**Installation:**

That means you need to install it in the experts folder. The indicator will write a CSV file in the folder experts/files.

**Use:**

1. Just attach the indicator at the graphic and you will se that appears a text that the export is complete.

2. Then from Trading solutions you need to upload history from a file.

It is called: Import data from your computer

Then just go to the Metatrader folder and find the file in experts/file. You will see the file with a name of the pair and the time period.

3. Open the file. There is one trick.

When you go to import data from your computer, you need to click to the option Viex text file import options for each file being imported. And then you select new files.

Why this is important. It is important because you have to manually put that the time is not a ticker but time otherwise you will get 24 times the same data.

От 23 септември 2011 |

От 23 септември 2011 |

Just you need to make sure that it looks like that:

All the rest is contained in the Tutorials.

In order to update the files you need to make sure that the CSV file is updated, maybe you would need to reload the the indicator (when you open the MT4 it is authomatically reloaded).

Then you need to go to update options from the import data wizard. You need to tab Update data in the target group. Just click next, and you should be done.

Why this is important. In fact it is important because you can upload data from Meta Trader 4. Here I used the SSA end- pointed, the information is called field 8.

It will not work unless you have installed the SSA end - pointed in the MT4.

You can choose in the export history as parameters what parameters you would like to write on the CSV file. However there is one thing you need to make more data bars on the SSA ep because the default is only 300 bars and they may not match the rest of the history.

As you can guess you can replace the icustom in the export history with something else and to have your favorite meta trader indicators under Trading solutions, like jurik indicators for example.

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This is the BPNN but this time we use Sinc wavelets as inputs. You need to use more sincpast bars than the ntr. Because the wavelets need some bars to calculate.

extern int SincPastBars =550; //Number of past bars. 0: all data.

extern int ntr =500; // # of training sets

I think this is a valuable tool in the collection of inputs for the BPNN.

You have also the the original Sinc extrapolator that does not use neural net for extrapolation.

This is the link. Understanding Russian pays sometimes ;).

**The important parameters are:**

trun =3; //Number of the last wavelets to truncate.

Q =1.0; //Damping factor. Higher Q gives more ripple. Q=1 gives sinc function.

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This is a BPNN with the extrapolator. Here I do not use linear extrapolation. We use 0 bars ahead of linear extrapolation and we plot the extrapolation from the BPNN. Well I just combine two things. However you need more bars on the extrapolator than the BPNN.

Method 1: Fourier's extrapolation; the frequencies are calculated using the Quinn-Fernandes Algorithm

Method 2: Autocorrelation Method

Method 3: Weighted Burg Method

Method 4: Burg Method with Helme-Nikias weighting function

Method 5: Itakura-Saito (geometric) method

Method 6: Modified covariance method

Methods 2-6 are the methods of linear prediction. The linear prediction is based on finding the future values as the linear functions of the past values. Assume that we have a number of prices x[0]..x[n-1] where the higher index is compliant with the recent price. The prediction of the future price x[n] is calculated as

x[n] = -Sum(a[i]*x[n-i], i=1..p)

where a[i=1..p] - coefficients of the model, p - order of the model. The listed methods 2-6 find the coefficients a[] by decreasing the mean-root-square error on the training last n-p bars. Of course, we can reach the zero error of prediction if we directly solve the set of equations mentioned above with n=2*p by the Levinson-Durbin method. Such method of prediction is called Prony Method. Its disadvantage is the instability during the prediction of the future values of the series. That's way this method has not been included.

The other input parameters are:

LastBar - the number of the last bar in the past data

PastBars - the number of past bars used for the prediction of the future values

LPOrder - the order of the linear model as a fraction from the number of the past bars (0..1)

FutBars - the number of future bars in the prediction

HarmNo - the maximum number of frequencies for the Method 1 (0 means all frequencies)

FreqTOL - the imprecision of the frequeincies calculation for the Method 1 (if it is >0.001 it can't converge)

BurgWin - the number of the weighting function for the Method 2 (0=Rectangular 1=Hamming 2=Parabolic)

The indicator draws two lines: the blue line shows the prices of the model on the training bars, the red line shows the predicted future prices.

**Trading strategy:**

But keep in mind that this is just a forecast and not an entry signal. That is why I plot on the chart another indicator that is giving trading directionnal signal.

On the lowest window there is the iVAR (You can also use the FGDI). This is a fracal dimension index. The neural net is having better chance to give a precise forecast when you ask it when the fractal dimension is low.

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*No need to spend your time analyzing markets; this indicator does the work for you. Get precise, detailed trading recommendations to implement accurate, profitable trades. With a focus on effective trades and risk control, you'll experience an uncommon level of detail and specificity – no guesswork required.*

Got the joke ;). Well this is coming from the work of Mark Whistler or precisely Whistler Volume Adjusted Volatility - WVAV. You can see his book Volatility Illuminated. Here I added two more predictors in one set. The idea is to try to predict the volatility too, we have an upper band and a lower band. As it was shown that the volatility has a cyclical component we can try to predict that too. Even if the center line is giving us the directionnal bias the volatility predictions are quite helpful too. Play with the number of ticks that ajusts the sensitivity of the WVAV. You can change the standard deviations of the volatility bands too.

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This is a BPNN Predictor HP mod. This mod uses the values from the Hodrick-Prescott filter

nobs =1000; //Number of bars to process for filter evaluation

lambda=1600; //Higher lambda leads to the smoother data

timeframe=0;//The applied timeframe, 0=the same as chart

price =PRICE_CLOSE;//The applied price

delay =0; //Shows the result of delaying (or advancing if negative) the HP filter

trend =10; //how many consecutive filter bars to check to determine trend

future =0; //How many bars in the future to display for the HP filter

repaint =FALSE; //To repaint last bar, FALSE for faster execution

alerts =FALSE; //Enable visual alert

extern string audio ="alert.wav"; //Enable audioalert

extern int history =1000; //history bars to display on initialisation, 0 means all history

Installation:

You need to copy the extracted files in the experts folder. You need the HPMA file in order to run the BPNN Predictor with Hodrick-Prescott filter. This file is included in the zip file.

]]>I am going to futher explore this concept together with the Elliotware princpiple. Do not forget this is just a tool.

От 22 септември 2011 |

You need to download the 3rd generation MA, it is free and no registration is necessary. It is based on the work of M. G. Dürschner

Dürschner, M. G. (2011, 04). VTAD Forschungsarbeiten, Award. Retrieved from Gleitende Durchschnitte 3.0 (Moving Averages 3.0):http://www.vtad.de/node/1441

От 22 септември 2011 |

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This is for short term prediction. The Cycle period would analyse the cycle period and the jjma would smooth the data before transferring to analyse by the neural net.

In theory it should eliminate some noise compared to the regular BPNN Cycle period neural net.

I think I should add the possibility to modify the niquist factor it is set to 1.5 of dominant cycle.

In this RAR file I add all the necessary files for the installation.

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