Neural networks made easy (Part 46): Goal-conditioned reinforcement learning (GCRL)
In this article, we will have a look at yet another reinforcement learning approach. It is called goal-conditioned reinforcement learning (GCRL). In this approach, an agent is trained to achieve different goals in specific scenarios.
MQL5 Wizard Techniques you should know (Part 16): Principal Component Analysis with Eigen Vectors
Principal Component Analysis, a dimensionality reducing technique in data analysis, is looked at in this article, with how it could be implemented with Eigen values and vectors. As always, we aim to develop a prototype expert-signal-class usable in the MQL5 wizard.
Polynomial models in trading
This article is about orthogonal polynomials. Their use can become the basis for a more accurate and effective analysis of market information allowing traders to make more informed decisions.
Developing a multi-currency Expert Advisor (Part 6): Automating the selection of an instance group
After optimizing the trading strategy, we receive sets of parameters. We can use them to create several instances of trading strategies combined in one EA. Previously, we did this manually. Here we will try to automate this process.
DoEasy. Controls (Part 12): Base list object, ListBox and ButtonListBox WinForms objects
In this article, I am going to create the base object of WinForms object lists, as well as the two new objects: ListBox and ButtonListBox.
Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging
In this article, we will enhance the responsiveness of the Admin Panel that we previously created. Additionally, we will explore the significance of quick messaging in the context of trading signals.
Artificial Electric Field Algorithm (AEFA)
The article presents an artificial electric field algorithm (AEFA) inspired by Coulomb's law of electrostatic force. The algorithm simulates electrical phenomena to solve complex optimization problems using charged particles and their interactions. AEFA exhibits unique properties in the context of other algorithms related to laws of nature.
Developing a Replay System (Part 26): Expert Advisor project — C_Terminal class
We can now start creating an Expert Advisor for use in the replay/simulation system. However, we need something improved, not a random solution. Despite this, we should not be intimidated by the initial complexity. It's important to start somewhere, otherwise we end up ruminating about the difficulty of a task without even trying to overcome it. That's what programming is all about: overcoming obstacles through learning, testing, and extensive research.
Reimagining Classic Strategies (Part V): Multiple Symbol Analysis on USDZAR
In this series of articles, we revisit classical strategies to see if we can improve the strategy using AI. In today's article, we will examine a popular strategy of multiple symbol analysis using a basket of correlated securities, we will focus on the exotic USDZAR currency pair.
Self Optimizing Expert Advisors in MQL5 (Part 16): Supervised Linear System Identification
Linear system identifcation may be coupled to learn to correct the error in a supervised learning algorithm. This allows us to build applications that depend on statistical modelling techniques without necessarily inheriting the fragility of the model's restrictive assumptions. Classical supervised learning algorithms have many needs that may be supplemented by pairing these models with a feedback controller that can correct the model to keep up with current market conditions.
Price Action Analysis Toolkit Development (Part 37): Sentiment Tilt Meter
Market sentiment is one of the most overlooked yet powerful forces influencing price movement. While most traders rely on lagging indicators or guesswork, the Sentiment Tilt Meter (STM) EA transforms raw market data into clear, visual guidance, showing whether the market is leaning bullish, bearish, or staying neutral in real-time. This makes it easier to confirm trades, avoid false entries, and time market participation more effectively.
Interview with Andrei Moraru (ATC 2011)
Ukrainian programmer Andrei Moraru (enivid) is an active participant of the Automated Trading Championship beginning from 2007. Andrei had already come in our view at that time and now we have decided to find out if there occured any changes in his attitude towards trading and selection of trading strategies for the past four years, and also to know about his new Expert Advisor.
Price Action Analysis Toolkit Development (Part 37): Sentiment Tilt Meter
Market sentiment is one of the most overlooked yet powerful forces influencing price movement. While most traders rely on lagging indicators or guesswork, the Sentiment Tilt Meter (STM) EA transforms raw market data into clear, visual guidance, showing whether the market is leaning bullish, bearish, or staying neutral in real-time. This makes it easier to confirm trades, avoid false entries, and time market participation more effectively.
