Articles on the MQL5 programming and use of trading robots

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Expert Advisors created for the MetaTrader platform perform a variety of functions implemented by their developers. Trading robots can track financial symbols 24 hours a day, copy deals, create and send reports, analyze news and even provide specific custom graphical interface.

The articles describe programming techniques, mathematical ideas for data processing, tips on creating and ordering of trading robots.

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MQL5 Wizard Techniques you should know (Part 27): Moving Averages and the Angle of Attack

MQL5 Wizard Techniques you should know (Part 27): Moving Averages and the Angle of Attack

The Angle of Attack is an often-quoted metric whose steepness is understood to strongly correlate with the strength of a prevailing trend. We look at how it is commonly used and understood and examine if there are changes that could be introduced in how it's measured for the benefit of a trade system that puts it in use.
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Neural networks made easy (Part 46): Goal-conditioned reinforcement learning (GCRL)

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.
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Design Patterns in software development and MQL5 (Part 2): Structural Patterns

Design Patterns in software development and MQL5 (Part 2): Structural Patterns

In this article, we will continue our articles about Design Patterns after learning how much this topic is more important for us as developers to develop extendable, reliable applications not only by the MQL5 programming language but others as well. We will learn about another type of Design Patterns which is the structural one to learn how to design systems by using what we have as classes to form larger structures.
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Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Lightweight time series forecasting models achieve high performance using a minimum number of parameters. This, in turn, reduces the consumption of computing resources and speeds up decision-making. Despite being lightweight, such models achieve forecast quality comparable to more complex ones.
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Developing a multi-currency Expert Advisor (Part 6): Automating the selection of an instance group

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.
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Neural networks made easy (Part 78): Decoder-free Object Detector with Transformer (DFFT)

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.
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Reimagining Classic Strategies (Part V): Multiple Symbol Analysis on USDZAR

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.
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Data label for time series mining (Part 6):Apply and Test in EA Using ONNX

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!
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MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels

MQL5 Trading Tools (Part 13): Creating a Canvas-Based Price Dashboard with Graph and Stats Panels

In this article, we develop a canvas-based price dashboard in MQL5 using the CCanvas class to create interactive panels for visualizing recent price graphs and account statistics, with support for background images, fog effects, and gradient fills. The system includes draggable and resizable features via mouse event handling, theme toggling between dark and light modes with dynamic color adjustments, and minimize/maximize controls for efficient chart space management.
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Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

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.
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From Novice to Expert: Mastering Detailed Trading Reports with Reporting EA

From Novice to Expert: Mastering Detailed Trading Reports with Reporting EA

In this article, we delve into enhancing the details of trading reports and delivering the final document via email in PDF format. This marks a progression from our previous work, as we continue exploring how to harness the power of MQL5 and Python to generate and schedule trading reports in the most convenient and professional formats. Join us in this discussion to learn more about optimizing trading report generation within the MQL5 ecosystem.
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From Novice to Expert: Revealing the Candlestick Shadows (Wicks)

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.
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Using the MQL5 Economic Calendar for News Filtering (Part 1): Implementing Pre- and Post-News Windows in MQL5

Using the MQL5 Economic Calendar for News Filtering (Part 1): Implementing Pre- and Post-News Windows in MQL5

We build a calendar‑driven news filter entirely in MQL5, avoiding web requests and external DLLs. Part 1 covers loading and caching events, mapping them to symbols by currency, filtering by impact level, defining pre/post windows, and blocking new trades during active news, with optional pre‑news position closure. The result is a configurable, prop‑firm‑friendly control that reduces false pauses and protects entries during volatility.
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Building AI-Powered Trading Systems in MQL5 (Part 8): UI Polish with Animations, Timing Metrics, and Response Management Tools

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.
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Category Theory in MQL5 (Part 22): A different look at Moving Averages

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.
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From Novice to Expert: The Essential Journey Through MQL5 Trading

From Novice to Expert: The Essential Journey Through MQL5 Trading

Unlock your potential! You're surrounded by opportunities. Discover 3 top secrets to kickstart your MQL5 journey or take it to the next level. Let's dive into discussion of tips and tricks for beginners and pros alike.
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Neural networks made easy (Part 45): Training state exploration skills

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.
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Codex Pipelines: From Python to MQL5 for Indicator Selection — A Multi-Quarter Analysis of the FXI ETF

Codex Pipelines: From Python to MQL5 for Indicator Selection — A Multi-Quarter Analysis of the FXI ETF

We continue our look at how MetaTrader can be used outside its forex trading ‘comfort-zone’ by looking at another tradable asset in the form of the FXI ETF. Unlike in the last article where we tried to do ‘too-much’ by delving into not just indicator selection, but also considering indicator pattern combinations, for this article we will swim slightly upstream by focusing more on indicator selection. Our end product for this is intended as a form of pipeline that can help recommend indicators for various assets, provided we have a reasonable amount of their price history.
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Developing a multi-currency Expert Advisor (Part 15): Preparing EA for real trading

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.
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Neural networks made easy (Part 51): Behavior-Guided Actor-Critic (BAC)

Neural networks made easy (Part 51): Behavior-Guided Actor-Critic (BAC)

The last two articles considered the Soft Actor-Critic algorithm, which incorporates entropy regularization into the reward function. This approach balances environmental exploration and model exploitation, but it is only applicable to stochastic models. The current article proposes an alternative approach that is applicable to both stochastic and deterministic models.
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Creating an MQL5-Telegram Integrated Expert Advisor (Part 7): Command Analysis for Indicator Automation on Charts

