

double alpha = 2.0/(period+1.0)

i1 = i1[1] + alpha * (price – i1[1])
i2 = i2[1] + alpha * (price – i1 – i2[1])

return i1 + i2

laurenzo

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05/10/2017 at 1:33 PM #35060

laurenzo

Smoothed Simple Moving Average

Voilà j’ai tenté la conversion 😉

// --- parameters
Series = CustomClose
// Period = 20
// ---

IF BarIndex < Period THEN
    SMMA = Series
ELSE
    SMMA = SMMA[1] + (Series - SMMA[1]) / Period
ENDIF

RETURN SMMA

// --- parameters

Series = CustomClose

// Period = 20

// ---

IF BarIndex < Period THEN

SMMA = Series

ELSE

SMMA = SMMA[1] + (Series - SMMA[1]) / Period

ENDIF

RETURN SMMA

laurenzo

Participant

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Replies: 64

Been thanked: 16 times

05/10/2017 at 1:42 PM #35065

laurenzo

Leader Exponential Moving Average

J’ai tenté la conversion 😉

//-----------------------------------//
// Leader Exponential Moving Average //
//-----------------------------------//

// --- parameters
Series = CustomClose
// Period = 20
// ---

Period = MAX(Period, 1)

IF BarIndex <= Period THEN
    p1 = Series
    p2 = Series
ELSE
    alpha = 2 / (Period + 1)
    p1 = p1[1] + alpha * (Series - p1[1])
    p2 = p2[1] + alpha * (Series - p1 - p2[1])
ENDIF

LEMA = p1 + p2

RETURN LEMA

//-----------------------------------//

// Leader Exponential Moving Average //

//-----------------------------------//

// --- parameters

Series = CustomClose

// Period = 20

// ---

Period = MAX(Period, 1)

IF BarIndex <= Period THEN

p1 = Series

p2 = Series

ELSE

alpha = 2 / (Period + 1)

p1 = p1[1] + alpha * (Series - p1[1])

p2 = p2[1] + alpha * (Series - p1 - p2[1])

ENDIF

LEMA = p1 + p2

RETURN LEMA

laurenzo

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Been thanked: 16 times

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