MQL4 and 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 made easy (Part 80): Graph Transformer Generative Adversarial Model (GTGAN)
In this article, I will get acquainted with the GTGAN algorithm, which was introduced in January 2024 to solve complex problems of generation architectural layouts with graph constraints.
Building the Market Structure Sentinel Indicator in MQL5
This article builds a Market Structure Sentinel indicator in MQL5 that detects and visualizes Smart Money Concepts (SMC) events, including Break of Structure (BOS) and Change of Character (CHOCH), in real time. It explains swing detection, structural validation, and trend classification, and adds a compact dashboard to track bullish, bearish, or ranging states for faster on‑chart interpretation.
From Basic to Intermediate: Array (I)
This article is a transition between what has been discussed so far and a new stage of research. To understand this article, you need to read the previous ones. The content presented here is intended solely for educational purposes. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
Building AI-Powered Trading Systems in MQL5 (Part 5): Adding a Collapsible Sidebar with Chat Popups
In Part 5 of our MQL5 AI trading system series, we enhance the ChatGPT-integrated Expert Advisor by introducing a collapsible sidebar, improving navigation with small and large history popups for seamless chat selection, while maintaining multiline input handling, persistent encrypted chat storage, and AI-driven trade signal generation from chart data.
Implementing Practical Modules from Other Languages in MQL5 (Part 02): Building the REQUESTS Library, Inspired by Python
In this article, we implement a module similar to requests offered in Python to make it easier to send and receive web requests in MetaTrader 5 using MQL5.
Fractal-Based Algorithm (FBA)
The article presents a new metaheuristic method based on a fractal approach to partitioning the search space for solving optimization problems. The algorithm sequentially identifies and separates promising areas, creating a self-similar fractal structure that concentrates computing resources on the most promising areas. A unique mutation mechanism aimed at better solutions ensures an optimal balance between exploration and exploitation of the search space, significantly increasing the efficiency of the algorithm.
Implementing the Truncated Newton Conjugate-Gradient Algorithm in MQL5
This article implements a box‑constrained Truncated Newton Conjugate‑Gradient (TNC) optimizer in MQL5 and details its core components: scaling, projection to bounds, line search, and Hessian‑vector products via finite differences. It provides an objective wrapper supporting analytic or numerical derivatives and validates the solver on the Rosenbrock benchmark. A logistic regression example shows how to use TNC as a drop‑in alternative to LBFGS.
Trading with the MQL5 Economic Calendar (Part 5): Enhancing the Dashboard with Responsive Controls and Filter Buttons
In this article, we create buttons for currency pair filters, importance levels, time filters, and a cancel option to improve dashboard control. These buttons are programmed to respond dynamically to user actions, allowing seamless interaction. We also automate their behavior to reflect real-time changes on the dashboard. This enhances the overall functionality, mobility, and responsiveness of the panel.
MQL5 Wizard Techniques you should know (Part 64): Using Patterns of DeMarker and Envelope Channels with the White-Noise Kernel
The DeMarker Oscillator and the Envelopes' indicator are momentum and support/ resistance tools that can be paired when developing an Expert Advisor. We continue from our last article that introduced these pair of indicators by adding machine learning to the mix. We are using a recurrent neural network that uses the white-noise kernel to process vectorized signals from these two indicators. This is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
Developing a Replay System — Market simulation (Part 17): Ticks and more ticks (I)
Here we will see how to implement something really interesting, but at the same time very difficult due to certain points that can be very confusing. The worst thing that can happen is that some traders who consider themselves professionals do not know anything about the importance of these concepts in the capital market. Well, although we focus here on programming, understanding some of the issues involved in market trading is paramount to what we are going to implement.
Neural Networks in Trading: Practical Results of the TEMPO Method
We continue our acquaintance with the TEMPO method. In this article we will evaluate the actual effectiveness of the proposed approaches on real historical data.
Self Optimizing Expert Advisors in MQL5 (Part 10): Matrix Factorization
Factorization is a mathematical process used to gain insights into the attributes of data. When we apply factorization to large sets of market data — organized in rows and columns — we can uncover patterns and characteristics of the market. Factorization is a powerful tool, and this article will show how you can use it within the MetaTrader 5 terminal, through the MQL5 API, to gain more profound insights into your market data.
Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (IV): Trade Management Panel class
This discussion covers the updated TradeManagementPanel in our New_Admin_Panel EA. The update enhances the panel by using built-in classes to offer a user-friendly trade management interface. It includes trading buttons for opening positions and controls for managing existing trades and pending orders. A key feature is the integrated risk management that allows setting stop loss and take profit values directly in the interface. This update improves code organization for large programs and simplifies access to order management tools, which are often complex in the terminal.