Risk-Based Trade Placement EA with On-Chart UI (Part 2): Adding Interactivity and Logic
Learn how to build an interactive MQL5 Expert Advisor with an on-chart control panel. Know how to compute risk-based lot sizes and place trades directly from the chart.
Trading with the MQL5 Economic Calendar (Part 10): Draggable Dashboard and Interactive Hover Effects for Seamless News Navigation
In this article, we enhance the MQL5 Economic Calendar by introducing a draggable dashboard that allows us to reposition the interface for better chart visibility. We implement hover effects for buttons to improve interactivity and ensure seamless navigation with a dynamically positioned scrollbar.
Creating an MQL5-Telegram Integrated Expert Advisor (Part 7): Command Analysis for Indicator Automation on Charts
In this article, we explore how to integrate Telegram commands with MQL5 to automate the addition of indicators on trading charts. We cover the process of parsing user commands, executing them in MQL5, and testing the system to ensure smooth indicator-based trading
Neural networks made easy (Part 78): Decoder-free Object Detector with Transformer (DFFT)
In this article, I propose to look at the issue of building a trading strategy from a different angle. We will not predict future price movements, but will try to build a trading system based on the analysis of historical data.
MetaTrader tick info access from MQL5 services to Python application using sockets
Sometimes everything is not programmable in the MQL5 language. And even if it is possible to convert existing advanced libraries in MQL5, it would be time-consuming. This article tries to show that we can bypass Windows OS dependency by transporting tick information such as bid, ask and time with MetaTrader services to a Python application using sockets.
Developing an MQL5 Reinforcement Learning agent with RestAPI integration (Part 1): How to use RestAPIs in MQL5
In this article we will talk about the importance of APIs (Application Programming Interface) for interaction between different applications and software systems. We will see the role of APIs in simplifying interactions between applications, allowing them to efficiently share data and functionality.
From Basic to Intermediate: SWITCH Statement
In this article, we will learn how to use the SWITCH statement in its simplest and most basic form. 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.
Market Simulation (Part 20): First steps with SQL (III)
Although we can perform operations on a database containing about 10 records, the material is absorbed much better when we work with a file that contains more than 15 thousand records. That is, if we tried to create such a database manually, this task would be enormous. However, it is difficult to find such a database, even for educational purposes, that is available for download. But in reality, we don’t need to resort to that — we can use MetaTrader 5 to create a database for ourselves. In today's article, we will look at how to do this.
Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)
This part of the article series is dedicated to integrating WhatsApp with MetaTrader 5 for notifications. We have included a flow chart to simplify understanding and will discuss the importance of security measures in integration. The primary purpose of indicators is to simplify analysis through automation, and they should include notification methods for alerting users when specific conditions are met. Discover more in this article.
Category Theory in MQL5 (Part 5): Equalizers
Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.
Neural Network in Practice: The First Neuron
In this article, we'll start building something simple and humble: a neuron. We will program it with a very small amount of MQL5 code. The neuron worked great in my tests. Let's go back a bit in this series of articles about neural networks to understand what I'm talking about.
MQL5 Wizard Techniques you should know (Part 57): Supervised Learning with Moving Average and Stochastic Oscillator
Moving Average and Stochastic Oscillator are very common indicators that some traders may not use a lot because of their lagging nature. In a 3-part ‘miniseries' that considers the 3 main forms of machine learning, we look to see if this bias against these indicators is justified, or they might be holding an edge. We do our examination in wizard assembled Expert Advisors.
From Matrices to Models: How to Build an ML Pipeline in MQL5 and Export It to ONNX
The article describes the arrangement of a coordinated ML pipeline in MetaTrader 5 with separation of roles: Python trains and exports the model to ONNX, MQL5 reproduces normalization and PCA via matrix/vector and performs inference. This approach makes the model's inputs stable and verifiable, and the MetaTrader 5 strategy tester provides metrics for analyzing the system behavior.
Developing a Replay System — Market simulation (Part 09): Custom events
Here we'll see how custom events are triggered and how the indicator reports the state of the replay/simulation service.
Developing a Replay System — Market simulation (Part 11): Birth of the SIMULATOR (I)
In order to use the data that forms the bars, we must abandon replay and start developing a simulator. We will use 1 minute bars because they offer the least amount of difficulty.
