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Market Simulation (Part 09): Sockets (III)
Market Simulation (Part 09): Sockets (III)
Today's article is a continuation of the previous one. We will look at the implementation of an Expert Advisor, focusing mainly on how the server code is executed. The code given in the previous article is not enough to make everything work as expected, so we need to dig a little deeper into it. Therefore, it is necessary to read both articles to better understand what will happen.
From Novice to Expert: Creating a Liquidity Zone Indicator
From Novice to Expert: Creating a Liquidity Zone Indicator
The extent of liquidity zones and the magnitude of the breakout range are key variables that substantially affect the probability of a retest occurring. In this discussion, we outline the complete process for developing an indicator that incorporates these ratios.
From Novice to Expert: Statistical Validation of Supply and Demand Zones
From Novice to Expert: Statistical Validation of Supply and Demand Zones
Today, we uncover the often overlooked statistical foundation behind supply and demand trading strategies. By combining MQL5 with Python through a Jupyter Notebook workflow, we conduct a structured, data-driven investigation aimed at transforming visual market assumptions into measurable insights. This article covers the complete research process, including data collection, Python-based statistical analysis, algorithm design, testing, and final conclusions. To explore the methodology and findings in detail, read the full article.
From Novice to Expert: Developing a Liquidity Strategy
From Novice to Expert: Developing a Liquidity Strategy
Liquidity zones are commonly traded by waiting for the price to return and retest the zone of interest, often through the placement of pending orders within these areas. In this article, we leverage MQL5 to bring this concept to life, demonstrating how such zones can be identified programmatically and how risk management can be systematically applied. Join the discussion as we explore both the logic behind liquidity-based trading and its practical implementation.
Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (IV): Trade Management Panel class
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.
Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer
Price Action Analysis Toolkit Development (Part 19): ZigZag Analyzer
Every price action trader manually uses trendlines to confirm trends and spot potential turning or continuation levels. In this series on developing a price action analysis toolkit, we introduce a tool focused on drawing slanted trendlines for easy market analysis. This tool simplifies the process for traders by clearly outlining key trends and levels essential for effective price action evaluation.
Integrating External Applications with MQL5 Community OAuth
Integrating External Applications with MQL5 Community OAuth
Learn how to add “Sign in with MQL5” to your Android app using the OAuth 2.0 authorization code flow. The guide covers app registration, endpoints, redirect URI, Custom Tabs, deep-link handling, and a PHP backend that exchanges the code for an access token over HTTPS. You will authenticate real MQL5 users and access profile data such as rank and reputation.
From Basic to Intermediate: Struct (V)
From Basic to Intermediate: Struct (V)
In this article, we will explore how to overload structural code. I know it can be quite challenging to understand at first, especially if you're seeing it for the first time. It is very important that you grasp these concepts and understand them well before attempting to delve into more complex and elaborate topics.
The MQL5 Standard Library Explorer (Part 7): Interactive Position Labeling with CCanvas
The MQL5 Standard Library Explorer (Part 7): Interactive Position Labeling with CCanvas
In this article, we explore how to build a position information visualization tool using the MQL5 Standard Library’s CCanvas. This project strengthens your skills in working with library modules while providing traders with a practical tool to visualize and interact with open positions directly on a live chart. Join the discussion to learn more.
The View component for tables in the MQL5 MVC paradigm: Base graphical element
The View component for tables in the MQL5 MVC paradigm: Base graphical element
The article covers the process of developing a base graphical element for the View component as part of the implementation of tables in the MVC (Model-View-Controller) paradigm in MQL5. This is the first article on the View component and the third one in a series of articles on creating tables for the MetaTrader 5 client terminal.
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.
Market Simulation (Part 08): Sockets (II)
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.
From Basic to Intermediate: Struct (III)
From Basic to Intermediate: Struct (III)
In this article, we will explore what structured code is. Many people confuse structured code with organized code, but there is a difference between these two concepts. This is exactly what will be discussed in this article. Despite the apparent complexity you may feel when first encountering this type of code writing, I have tried to approach the topic as simply as possible. However, this article is just the first step toward something greater.
Market Simulation (Part 07): Sockets (I)
Market Simulation (Part 07): Sockets (I)
Sockets. Do you know what they are for or how to use them in MetaTrader 5? If the answer is no, let's start by studying them. In today's article, we'll cover the basics. Since there are several ways to do the same thing, and we are always interested in the result, I want to show that there is indeed a simple way to transfer data from MetaTrader 5 to other programs, such as Excel. However, the main idea is not to transfer data from MetaTrader 5 to Excel, but the opposite, that is, to transfer data from Excel or any other program to MetaTrader 5.
