MQL4 and MQL5 Programming Articles

The article presents an innovative quantum neural network architecture for algorithmic trading that combines the principles of quantum mechanics with modern machine learning methods. The system includes quantum effects (resonance, interference, decoherence), multi-level memory of different time scales, Markov chains with the ALGLIB library, and adaptive parameter control. The full implementation is done in MQL5 using the built-in matrix/vector types, which removes implementation barriers in MetaTrader 5.

This article introduces a frequency-analysis framework for encoded candlestick patterns in MQL5. By transforming candlesticks into alphabetic symbols, historical price action can be analyzed as a statistical sequence rather than a visual chart. Using GBPUSD and Gold across multiple timeframes, the study examines the occurrence frequency of individual candlestick types, identifies dominant market structures, and reveals the symmetry between bullish and bearish price movements. The results establish a quantitative foundation for pattern discovery and prepare the way for analyzing multi-candlestick sequences and their predictive potential in algorithmic trading systems.

This article presents a compact MQL5 utility layer for routine trade operations. It includes position existence checkers, position counters, bulk close helpers, and functions to retrieve the most recent or oldest position by symbol, magic, or type. A simple SMA crossover Expert Advisor demonstrates integration. The result is cleaner EAs, fewer inconsistencies across projects, and faster maintenance.

The article explains how to develop a tool for analyzing recurring price patterns in financial markets — by day of the month (1-31), day of the week (Monday-Sunday), or hour of the day (0-23). The indicator analyzes historical data, calculates the average return for each period, and displays the results as a histogram with a forecast. It includes customizable parameters: seasonality type, number of bars analyzed, display as percentages or absolute values, chart colors.

Building a purchasing power parity (PPP)-based exchange rate analysis system using Python. The author developed an algorithm with 5 methods for calculating fair exchange rates using IMF data. A practical guide to fundamental currency analysis, economic data processing, and integration with trading systems. Full code in open source.

Implementation of the N-BEATS architecture for Forex trading in MetaTrader 5 with quantile forecasting and adaptive risk management. The architecture is adapted through bilinear normalization and specialized loss functions for financial data. Backtesting on 2025 data shows inability to generate profits, confirming the gap between theoretical achievements and practical trading performance.

The article presents a detailed analysis of the Exchange Market Algorithm (EMA) inspired by the behavior of stock market traders. The algorithm simulates stock trading, where market participants with varying levels of success employ different strategies to maximize profits.

In this article, we expand our butterfly animation program with a four-stage animation pipeline: sequential curve drawing, smooth wing fill fading, detailed body rendering, and continuous flight. We implement a timer-driven state machine, four oscillators for wing flapping, vertical bobbing, horizontal sway, and tilt, as well as a neon glow around the wing outlines and a cyclical color change based on hue. You will learn how to structure these effects on the MetaTrader 5 canvas for clean and controlled playback.

The article explores the possibility of using regression models in algorithmic trading. Regression models, unlike binary classification, allow for the creation of more flexible trading strategies by quantifying predicted price changes.

In this article, we explored the concept of body in HTTP requests, which is essential for sending data such as JSON and plain text. We discussed and explained how to use it correctly with the appropriate headers. We also introduced the ChttpBody class, part of the Connexus library, which will simplify working with the body of requests.

In this final installment of our Connexus library series, we explored the implementation of the Observer pattern, as well as essential refactorings to file paths and method names. This series covered the entire development of Connexus, designed to simplify HTTP communication in complex applications.

Create a CSV trading journal in MQL5 by reading account history over a defined period and writing structured records to file. The article explains deal counting, ticket retrieval, symbol and order type decoding, and capturing entry (lot, time, price, SL/TP) and exit (time, price, profit, result) data with dynamic arrays. The result is an organized, persistent log suitable for analysis and reporting.

In today's article, we will show how to approach solving problems related to structuring different elements and creating simpler and more attractive solutions. Although the content is oriented toward learning and, therefore, does not constitute production code, it is essential to thoroughly understand the concepts and knowledge that will be covered here. In this way, in the future we will be able to follow the codes we will present.

In this article, you will learn how to create an interactive control panel in MetaTrader 5. We cover the basics of adding input fields, action buttons, and labels to display text. Using a project-based approach, you will see how to set up a panel where users can type messages and eventually display server responses from an API.

For this article we switch to a custom MQL5 Wizard class implementation that explores Money Management. We are labelling our custom class ‘CMoneySuffixAE’ that we derive by combining the Suffix Automaton algorithm with an Autoencoder neural network. As always, this formulation is testable with MQL5 Wizard Assembled Expert Advisors that can be tuned with various entry signals and trailing stop approaches.