Brain Storm Optimization algorithm (Part II): Multimodality
In the second part of the article, we will move on to the practical implementation of the BSO algorithm, conduct tests on test functions and compare the efficiency of BSO with other optimization methods.
Using the MQL5 Economic Calendar for News Filtering (Part 2): Stop Management Positions During News Releases
In part 2, we extend the news filter to protect existing positions during news events. Instead of closing trades, we temporarily remove stop-loss and take-profit levels, storing them safely in memory. When the news window ends, stops are deterministically restored, adjusted if price has already crossed the original levels, while respecting broker minimum distance rules. The result is a mechanism that preserves trade integrity without interfering with entry logic, keeping the EA in control through volatility.
Automating Market Memory Zones Indicator: Where Price is Likely to Return
This article turns Market Memory Zones from a chart-only concept into a complete MQL5 Expert Advisor. It automates Displacement, Structure Transition (CHoCH), and Liquidity Sweep zones using ATR- and candle-structure filters, applies lower-timeframe confirmation, and enforces risk-based position sizing with dynamic SL and structure-based TP. You will get the code architecture for detection, entries, trade management, and visualization, plus a brief backtest review.
Data Science and ML (Part 32): Keeping your AI models updated, Online Learning
In the ever-changing world of trading, adapting to market shifts is not just a choice—it's a necessity. New patterns and trends emerge everyday, making it harder even the most advanced machine learning models to stay effective in the face of evolving conditions. In this article, we’ll explore how to keep your models relevant and responsive to new market data by automatically retraining.
Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects
Let's explore how you can start integrating external code from any repository in the MQL5 Algo Forge storage into your own project. In this article, we finally turn to this promising, yet more complex, task: how to practically connect and use libraries from third-party repositories within MQL5 Algo Forge.
From Novice to Expert: Revealing the Candlestick Shadows (Wicks)
In this discussion, we take a step forward to uncover the underlying price action hidden within candlestick wicks. By integrating a wick visualization feature into the Market Periods Synchronizer, we enhance the tool with greater analytical depth and interactivity. This upgraded system allows traders to visualize higher-timeframe price rejections directly on lower-timeframe charts, revealing detailed structures that were once concealed within the shadows.
Developing a Replay System (Part 27): Expert Advisor project — C_Mouse class (I)
In this article we will implement the C_Mouse class. It provides the ability to program at the highest level. However, talking about high-level or low-level programming languages is not about including obscene words or jargon in the code. It's the other way around. When we talk about high-level or low-level programming, we mean how easy or difficult the code is for other programmers to understand.
Alexander Anufrenko: "A danger foreseen is half avoided" (ATC 2010)
The risky development of Alexander Anufrenko (Anufrenko321) had been featured among the top three of the Championship for three weeks. Having suffered a catastrophic Stop Loss last week, his Expert Advisor lost about $60,000, but now once again he is approaching the leaders. In this interview the author of this interesting EA is describing the operating principles and characteristics of his application.
Statistical Arbitrage Through Cointegrated Stocks (Part 6): Scoring System
In this article, we propose a scoring system for mean-reversion strategies based on statistical arbitrage of cointegrated stocks. The article suggests criteria that go from liquidity and transaction costs to the number of cointegration ranks and time to mean-reversion, while taking into account the strategic criteria of data frequency (timeframe) and the lookback period for cointegration tests, which are evaluated before the score ranking properly. The files required for the reproduction of the backtest are provided, and their results are commented on as well.
Building AI-Powered Trading Systems in MQL5 (Part 8): UI Polish with Animations, Timing Metrics, and Response Management Tools
In this article, we enhance the AI-powered trading system in MQL5 with user interface improvements, including loading animations for request preparation and thinking phases, as well as timing metrics displayed in responses for better feedback. We add response management tools like regenerate buttons to re-query the AI and export options to save the last response to a file, streamlining interaction.
Population optimization algorithms: Binary Genetic Algorithm (BGA). Part II
In this article, we will look at the binary genetic algorithm (BGA), which models the natural processes that occur in the genetic material of living things in nature.
Andrey Bolkonsky (abolk): "Any programmer knows that there is no software without bugs"
Andrey Bolkonsky (abolk) has been participating in the Jobs service since its opening. He has developed dozens of indicators and Expert Advisors for the MetaTrader 4 and MetaTrader 5 platforms. We will talk with Andrey about what a server is from the perspective of a programmer.
A New Approach to Custom Criteria in Optimizations (Part 1): Examples of Activation Functions
The first of a series of articles looking at the mathematics of Custom Criteria with a specific focus on non-linear functions used in Neural Networks, MQL5 code for implementation and the use of targeted and correctional offsets.
