Applying Localized Feature Selection in Python and MQL5
This article explores a feature selection algorithm introduced in the paper 'Local Feature Selection for Data Classification' by Narges Armanfard et al. The algorithm is implemented in Python to build binary classifier models that can be integrated with MetaTrader 5 applications for inference.
Artificial Tribe Algorithm (ATA)
The article provides a detailed discussion of the key components and innovations of the ATA optimization algorithm, which is an evolutionary method with a unique dual behavior system that adapts depending on the situation. ATA combines individual and social learning while using crossover for explorations and migration to find solutions when stuck in local optima.
From Basic to Intermediate: Indicator (V)
In this article, we will look at how to handle user requests to change the chart plotting mode. This is necessary so that an indicator designed for the current chart plotting mode does not look strange or differ from what a MetaTrader 5 user expects.
Developing a Replay System (Part 68): Getting the Time Right (I)
Today we will continue working on getting the mouse pointer to tell us how much time is left on a bar during periods of low liquidity. Although at first glance it seems simple, in reality this task is much more difficult. This involves some obstacles that we will have to overcome. Therefore, it is important that you have a good understanding of the material in this first part of this subseries in order to understand the following parts.
Market Simulation (Part 08): Sockets (II)
How about creating something practical using sockets? In today's article, we'll start creating a mini-chat. Let's look together at how this is done - it will be very interesting. Please note that the code provided here is for educational purposes only. It should not be used for commercial purposes or in ready-made applications, as it does not provide data transfer security and the content transmitted over the socket can be accessed.
Overcoming Accessibility Challenges in MQL5 Trading Tools (Part II): Enabling EA Voice Using a Python Text-to-Speech Engine
Let's discuss how we can make our Expert Advisors speech‑capable using text‑to‑speech technology, partnering Python and MQL5. After reading this article, you will walk away with a working example of an EA that speaks dynamic market information. You will master the application of TTS, the WebRequest function, and learn how Python libraries integrate with the MQL5 language to create a truly voice‑aware trading tool.
From Basic to Intermediate: Variables (II)
Today we will look at how to work with static variables. This question often confuses many programmers, both beginners and those with some experience, because there are several recommendations that must be followed when using this mechanism. The materials presented here are intended for didactic purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
Bivariate Copulae in MQL5 (Part 1): Implementing Gaussian and Student's t-Copulae for Dependency Modeling
This is the first part of an article series presenting the implementation of bivariate copulae in MQL5. This article presents code implementing Gaussian and Student's t-copulae. It also delves into the fundamentals of statistical copulae and related topics. The code is based on the Arbitragelab Python package by Hudson and Thames.
Overcoming The Limitation of Machine Learning (Part 4): Overcoming Irreducible Error Using Multiple Forecast Horizons
Machine learning is often viewed through statistical or linear algebraic lenses, but this article emphasizes a geometric perspective of model predictions. It demonstrates that models do not truly approximate the target but rather map it onto a new coordinate system, creating an inherent misalignment that results in irreducible error. The article proposes that multi-step predictions, comparing the model’s forecasts across different horizons, offer a more effective approach than direct comparisons with the target. By applying this method to a trading model, the article demonstrates significant improvements in profitability and accuracy without changing the underlying model.
Building a Correlation-Aware Portfolio Risk Monitor in MQL5
The article quantifies correlation and portfolio risk in MetaTrader 5: from time-aligned returns to a covariance matrix, true portfolio variance against the independent-sum assumption, and position-level risk attribution. A MetaTrader 5 service runs in the background, shows the metrics on a small chart panel, and pushes alerts when risk thresholds are crossed. Source code is provided for an example script, a reusable risk engine class, and the service.
Multiple Symbol Analysis With Python And MQL5 (Part II): Principal Components Analysis For Portfolio Optimization
Managing trading account risk is a challenge for all traders. How can we develop trading applications that dynamically learn high, medium, and low-risk modes for various symbols in MetaTrader 5? By using PCA, we gain better control over portfolio variance. I’ll demonstrate how to create applications that learn these three risk modes from market data fetched from MetaTrader 5.
The MQL5 Standard Library Explorer (Part 12): Multi-Timeframe Composite-Score Dashboard
The article implements CMultiTimeframeMatrix, a reusable dashboard that maps symbols vs. timeframes and displays a numeric, colour‑coded score. The score combines trend, momentum, and volatility, updates by timer, and respects performance constraints. You will learn how to build the UI with CAppDialog/CLabel, compute metrics via CMatrixDouble, and embed the component into a thin EA for a consistent, real-time overview.
All about Automated Trading Championship: Interviews with the Participants'07
The published interviews of Championship 2007 bear the stamp of the results obtained during the preceding contest. The first Championship evoked a wide response on the internet and in printings. The leading developer of the MetaQuotes Software Corp. tells about changes made to the forthcoming Automated Trading Championship 2007. We put our questions to the developer of a well-known indicating complex ZUP, Eugeni Neumoin (nen) and spoke to an equity trader, Alexander Pozdnishev (AlexSilver).