From Basic to Intermediate: Events (II)
From Basic to Intermediate: Events (II)
In this article, we will see that not everything always needs to be implemented in a certain specific way. There are alternative approaches to problem-solving. To properly understand this article, it is necessary to grasp the concepts described in the previous articles. The materials presented here are for educational purposes only. Do not regard it as a finished application. Its purpose is to study the concepts presented here.
From Basic to Intermediate: Indicator (I)
From Basic to Intermediate: Indicator (I)
In this article, we will create our first fully practical and functional indicator. The goal is not to show how to create an application, but to help you understand how you can develop your own ideas and give you the opportunity to apply them in a safe, simple, and practical way.
From Basic to Intermediate: Indicator (II)
From Basic to Intermediate: Indicator (II)
In this article, we will examine how to implement a moving average calculation and what precautions should be taken when performing this calculation. We will also discuss overloading the OnCalculate function to know when and how to work with one model or another.
Integrating MQL5 with Data Processing Packages (Part 7): Building Multi-Agent Environments for Cross-Symbol Collaboration
Integrating MQL5 with Data Processing Packages (Part 7): Building Multi-Agent Environments for Cross-Symbol Collaboration
The article presents a complete Python–MQL5 integration for multi‑agent trading: MT5 data ingestion, indicator computation, per‑agent decisions, and a weighted consensus that outputs a single action. Signals are stored to JSON, served by Flask, and consumed by an MQL5 Expert Advisor for execution with position sizing and ATR‑derived SL/TP. Flask routes provide safe lifecycle control and status monitoring.
Price Action Analysis Toolkit Development (Part 60): Objective Swing-Based Trendlines for Structural Analysis
Price Action Analysis Toolkit Development (Part 60): Objective Swing-Based Trendlines for Structural Analysis
We present a rule-based approach to trendlines that avoids indicator pivots and uses ordered swings derived from raw prices. The article walks through swing detection, size qualification via ATR or fixed thresholds, and validation of ascending and descending structures, then implements these rules in MQL5 with non-repainting drawing and selective output. You get a clear, repeatable way to track structural support and resistance that holds up across market conditions.
From Basic to Intermediate: Indicator (III)
From Basic to Intermediate: Indicator (III)
In this article, we will explore how to declare various graphical representation indicators, such as DRAW_COLOR_LINE and DRAW_FILLING. Additionally, of course, we will learn how to plot graphs using multiple indicators in a simple, practical, and fast way. This can truly change your perspective on MetaTrader 5 and the market as a whole.
Bivariate Copulae in MQL5: (Part 3): Implementation and Tuning of Mixed Copula Models in MQL5
Bivariate Copulae in MQL5: (Part 3): Implementation and Tuning of Mixed Copula Models in MQL5
The article extends our copula toolkit with mixed copulas implemented natively in MQL5. We construct Clayton–Frank–Gumbel and Clayton–Student–t–Gumbel mixtures, estimate them via EM, and enable sparsity control through SCAD with cross‑validation. Provided scripts tune hyperparameters, compare mixtures using information criteria, and save trained models. Practitioners can apply these components to capture asymmetric tail dependence and embed the selected model in indicators or Expert Advisors.
From Basic to Intermediate: Indicator (IV)
From Basic to Intermediate: Indicator (IV)
In this article, we will explore how to easily create and implement an operational approach for coloring candles. This concept is highly valued by traders. When implementing such things, care must be taken to ensure that the bars or candles retain their original appearance and do not hinder reading candle by candle.
Price Action Analysis Toolkit Development (Part 61): Structural Slanted Trendline Breakouts with 3-Swing Validation
Price Action Analysis Toolkit Development (Part 61): Structural Slanted Trendline Breakouts with 3-Swing Validation
We present a slanted trendline breakout tool that relies on three‑swing validation to generate objective, price‑action signals. The system automates swing detection, trendline construction, and breakout confirmation using crossing logic to reduce noise and standardize execution. The article explains the strategy rules, shows the MQL5 implementation, and reviews testing results; the tool is intended for analysis and signal confirmation, not automated trading.
MQL5 Trading Tools (Part 18): Rounded Speech Bubbles/Balloons with Orientation Control
MQL5 Trading Tools (Part 18): Rounded Speech Bubbles/Balloons with Orientation Control
This article shows how to build rounded speech bubbles in MQL5 by combining a rounded rectangle with a pointer triangle and controlling orientation (up, down, left, right). It details geometry precomputation, supersampled filling, rounded apex arcs, and segmented borders with an extension ratio for seamless joins. Readers get configurable code for size, radii, colors, opacity, and thickness, ready for alerts or tooltips in trading interfaces.
