Discussion of article "Practical application of neural networks in trading. It's time to practice"

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New article Practical application of neural networks in trading. It's time to practice has been published:

The article provides a description and instructions for the practical use of neural network modules on the Matlab platform. It also covers the main aspects of creation of a trading system using the neural network module. In order to be able to introduce the complex within one article, I had to modify it so as to combine several neural network module functions in one program.

The below figure shows how the Neural Network Module looks like at the initial launch.

НСМ EURUSD_MT5

  1. The Online block is designed to start and stop neural networks during real trading and when testing in the visual mode.
  2. Information fields with the conditions for the signal line crossing the response line of neural networks, when the Online block is activated. 
  3. "Train" is a demonstration block which is designed for training and "retraining" (?) of neural networks.
  4. Fields for outputting the response values of neural networks. Left - neural network responses; right - the signal line. Lower - current bar, upper - previous bar.
  5. The Offline block is designed for outputting neural network responses in a test sample to an array.
  6. Field for entering the averaging value for the neural network response line when using the Online block. (Signal line period). Editable value.
  7. Blocks "Net1,2,3" — three submodules of networks trained in different segments of a time series. Each block includes two neural networks.
  8. NNM operation end time when using the Online block.
  9. Field for entering the NNM operation period in hours, when using the Online block. Editable value.
  10. Counting the time elapsed since NNM start, when using the Online block.

Author: Andrey Dibrov

 
This is outstanding ! You are for real, I salute. <Deleted>
 
This is a great contribution and more sophisticated approach to trading FX. I will spend some time to study your approach and try to replicate. Thank you!
 

Temporal Convolutional neural network TCN's versus RNN 

Latest Neural network design TCN neural nets explained in attached PDF...

(TCN's Faster and more effective... )

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