Black Hole Algorithm (BHA)
The Black Hole Algorithm (BHA) uses the principles of black hole gravity to optimize solutions. In this article, we will look at how BHA attracts the best solutions while avoiding local extremes, and why this algorithm has become a powerful tool for solving complex problems. Learn how simple ideas can lead to impressive results in the world of optimization.
Dimitar Manov: "I fear only extraordinary situations in the Championship" (ATC 2010)
In the recent review by Boris Odintsov the Expert Advisor of the Bulgarian Participant Dimitar Manov appeared among the most stable and reliable EAs. We decided to interview this developer and try to find the secret of his success. In this interview Dimitar has told us what situation would be unfavorable for his robot, why he's not using indicators and whether he is expecting to win the competition.
Price movement discretization methods in Python
We will look at price discretization methods using Python + MQL5. In this article, I will share my practical experience developing a Python library that implements a wide range of approaches to bar formation — from classic Volume and Range bars to more exotic methods like Renko and Kagi. We will consider three-line breakout candles and range bars analyzing their statistics and trying to define how else the prices can be represented discretely.
Interview with Valery Mazurenko (ATC 2011)
The task of writing an Expert Advisor trading on multiple currency pairs is complex both in terms of finding suitable strategies and from the technological side. But if the goal is set clear, nothing is impossible then. It was four times already that Vitaly Mazurenko (notused) submitted his multi-currency Expert Advisor. It seems, he has managed to find the right way this time.
Creating a Trading Administrator Panel in MQL5 (Part V): Two-Factor Authentication (2FA)
Today, we will discuss enhancing security for the Trading Administrator Panel currently under development. We will explore how to implement MQL5 in a new security strategy, integrating the Telegram API for two-factor authentication (2FA). This discussion will provide valuable insights into the application of MQL5 in reinforcing security measures. Additionally, we will examine the MathRand function, focusing on its functionality and how it can be effectively utilized within our security framework. Continue reading to discover more!
Data Science and ML (Part 38): AI Transfer Learning in Forex Markets
The AI breakthroughs dominating headlines, from ChatGPT to self-driving cars, aren’t built from isolated models but through cumulative knowledge transferred from various models or common fields. Now, this same "learn once, apply everywhere" approach can be applied to help us transform our AI models in algorithmic trading. In this article, we are going to learn how we can leverage the information gained across various instruments to help in improving predictions on others using transfer learning.
Time series clustering in causal inference
Clustering algorithms in machine learning are important unsupervised learning algorithms that can divide the original data into groups with similar observations. By using these groups, you can analyze the market for a specific cluster, search for the most stable clusters using new data, and make causal inferences. The article proposes an original method for time series clustering in Python.
Neural Networks in Trading: Memory Augmented Context-Aware Learning (MacroHFT) for Cryptocurrency Markets
I invite you to explore the MacroHFT framework, which applies context-aware reinforcement learning and memory to improve high-frequency cryptocurrency trading decisions using macroeconomic data and adaptive agents.
Data label for time series mining (Part 6)：Apply and Test in EA Using ONNX
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
Price Action Analysis Toolkit Development (Part 22): Correlation Dashboard
This tool is a Correlation Dashboard that calculates and displays real-time correlation coefficients across multiple currency pairs. By visualizing how pairs move in relation to one another, it adds valuable context to your price-action analysis and helps you anticipate inter-market dynamics. Read on to explore its features and applications.
Python-MetaTrader 5 Strategy Tester (Part 04): Tester 101
In this fascinating article, we build our very first trading robot in the simulator and run a strategy testing action that resembles how the MetaTrader 5 strategy tester works, then compare the outcome produced in a custom simulation against our favorite terminal.
Neural Networks in Trading: Dual-Attention-Based Trend Prediction Model
We continue the discussion about the use of piecewise linear representation of time series, which was started in the previous article. Today we will see how to combine this method with other approaches to time series analysis to improve the price trend prediction quality.
Creating Custom Indicators in MQL5 (Part 11): Enhancing the Footprint Chart with Market Structure and Order Flow Layers
This article extends the MQL5 footprint chart with market-structure and order-flow layers: volume-profile bars, point of control, value-area highlighting, stacked imbalance detection, absorption zones, and single-print/unfinished markers. We expand bar data structures, add functions for POC/value area, imbalance, and absorption, and build a fixed-order rendering pipeline. You will get ready-to-use inputs, metadata, and drawing utilities to integrate and customize these layers in your indicator.
Category Theory in MQL5 (Part 13): Calendar Events with Database Schemas
This article, that follows Category Theory implementation of Orders in MQL5, considers how database schemas can be incorporated for classification in MQL5. We take an introductory look at how database schema concepts could be married with category theory when identifying trade relevant text(string) information. Calendar events are the focus.