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.
Risk Management (Part 4): Completing the Key Class Methods
Risk Management (Part 4): Completing the Key Class Methods
This is Part 4 of our series on risk management in MQL5, where we continue exploring advanced methods for protecting and optimizing trading strategies. Having laid important foundations in earlier articles, we will now focus on completing all remaining methods postponed in Part 3, including functions for checking whether specific profit or loss levels have been reached. In addition, we will introduce new key events that enable more accurate and flexible risk management.
Market Simulation (Part 12): Sockets (VI)
Market Simulation (Part 12): Sockets (VI)
In this article, we will look at how to solve certain problems and issues that arise when using Python code within other programs. More specifically, we will demonstrate a common issue encountered when using Excel in conjunction with MetaTrader 5, although we will be using Python to facilitate this interaction. However, this implementation has a minor drawback. It does not occur in all cases, but only in certain specific situations. When it does happen, it is necessary to understand the cause. In today’s article, we will begin explaining how to resolve this issue.
Market Simulation: (Part 11): Sockets (V)
Market Simulation: (Part 11): Sockets (V)
We are beginning to implement the connection between Excel and MetaTrader 5, but first we need to understand some key points. This way, you won't have to rack your brains trying to figure out why something works or doesn't. And before you frown at the prospect of integrating Python and Excel, let's see how we can (to some extent) control MetaTrader 5 through Excel using xlwings. What we demonstrate here will primarily focus on educational objectives. However, don't think that we can only do what will be covered here.
From Basic to Intermediate: Struct (VI)
From Basic to Intermediate: Struct (VI)
In this article, we will explore how to approach the implementation of a common structural code base. The goal is to reduce the programming workload and leverage the full potential of the programming language itself—in this case, MQL5.
From Basic to Intermediate: Struct (IV)
From Basic to Intermediate: Struct (IV)
In this article, we will explore how to create so-called structural code, where the entire context and methods for manipulating variables and information are placed within a structure to create a suitable context for implementing any code. Therefore, we will examine the necessity of using a private section of the code to separate what is public from what is not, thereby adhering to the rule of encapsulation and preserving the context for which the data structure was created.
Market Simulation (Part 14): Sockets (VIII)
Market Simulation (Part 14): Sockets (VIII)
Many programmers might assume we should abandon using Excel and move directly to Python, using some packages that allow Python to generate an Excel file for later analysis of results. However, as mentioned in the previous article, although this solution is the simplest for many programmers, it will not be accepted by some users. And in this particular case, the user is always right. As programmers, we must find a way to make everything work.
Developing A Custom Account Performance Matrix Indicator
Developing A Custom Account Performance Matrix Indicator
This indicator acts as a discipline enforcer by tracking account equity, profit/loss, and drawdown in real-time while displaying a performance dashboard. It can help traders stay consistent, avoid overtrading, and comply with prop-firm challenge rules.
From Novice to Expert: Automating Intraday Strategies
From Novice to Expert: Automating Intraday Strategies
We translate the EMA‑50 retest idea into a behavior‑driven Expert Advisor for intraday trading. The study formalizes trend bias, EMA interaction (pierce and close), reaction confirmation, and optional filters, then implements them in MQL5 with modular functions and resource‑safe handles. Visual testing in the Strategy Tester verifies signal correctness. The result is a clear template for coding discretionary bounces.
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
The article extends a liquidity-based strategy with a simple trend constraint: trade liquidity zones only in the direction of the EMA(50). It explains filtering rules, presents a reusable TrendFilter.mqh class and EA integration in MQL5, and compares baseline versus filtered tests. Readers gain a clear directional bias, reduced overtrading in countertrend phases, and ready-to-use source files.
Overcoming Accessibility Problems in MQL5 Trading Tools (Part I): How to Add Contextual Voice Alerts in MQL5 Indicators
Overcoming Accessibility Problems in MQL5 Trading Tools (Part I): How to Add Contextual Voice Alerts in MQL5 Indicators
This article explores an accessibility-focused enhancement that goes beyond default terminal alerts by leveraging MQL5 resource management to deliver contextual voice feedback. Instead of generic tones, the indicator communicates what has occurred and why, allowing traders to understand market events without relying solely on visual observation. This approach is especially valuable for visually impaired traders, but it also benefits busy or multitasking users who prefer hands-free interaction.