Articles on the MQL5 programming and use of trading robots

The article provides a practical research setup for weekend gap analysis: MQL5 extracts precise pip‑based gaps and tracks fills, while Python performs statistical testing and visualization. You will compute fill rates by gap buckets, model fill probability with logistic regression, and assess time-to-fill via Kaplan–Meier curves. All steps are configurable and reproducible for EURUSD, GBPUSD, USDJPY and beyond.

Build a level-2 path-signature engine in pure MQL5 to read the lead-lag ordering between two data streams without choosing a lag and without a linear model. The article delivers a reusable library, an indicator that plots the Levy‑area oscillator, and a simple rule‑based Expert Advisor. Code is cross‑checked against closed‑form cases, and the components are ready to plug into your projects.

The article provides a practical research setup for weekend gap analysis: MQL5 extracts precise pip‑based gaps and tracks fills, while Python performs statistical testing and visualization. You will compute fill rates by gap buckets, model fill probability with logistic regression, and assess time-to-fill via Kaplan–Meier curves. All steps are configurable and reproducible for EURUSD, GBPUSD, USDJPY and beyond.

We extend the supply and demand framework with a strategy layer that converts zone interactions into decisions. Qualified zones pass sequential checks for interaction proximity, approach behavior, higher‑timeframe alignment, and price action before execution is handed to a dedicated trade manager. This architecture improves control, maintainability, and future extensibility without changing the underlying zone engine.

The article provides a fascinating look at how SwiGLU embedding reveals hidden market patterns, and how a sparse Mixture of Experts within a Decoder-Only Transformer makes forecasts more accurate at reasonable computational cost. We take an in-depth look at the integration of Time‑MoE into MQL5 and OpenCL, and provide a step-by-step guide to configuring and training the model.

We continue enhancing our modular indicator search panel by adding symbol selection capabilities. The implementation allows users to search for built-in indicators, choose a destination symbol, and attach the selected indicator without opening multiple charts or running separate Expert Advisor instances.