Discussion of article "Practical application of neural networks in trading (Part 2). Computer vision"

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New article Practical application of neural networks in trading (Part 2). Computer vision has been published:

The use of computer vision allows training neural networks on the visual representation of the price chart and indicators. This method enables wider operations with the whole complex of technical indicators, since there is no need to feed them digitally into the neural network.

Before preparing an array of images, define the purpose of your neural network. Ideally, it would be great to train the network at pivots. According to this purpose, we would need to make screenshots with the last extreme bar. However, this experiment showed no practical value. That is why we will use another set of images. Further, you can experiment with different arrays, including the above mentioned one. This may also provide additional proofs of the efficiency of neural networks in solving image-based classification tasks. The neural network responses obtained on a continuous time series require additional optimization. 

Let us not complicate the experiment and focus on two categories of images:

  • Buy - when the price moves up or when the price has reached the daily low
  • Sell - when the price moves down or when the price has reached the daily high

Buy   Buy1  Buy2  Buy3

For neural network training purposes, the movement in any direction will be determined as the price reaching new extreme values in trend direction. At these moments chart screenshots will be made. Trend reversal moment is also important for network training. A chart screenshot will also be made when the price reaches the daily high or low.

Author: Andrey Dibrov

SkystheLimit 986
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SkystheLimit 986  

Very good article! Thank you!