Discussing the article: "Integrating Computer Vision into Trading in MQL5 (Part 2): Extending the Architecture to 2D RGB Image Analysis"

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Check out the new article: Integrating Computer Vision into Trading in MQL5 (Part 2): Extending the Architecture to 2D RGB Image Analysis.

Computer vision for trading: how it works and how to develop it step by step. We create an algorithm for recognition of RGB images of price charts using the attention mechanism and a bidirectional LSTM layer. As a result, we obtain a working model for forecasting the EURUSD price with the accuracy of up to 55% in the validation section.

In the first part of our research we showed how convolutional neural networks can analyze time series of currency quotes through one-dimensional filters. Now we are taking a qualitative leap: we are going to teach algorithms to perceive the market as a holistic landscape filled with textures, patterns, and hidden signals.

Transforming dry numerical series into images allows the algorithm to analyze the market from a completely new perspective. This is exactly how master traders think, seeing not just tables of data, but a living picture of the market, where every detail carries a significant signal. The algorithm rises above the one-dimensional representation, revealing structures and patterns that remain invisible in numerical series.


Author: Yevgeniy Koshtenko

 
I appreciate your work. Thanks for helping the community.
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