From Basic to Intermediate: Arrays and Strings (I)
In today's article, we'll start exploring some special data types. To begin, we'll define what a string is and explain how to use some basic procedures. This will allow us to work with this type of data, which can be interesting, although sometimes a little confusing for beginners. 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.
From Basic to Intermediate: Overload
Perhaps this article will be the most confusing for novice programmers. As a matter of fact, here I will show that it is not always that all functions and procedures have unique names in the same code. Yes, we can easily use functions and procedures with the same name — and this is called overload.
All about Automated Trading Championship: Additional Materials of Championships 2006-2007
We present to you a selection of these materials that are divided into several parts. The present one contains additional materials about automated trading, Expert Advisors development, etc.
From Basic to Intermediate: Operator Precedence
This is definitely the most difficult question to be explained purely theoretically. That is why you need to practice everything that we're going to discuss here. While this may seem simple at first, the topic of operators can only be understood in practice combined with constant education.
Interactive Supply and Demand Zone Manager in MQL5 (Part II): Event-Driven Architecture and Persistent Lifecycle Logging
This article advances the stateful supply and demand zone framework for MetaTrader 5 by replacing polling with an event-driven model based on OnChartEvent(). We split synchronization into dedicated handlers for creation, modification, and deletion, and separate market logic in OnTick() from user interactions in OnChartEvent(). A persistent, append-only CSV logger records all lifecycle events, improving responsiveness, state consistency, and recoverable history for downstream analysis.
Automating Classic Market Methods in MQL5 (Part 2): Wyckoff Cause and Effect—Point and Figure Price Targets
This article builds a self-contained MQL5 Expert Advisor that completes the Wyckoff cycle: it detects accumulation/distribution with a finite state machine, enters at the last point of support/supply, and calculates exit point-and-figure counts under Wyckoff's Cause and Effect. We detail the box size from range ATR, a 1-box reversal, target validation, and a 2R fallback. Readers get runnable code without external dependencies.
Population optimization algorithms: Evolution of Social Groups (ESG)
We will consider the principle of constructing multi-population algorithms. As an example of this type of algorithm, we will have a look at the new custom algorithm - Evolution of Social Groups (ESG). We will analyze the basic concepts, population interaction mechanisms and advantages of this algorithm, as well as examine its performance in optimization problems.
From Basic to Intermediate: Arrays and Strings (III)
This article considers two aspects. First, how the standard library can convert binary values to other representations such as octal, decimal, and hexadecimal. Second, we will talk about how we can determine the width of our password based on the secret phrase, using the knowledge we have already acquired.
Implementing a Breakeven Mechanism in MQL5 (Part 2): ATR- and RRR-Based Breakeven
This article completes the implementation of ATR- and RRRR-based breakeven mechanisms in MQL5 and develops, from scratch, a class that makes it easy to switch breakeven modes without having to enter the parameters again. To evaluate the effectiveness of each breakeven type, several backtests are run, analyzing their advantages and disadvantages in the context of algorithmic trading.
Database Is Easy (Part 1): A Lightweight ORM Framework for MQL5 Using SQLite
This article presents a structured way to manage SQLite data in MQL5 through an ORM layer for MetaTrader 5. It introduces core classes for entity modeling and database access, a fluent CRUD API, reflection hooks for OnGet/OnSet, and macros to define models quickly. Practical code shows creating tables, binding fields, inserting, updating, querying, and deleting records. Developers gain reusable, type-safe components that minimize repetitive SQL.
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
Discover how to create exportable EX5 functions to efficiently query and save historical position data. In this step-by-step guide, we will expand the History Management EX5 library by developing modules that retrieve key properties of the most recently closed position. These include net profit, trade duration, pip-based stop loss, take profit, profit values, and various other important details.
Bacterial Chemotaxis Optimization (BCO)
The article presents the original version of the Bacterial Chemotaxis Optimization (BCO) algorithm and its modified version. We will take a closer look at all the differences, with a special focus on the new version of BCOm, which simplifies the bacterial movement mechanism, reduces the dependence on positional history, and uses simpler math than the computationally heavy original version. We will also conduct the tests and summarize the results.
DoEasy. Controls (Part 33): Vertical ScrollBar
In this article, we will continue the development of graphical elements of the DoEasy library and add vertical scrolling of form object controls, as well as some useful functions and methods that will be required in the future.
RiskGate: Centralized Risk Management for Multiple EAs
Many MetaTrader 5 setups run several EAs on one account, so risk gets fragmented and correlated exposure slips through. The article introduces RiskGate, a centralized Service that evaluates EA intents account‑wide: EAs send a JSON signal, the Service returns approved, lot and reason. You will see the client/server wiring, example rules (daily loss, exposure and correlation caps), unit‑tested handler design, and an EA example. The result is consistent portfolio‑level risk with simpler EAs.
Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography
Security prompts, such as those triggered every time you refresh the chart, add a new pair to the chat with the Admin Panel EA, or restart the terminal, can become tedious. In this discussion, we will explore and implement a feature that tracks the number of login attempts to identify a trusted user. After a set number of failed attempts, the application will transition to an advanced login procedure, which also facilitates passcode recovery for users who may have forgotten it. Additionally, we will cover how cryptography can be effectively integrated into the Admin Panel to enhance security.
Reimagining Classic Strategies (Part 22): Ensemble Mean Reverting Strategy
This article will illustrate to the reader how to implement a mean-reverting strategy for the EURUSD pair. The strategy follows contrarian trading rules. Our strategy implements a weekly moving average channel, with one moving average on the high-price feed and the latter on the low-price feed. We enter short positions when the price falls beneath the low moving average and long positions when the price rises above the high moving average. Additionally, we will export daily market data to build a simple ONNX model of the market to provide an additional filter for our entries. This provides the reader with a reproducible template for strategy development and backtesting.
Gating mechanisms in ensemble learning
In this article, we continue our exploration of ensemble models by discussing the concept of gates, specifically how they may be useful in combining model outputs to enhance either prediction accuracy or model generalization.
Developing a Replay System (Part 65): Playing the service (VI)
In this article, we will look at how to implement and solve the mouse pointer issue when using it in conjunction with a replay/simulation application. 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.
All about Automated Trading Championship: Interviews with the Participants'06
Interviews with the Participants of Automated Trading Championship 2006 demonstrated a great variety of views of automated trading and trading as a whole. You can see yourselves which ideas turned out to work better during the Championship and which of them could not pass the critical verification through a three-month long "test-drive" on a contest account.
Engineering Trading Discipline into Code (Part 6): Building a Unified Discipline Framework in MQL5
The article introduces a unified MQL5 discipline framework that consolidates the symbol whitelist, trading‑hours and news filters, and daily trade‑limit modules under CDisciplineEngine.mqh. It explains centralized trade validation and state synchronization shared by a chart dashboard and an enforcement Expert Advisor. Readers learn how to authorize orders through a single gate, monitor permissions in real time, and automatically enforce rules across the terminal.
The Group Method of Data Handling: Implementing the Multilayered Iterative Algorithm in MQL5
In this article we describe the implementation of the Multilayered Iterative Algorithm of the Group Method of Data Handling in MQL5.
Formulating Dynamic Multi-Pair EA (Part 10): Asymmetric Stop-Loss Logic Based on Pair-Specific Volatility Signatures
The EA learns each symbol's volatility profile before trading by processing 1000 bars and summarizing candle ranges, bodies and wicks, noise ratio, trend runs, pullback size, and true‑range dispersion. A classifier assigns regime and structure labels per pair. The stop‑loss optimizer maps those labels to a symbol‑specific ATR multiplier, and the risk module sizes lots to maintain constant percentage risk.
From Basic to Intermediate: Events (I)
Given everything that has been shown so far, I think we can now start implementing some kind of application to run some symbol directly on the chart. However, first we need to talk about a concept that can be rather confusing for beginners. Namely, it's the fact that applications developed in MQL5 and intended for display on a chart are not created in the same way as we have seen so far. In this article, we'll begin to understand this a little better.
Population optimization algorithms: Binary Genetic Algorithm (BGA). Part I
In this article, we will explore various methods used in binary genetic and other population algorithms. We will look at the main components of the algorithm, such as selection, crossover and mutation, and their impact on the optimization. In addition, we will study data presentation methods and their impact on optimization results.
GoertzelBrain: Adaptive Spectral Cycle Detection with Neural Network Ensemble in MQL5
GoertzelBrain combines Goertzel spectral analysis with an online‑trained neural network ensemble to convert cycle features into a directional confirmation signal. The indicator builds a compact feature vector from the dominant period, amplitude, confidence and their dynamics, plus local volatility, and outputs +1, −1 or 0. The article provides the full MQL5 implementation, explains the architecture and feature engineering, and shows how to use it as a directional filter.
Market Simulation (Part 03): A Matter of Performance
Often we have to take a step back and then move forward. In this article, we will show all the changes necessary to ensure that the Mouse and Chart Trade indicators do not break. As a bonus, we'll also cover other changes that have occurred in other header files that will be widely used in the future.
Developing an MQL5 RL agent with RestAPI integration (Part 4): Organizing functions in classes in MQL5
This article discusses the transition from procedural coding to object-oriented programming (OOP) in MQL5 with an emphasis on integration with the REST API. Today we will discuss how to organize HTTP request functions (GET and POST) into classes. We will take a closer look at code refactoring and show how to replace isolated functions with class methods. The article contains practical examples and tests.