MQL4 and MQL5 Programming Articles

The article examines the quality of a seasonal trading approach on a daily timeframe, both for individual symbols and for spreads. Particular attention is paid to identifying recurring monthly cycles and the possibilities of their application in trading within the current year.

This article explains how to implement parameter versioning in MQL5 using binary files and packed structures. It shows how to write and read fixed-size records with FileWriteStruct and FileReadStruct in FILE_BIN mode, including version numbers, timestamps, and a checksum. You will also see how to detect changes via checksums, append records safely, and load the latest configuration without overwriting prior settings.

The article extends our copula toolkit with mixed copulas implemented natively in MQL5. We construct Clayton–Frank–Gumbel and Clayton–Student–t–Gumbel mixtures, estimate them via EM, and enable sparsity control through SCAD with cross‑validation. Provided scripts tune hyperparameters, compare mixtures using information criteria, and save trained models. Practitioners can apply these components to capture asymmetric tail dependence and embed the selected model in indicators or Expert Advisors.

Integrating Python's logging module with MQL5 empowers traders with a systematic logging approach, simplifying the process of monitoring, debugging, and documenting trading activities. This article explains the adaptation process, offering traders a powerful tool for maintaining clarity and organization in trading software development.

In this article, we will continue diving into the implementation of the ACMO (Atmospheric Cloud Model Optimization) algorithm. In particular, we will discuss two key aspects: the movement of clouds into low-pressure regions and the rain simulation, including the initialization of droplets and their distribution among clouds. We will also look at other methods that play an important role in managing the state of clouds and ensuring their interaction with the environment.

From ChatGPT to Gemini and many model AI tools for text, image, and video generation. Transformers have rocked the AI-world. But, are they applicable in the financial (trading) space? Let's find out.

In this article, we look to explore how a complimentary indicator pairing can be used to analyze the recent 5-year history of Vanguard Information Technology Index Fund ETF. By considering two options of algorithms, Kendall’s Tau and Distance-Correlation, we look to select not just an ideal indicator pair for trading the VGT, but also suitable signal-pattern pairings of these two indicators.

We continue dwelling on the topic of social behavior of living organisms and its impact on the development of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will dive into the two-phase evolution, test the algorithm and draw conclusions. Just as in nature a group of living organisms join their efforts to survive, ASBO uses principles of collective behavior to solve complex optimization problems.

We continue our new series on Market-Positioning, where we study particular assets, with specific trade directions over manageable test windows. We started this by considering Nvidia Corp stock in the last article, where we covered 5 signal patterns from the complimentary pairing of the RSI and DeMarker oscillators. For this article, we cover the remaining 5 patterns and also delve into multi-pattern options that not only feature untethered combinations of all ten, but also specialized combinations of just a pair.

In this article, we will look at how to solve certain problems and issues that arise when using Python code within other programs. More specifically, we will demonstrate a common issue encountered when using Excel in conjunction with MetaTrader 5, although we will be using Python to facilitate this interaction. However, this implementation has a minor drawback. It does not occur in all cases, but only in certain specific situations. When it does happen, it is necessary to understand the cause. In today’s article, we will begin explaining how to resolve this issue.

The article explores one of the most interesting non-gradient optimization algorithms, which learns to understand the geometry of the objective function. We will focus on the classical implementation of CMA-ES with a slight modification - replacing the normal distribution with the power one. We will thoroughly examine the math behind the algorithm, as well as practical implementation, and check where CMA-ES is unbeatable and where it should be avoided.

This article adds six order-flow functions and a new OrderFlowAnalysis struct to MicroStructureFoundation.mqh: VPINOHLC, signed flow imbalance, trade intensity versus a 20-session baseline, a late-minus-early smart-money index, flow momentum, and a wrapper that outputs a confidence weight. Flow confidence is gated by noise and jump intensity from Parts 5 and 4. Calibrated on 602 NQ M1 NY sessions, it provides ready-to-use intraday flow signals with documented thresholds.

The article provides a step-by-step guide on how to migrate code from a published project into a fully-fledged MQL5 Algo Forge project. You will set up the environment and authentication in MetaEditor, create a project in Shared Projects, select the type, arrange the files, add README.md, check the encoding and build, commit the changes to Git, and open the repository publicly. The article helps to build a working structure and preserve version history for the convenience of readers.

The present article contains Weekly Reports of the ATC 2007. These materials are like snapshots, they are interesting-to-read not only during the Championship, but years later as well.