Discussing the article: "Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation"

 

Check out the new article: Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation.

In this part, we focus on how to merge real-time market feedback—such as live trade outcomes, volatility changes, and liquidity shifts—with adaptive model learning to maintain a responsive and self-improving trading system.

In the OnDeinit function, we remove all info labels with the ObjectsDeleteAll function specifying prefix "InfoLabel_" and type OBJ_LABEL across all subwindows, then delete the daily Fib object via "ObjectDelete" on "FIB_OBJ" and the array one on "fibName" to clear visuals. Upon compilation, we get the following outcome.

COMPILED GIF

We can see that we manage the positions by default by applying trailing stops when needed, hence achieving our objectives. The thing that remains is backtesting the program, and that is handled in the next section.

Author: Hlomohang John Borotho

 
question about -  Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation. ... the file thats added to that article. is that an actual EA? how do i go about utilizing it?
Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation
Integrating MQL5 with Data Processing Packages (Part 6): Merging Market Feedback with Model Adaptation
  • 2025.11.17
  • www.mql5.com
In this part, we focus on how to merge real-time market feedback—such as live trade outcomes, volatility changes, and liquidity shifts—with adaptive model learning to maintain a responsive and self-improving trading system.