MQL4 and MQL5 Programming Articles

It's the second time Matúš German participates in the Automated Trading Championship. By the end of the fourth week of ATC 2012 his Expert Advisor has been holding its positions in the TOP-10 having about $30 000. Matúš is from Slovakia, from the little town Bardejov. Matúš is interested in trading for about 5 years and he develops Expert Advisors for 3 years already.

In this article, I will fix the names of WinForms object class methods and create Button and RadioButton WinForms objects.

In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.

In the previous article, I implemented the ability to move pivot points of an extended graphical object using control forms. Now I am going to implement the ability to move a composite graphical object using a single graphical object control point (form).

Machine learning has become a popular method for strategy development. Whilst there has been more emphasis on maximizing profitability and prediction accuracy , the importance of processing the data used to build predictive models has not received a lot of attention. In this article we consider using the concept of entropy to evaluate the appropriateness of indicators to be used in predictive model building as documented in the book Testing and Tuning Market Trading Systems by Timothy Masters.

This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?

Numerous attempts to apply statistical methods to the objective reality, i.e. to financial series, crash when met with the nonstationarity of processes, "fat tails" of accompanying probability distributions, and insufficient volume of financial data.In this publication I will try to refer not to the financial series as such, but to their subjective presentation - in this case, to the way a trader tries to halter the series, i.e. to the trading system. The eduction of statistical regularities of the trading results process is a rather enthralling task. In some cases quite true conclusions about the model of this process can be made, and these can be applied to the trading system.

In the article, I will create the class of the standard graphical object memory allowing the object to save its states when its properties are modified. In turn, this allows retracting to the previous graphical object states.

A new article from Design Patterns articles and we will take a look at one of its types which is behavioral patterns to understand how we can build communication methods between created objects effectively. By completing these Behavior patterns we will be able to understand how we can create and build a reusable, extendable, tested software.

Contrastive training is an unsupervised method of training representation. Its goal is to train a model to highlight similarities and differences in data sets. In this article, we will talk about using contrastive training approaches to explore different Actor skills.

In this article, I will implement handling Padding (internal indents/margin on all sides of an element) and Dock parameters (the way an object is located inside its container).

This article presents CSwingEngine, a reusable MQL5 class that detects H4 swing highs and lows, labels them HH, LH, HL, or LL, and classifies market structure as trend or range. Swings are always computed on H4, regardless of the attached chart, and each point draws correctly on lower timeframes via native datetime anchoring. The engine exposes a clean interface to query the current trend and retrieve the swing array for context-aware pattern logic.

Enhance your MQL5 code by optimizing logic, refining calculations, and reducing execution time to improve back-test accuracy. Fine-tune parameters, optimize loops, and eliminate inefficiencies for better performance.

GridSearchCV and RandomizedSearchCV share a fundamental limitation in financial ML: each trial is independent, so search quality does not improve with additional compute. This article integrates Optuna — using the Tree-structured Parzen Estimator — with PurgedKFold cross-validation, HyperbandPruner early stopping, and a dual-weight convention that separates training weights from evaluation weights. The result is a five-component system: an objective function with fold-level pruning, a suggestion layer that optimizes the weighting scheme jointly with model hyperparameters, a financially-calibrated pruner, a resumable SQLite-backed orchestrator, and a converter to scikit-learn cv_results_ format. The article also establishes the boundary — drawn from Timothy Masters — between statistical objectives where directed search is beneficial and financial objectives where it is harmful.

The article considers creation of 'GroupBox' and 'CheckBox' WinForms objects, as well as the development of base objects for WinForms object categories. All created objects are still static, i.e. they are unable to interact with the mouse.

The Ichimoku-Kinko-Hyo Indicator and the ADX-Wilder oscillator are a pairing that could be used in complimentarily within an MQL5 Expert Advisor. The Ichimoku is multi-faceted, however for this article, we are relying on it primarily for its ability to define support and resistance levels. Meanwhile, we also use the ADX to define our trend. As usual, we use the MQL5 wizard to build and test any potential these two may possess.

When working on projects in MetaEditor, developers often face the need to manage code versions. MetaQuotes recently announced migration to GIT and the launch of MQL5 Algo Forge with code versioning and collaboration capabilities. In this article, we will discuss how to use the new and previously existing tools more efficiently.

In this article the author offers ways to improve trading systems described in his previous articles. The article will be interesting for traders that already have some experience of writing Expert Advisors.

Machine learning models come with various adjustable parameters. In this series of articles, we will explore how to customize your AI models to fit your specific market using the SciPy library.