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
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Price Action Analysis Toolkit Development (Part 59): Using Geometric Asymmetry to Identify Precision Breakouts from Fractal Consolidation

Price Action Analysis Toolkit Development (Part 59): Using Geometric Asymmetry to Identify Precision Breakouts from Fractal Consolidation

While studying a wide range of breakout setups, I noticed that failed breakouts were rarely caused by a lack of volatility, but more often by weak internal structure. That observation led to the framework presented in this article. The approach identifies patterns where the final price leg shows superior length, steepness, and speed—clear signs of momentum accumulation ahead of directional expansion. By detecting these subtle geometric imbalances within consolidation, traders can anticipate higher-probability breakouts before price exits the range. Continue reading to see how this fractal-based, geometric framework translates structural imbalance into precise breakout signals.
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Neural Networks in Trading: Controlled Segmentation (Final Part)

Neural Networks in Trading: Controlled Segmentation (Final Part)

We continue the work started in the previous article on building the RefMask3D framework using MQL5. This framework is designed to comprehensively study multimodal interaction and feature analysis in a point cloud, followed by target object identification based on a description provided in natural language.
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Self Optimizing Expert Advisors in MQL5 (Part 16): Supervised Linear System Identification

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.
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Neural Networks in Trading: Contrastive Pattern Transformer

Neural Networks in Trading: Contrastive Pattern Transformer

The Contrastive Transformer is designed to analyze markets both at the level of individual candlesticks and based on entire patterns. This helps improve the quality of market trend modeling. Moreover, the use of contrastive learning to align representations of candlesticks and patterns fosters self-regulation and improves the accuracy of forecasts.
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Self Optimizing Expert Advisors in MQL5 (Part 16): Supervised Linear System Identification

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.
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Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part III)

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.
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Automating Market Memory Zones Indicator: Where Price is Likely to Return

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.
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Developing a multi-currency Expert Advisor (Part 16): Impact of different quote histories on test results

Developing a multi-currency Expert Advisor (Part 16): Impact of different quote histories on test results

The EA under development is expected to show good results when trading with different brokers. But for now we have been using quotes from a MetaQuotes demo account to perform tests. Let's see if our EA is ready to work on a trading account with different quotes compared to those used during testing and optimization.
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MQL5 Trading Tools (Part 5): Creating a Rolling Ticker Tape for Real-Time Symbol Monitoring

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.
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Trading with the MQL5 Economic Calendar (Part 10): Draggable Dashboard and Interactive Hover Effects for Seamless News Navigation

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.
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Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)

Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)

In this article, we explore how previously invalidated orderblocks can be reused as mitigation blocks within Smart Money Concepts (SMC). These zones reveal where institutional traders re-enter the market after a failed orderblock, providing high-probability areas for trade continuation in the dominant trend.
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Neural Networks Made Easy (Part 85): Multivariate Time Series Forecasting

Neural Networks Made Easy (Part 85): Multivariate Time Series Forecasting

In this article, I would like to introduce you to a new complex timeseries forecasting method, which harmoniously combines the advantages of linear models and transformers.
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Neural Networks Made Easy (Part 86): U-Shaped Transformer

Neural Networks Made Easy (Part 86): U-Shaped Transformer

We continue to study timeseries forecasting algorithms. In this article, we will discuss another method: the U-shaped Transformer.
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Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)

Reusing Invalidated Orderblocks As Mitigation Blocks (SMC)

In this article, we explore how previously invalidated orderblocks can be reused as mitigation blocks within Smart Money Concepts (SMC). These zones reveal where institutional traders re-enter the market after a failed orderblock, providing high-probability areas for trade continuation in the dominant trend.
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From Novice to Expert: Detecting Liquidity Zone Flips Using MQL5

From Novice to Expert: Detecting Liquidity Zone Flips Using MQL5

This article presents an MQL5 indicator that detects and manages liquidity zone flips. It identifies supply and demand zones from higher timeframes using a base–impulse pattern, applies objective breakout and impulse thresholds, and flips zones automatically when structure changes. The result is a dynamic support‑resistance map that reduces manual redraws and gives you clear, actionable context for signals and retests.
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Cross-validation and basics of causal inference in CatBoost models, export to ONNX format

Cross-validation and basics of causal inference in CatBoost models, export to ONNX format

The article proposes the method of creating bots using machine learning.
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Neural networks made easy (Part 74): Trajectory prediction with adaptation

Neural networks made easy (Part 74): Trajectory prediction with adaptation

This article introduces a fairly effective method of multi-agent trajectory forecasting, which is able to adapt to various environmental conditions.
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Neural Networks in Trading: Node-Adaptive Graph Representation with NAFS

Neural Networks in Trading: Node-Adaptive Graph Representation with NAFS

We invite you to get acquainted with the NAFS (Node-Adaptive Feature Smoothing) method, which is a non-parametric approach to creating node representations that does not require parameter training. NAFS extracts features of each node given its neighbors and then adaptively combines these features to form a final representation.
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MQL5 Wizard Techniques you should know (Part 24): Moving Averages

MQL5 Wizard Techniques you should know (Part 24): Moving Averages

Moving Averages are a very common indicator that are used and understood by most Traders. We explore possible use cases that may not be so common within MQL5 Wizard assembled Expert Advisors.