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Data Mining with STATISTICA

Stock Quote Forecast using STATISTICA Automated Neural Networks

13th of August, 2013

I am posting a short tutorial on how to take the technical indicator data collected using R and create a forecast using STATISTICA Automated Neural Networks.  First of all I would like to make a disclaimer that I cannot be held responsible for any trading losses you might sustain due to using some of the techniques discussed here.  This tutorial is meant to demonstrate how to use STATISTICA to make a forecast.  I do not recommend using this information to guide you in making decisions about trading in the stock market.  If you do you use the techniques discussed in this tutorial, this is a warning that you do so at your own risk and will not hold the author responsible for any losses you might sustain.

The .csv file created using the information from the last blog post will need to be imported into STATISTICA.  There will need to be some formatting of the data to make it usable which will not be covered in detail here.  Note that typically the first column in the data set will not have a variable name so the column names will get offset by one.  There are several ways to deal with this.  One solution would be to remove the first column and align the variable names to the correct column using Microsoft Excel before importing the data.

Once the .csv is imported and saved as a .sta file, you will need to add five cases to the end of the .sta file.  This is necessary to provide the space to create the forecast.  This will need to be completed before watching the following video.

  1. Hi,

    Your explanation is very useful. However, I have doubts and want to ask you if you can kindly provide your email id

    Thanks and regards
    Ali

    Reply

    • The blog post was intended to demonstrate how one could go about building a stock forecasting model using Statistica. I would agree that the model is not good at forecasting. If you doubt the outcomes of the model, then you are justified in that doubt.

      Reply

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