MQL5 Programming Articles
Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.
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Neural Networks in Trading: From Transformers to Spiking Neurons (Conclusion)
Neural networks are already changing the way we analyze markets, and new architectures are opening up even more possibilities. In this article, we wrap up our work with the SpikingBrain framework, which opens up new possibilities for us.
The Maximal Information Coefficient: Detecting Any Relationship, and the Null That Decides Whether It Is Real
This article implements the Maximal Information Coefficient (MINE) for MQL5, including the grid search with dynamic programming and the four MINE statistics. It explains why raw MIC has a nonzero noise floor and builds a permutation null to judge significance. The result is a verified library with a dependence scanner and a chart indicator, allowing you to test features and interpret scores consistently across relationship shapes.
Certified Robustness Radius: Knowing How Much Noise Your ONNX Trading Model Can Survive
We introduce a certified-radius gate for ONNX signals implemented natively in MQL5. The system estimates per-prediction robustness via randomized smoothing and a one-sided Clopper–Pearson bound, then applies the radius to trade admission, lot scaling, and monitoring. This provides an actionable confidence margin that reflects input noise tolerance rather than softmax magnitude.