Category Theory in MQL5 (Part 22): A different look at Moving Averages
In this article we attempt to simplify our illustration of concepts covered in these series by dwelling on just one indicator, the most common and probably the easiest to understand. The moving average. In doing so we consider significance and possible applications of vertical natural transformations.
Neural networks made easy (Part 45): Training state exploration skills
Training useful skills without an explicit reward function is one of the main challenges in hierarchical reinforcement learning. Previously, we already got acquainted with two algorithms for solving this problem. But the question of the completeness of environmental research remains open. This article demonstrates a different approach to skill training, the use of which directly depends on the current state of the system.
Population ADAM (Adaptive Moment Estimation)
The article presents the transformation of the well-known and popular ADAM gradient optimization method into a population algorithm and its modification with the introduction of hybrid individuals. The new approach allows creating agents that combine elements of successful decisions using probability distribution. The key innovation is the formation of hybrid population individuals that adaptively accumulate information from the most promising solutions, increasing the efficiency of search in complex multidimensional spaces.
Developing a multi-currency Expert Advisor (Part 15): Preparing EA for real trading
As we gradually approach to obtaining a ready-made EA, we need to pay attention to issues that seem secondary at the stage of testing a trading strategy, but become important when moving on to real trading.
Developing a Replay System — Market simulation (Part 14): Birth of the SIMULATOR (IV)
In this article we will continue the simulator development stage. this time we will see how to effectively create a RANDOM WALK type movement. This type of movement is very intriguing because it forms the basis of everything that happens in the capital market. In addition, we will begin to understand some concepts that are fundamental to those conducting market analysis.
Mastering Log Records (Part 1): Fundamental Concepts and First Steps in MQL5
Welcome to the beginning of another journey! This article opens a special series where we will create, step by step, a library for log manipulation, tailored for those who develop in the MQL5 language.
Custom Debugging and Profiling Tools for MQL5 Development (Part I): Advanced Logging
Learn how to implement a powerful custom logging framework for MQL5 that goes beyond simple Print() statements by supporting severity levels, multiple output handlers, and automated file rotation—all configurable on‐the‐fly. Integrate the singleton CLogger with ConsoleLogHandler and FileLogHandler to capture contextual, timestamped logs in both the Experts tab and persistent files. Streamline debugging and performance tracing in your Expert Advisors with clear, customizable log formats and centralized control.
Atomic Orbital Search (AOS) algorithm
The article considers the Atomic Orbital Search (AOS) algorithm, which uses the concepts of the atomic orbital model to simulate the search for solutions. The algorithm is based on probability distributions and the dynamics of interactions in the atom. The article discusses in detail the mathematical aspects of AOS, including updating the positions of candidate solutions and the mechanisms of energy absorption and release. AOS opens new horizons for applying quantum principles to computing problems by offering an innovative approach to optimization.
MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring
In this article, we develop a rolling ticker tape in MQL5 for real-time monitoring of multiple symbols, displaying bid prices, spreads, and daily percentage changes with scrolling effects. We implement customizable fonts, colors, and scroll speeds to highlight price movements and trends effectively.
Building a Volume Bubble Indicator in MQL5 Using Standard Deviation
The article demonstrates how to build a Volume Bubble Indicator in MQL5 that visualizes market activity using statistical normalization. It covers how to work with tick and real volume, compute the mean and standard deviation over a rolling window, and normalize volume values to identify relative strength. You will implement chart objects to display bubbles with dynamic size and color, providing a clear representation of volume intensity directly on the chart.
Atomic Orbital Search (AOS) algorithm
The article considers the Atomic Orbital Search (AOS) algorithm, which uses the concepts of the atomic orbital model to simulate the search for solutions. The algorithm is based on probability distributions and the dynamics of interactions in the atom. The article discusses in detail the mathematical aspects of AOS, including updating the positions of candidate solutions and the mechanisms of energy absorption and release. AOS opens new horizons for applying quantum principles to computing problems by offering an innovative approach to optimization.
MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring
In this article, we develop a rolling ticker tape in MQL5 for real-time monitoring of multiple symbols, displaying bid prices, spreads, and daily percentage changes with scrolling effects. We implement customizable fonts, colors, and scroll speeds to highlight price movements and trends effectively.