MQL4 and MQL5 Programming Articles

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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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Creating Custom Indicators in MQL5 (Part 5): WaveTrend Crossover Evolution Using Canvas for Fog Gradients, Signal Bubbles, and Risk Management

Creating Custom Indicators in MQL5 (Part 5): WaveTrend Crossover Evolution Using Canvas for Fog Gradients, Signal Bubbles, and Risk Management

In this article, we enhance the Smart WaveTrend Crossover indicator in MQL5 by integrating canvas-based drawing for fog gradient overlays, signal boxes that detect breakouts, and customizable buy/sell bubbles or triangles for visual alerts. We incorporate risk management features with dynamic take-profit and stop-loss levels calculated via candle multipliers or percentages, displayed through lines and a table, alongside options for trend filtering and box extensions.
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Developing a Replay System (Part 31): Expert Advisor project — C_Mouse class (V)

Developing a Replay System (Part 31): Expert Advisor project — C_Mouse class (V)

We need a timer that can show how much time is left till the end of the replay/simulation run. This may seem at first glance to be a simple and quick solution. Many simply try to adapt and use the same system that the trading server uses. But there's one thing that many people don't consider when thinking about this solution: with replay, and even m ore with simulation, the clock works differently. All this complicates the creation of such a system.
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Neural Networks Made Easy (Part 81): Context-Guided Motion Analysis (CCMR)

Neural Networks Made Easy (Part 81): Context-Guided Motion Analysis (CCMR)

In previous works, we always assessed the current state of the environment. At the same time, the dynamics of changes in indicators always remained "behind the scenes". In this article I want to introduce you to an algorithm that allows you to evaluate the direct change in data between 2 successive environmental states.
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Analyzing Overbought and Oversold Trends Via Chaos Theory Approaches

Analyzing Overbought and Oversold Trends Via Chaos Theory Approaches

We determine the overbought and oversold condition of the market according to chaos theory: integrating the principles of chaos theory, fractal geometry and neural networks to forecast financial markets. The study demonstrates the use of the Lyapunov exponent as a measure of market randomness and the dynamic adaptation of trading signals. The methodology includes an algorithm for generating fractal noise, hyperbolic tangent activation, and moment optimization.
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From Novice to Expert: Animated News Headline Using MQL5 (VII) — Post Impact Strategy for News Trading

From Novice to Expert: Animated News Headline Using MQL5 (VII) — Post Impact Strategy for News Trading

The risk of whipsaw is extremely high during the first minute following a high-impact economic news release. In that brief window, price movements can be erratic and volatile, often triggering both sides of pending orders. Shortly after the release—typically within a minute—the market tends to stabilize, resuming or correcting the prevailing trend with more typical volatility. In this section, we’ll explore an alternative approach to news trading, aiming to assess its effectiveness as a valuable addition to a trader’s toolkit. Continue reading for more insights and details in this discussion.
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Forex arbitrage trading: Analyzing synthetic currencies movements and their mean reversion

Forex arbitrage trading: Analyzing synthetic currencies movements and their mean reversion

In this article, we will examine the movements of synthetic currencies using Python and MQL5 and explore how feasible Forex arbitrage is today. We will also consider ready-made Python code for analyzing synthetic currencies and share more details on what synthetic currencies are in Forex.
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Package-based approach with KnitPkg for MQL5 development

Package-based approach with KnitPkg for MQL5 development

For maximum reliability and productivity in MetaTrader products built with MQL, this article advocates a development approach based on reusable “packages” managed by KnitPkg, a project manager for MQL5/MQL4. A package can be used as a building block for other packages or as the foundation for final artifacts that run directly on the MetaTrader platform, such as EAs, indicators, and more.
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Chemical reaction optimization (CRO) algorithm (Part II): Assembling and results

Chemical reaction optimization (CRO) algorithm (Part II): Assembling and results

In the second part, we will collect chemical operators into a single algorithm and present a detailed analysis of its results. Let's find out how the Chemical reaction optimization (CRO) method copes with solving complex problems on test functions.
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Developing a Replay System (Part 44): Chart Trade Project (III)

Developing a Replay System (Part 44): Chart Trade Project (III)

In the previous article I explained how you can manipulate template data for use in OBJ_CHART. In that article, I only outlined the topic without going into details, since in that version the work was done in a very simplified way. This was done to make it easier to explain the content, because despite the apparent simplicity of many things, some of them were not so obvious, and without understanding the simplest and most basic part, you would not be able to truly understand the entire picture.
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Artificial Ecosystem-based Optimization (AEO) algorithm

Artificial Ecosystem-based Optimization (AEO) algorithm

The article considers a metaheuristic Artificial Ecosystem-based Optimization (AEO) algorithm, which simulates interactions between ecosystem components by creating an initial population of solutions and applying adaptive update strategies, and describes in detail the stages of AEO operation, including the consumption and decomposition phases, as well as different agent behavior strategies. The article introduces the features and advantages of this algorithm.
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Data Science and ML (Part 34): Time series decomposition, Breaking the stock market down to the core

Data Science and ML (Part 34): Time series decomposition, Breaking the stock market down to the core

In a world overflowing with noisy and unpredictable data, identifying meaningful patterns can be challenging. In this article, we'll explore seasonal decomposition, a powerful analytical technique that helps separate data into its key components: trend, seasonal patterns, and noise. By breaking data down this way, we can uncover hidden insights and work with cleaner, more interpretable information.
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Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (III): Communication Module

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (III): Communication Module

Join us for an in-depth discussion on the latest advancements in MQL5 interface design as we unveil the redesigned Communications Panel and continue our series on building the New Admin Panel using modularization principles. We'll develop the CommunicationsDialog class step by step, thoroughly explaining how to inherit it from the Dialog class. Additionally, we'll leverage arrays and ListView class in our development. Gain actionable insights to elevate your MQL5 development skills—read through the article and join the discussion in the comments section!
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From Basic to Intermediate: Structs (II)

From Basic to Intermediate: Structs (II)

In this article, we will try to understand why programming languages like MQL5 have structures, and why in some cases structures are the ideal way to pass values between functions and procedures, while in other cases they may not be the best way to do it.
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MQL5 Wizard Techniques you should know (Part 36): Q-Learning with Markov Chains

MQL5 Wizard Techniques you should know (Part 36): Q-Learning with Markov Chains

Reinforcement Learning is one of the three main tenets in machine learning, alongside supervised learning and unsupervised learning. It is therefore concerned with optimal control, or learning the best long-term policy that will best suit the objective function. It is with this back-drop, that we explore its possible role in informing the learning-process to an MLP of a wizard assembled Expert Advisor.
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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.
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Reimagining Classic Strategies: Crude Oil

Reimagining Classic Strategies: Crude Oil

In this article, we revisit a classic crude oil trading strategy with the aim of enhancing it by leveraging supervised machine learning algorithms. We will construct a least-squares model to predict future Brent crude oil prices based on the spread between Brent and WTI crude oil prices. Our goal is to identify a leading indicator of future changes in Brent prices.
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Category Theory in MQL5 (Part 6): Monomorphic Pull-Backs and Epimorphic Push-Outs

Category Theory in MQL5 (Part 6): Monomorphic Pull-Backs and Epimorphic Push-Outs

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.
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Developing a Replay System (Part 66): Playing the service (VII)

Developing a Replay System (Part 66): Playing the service (VII)

In this article, we will implement the first solution that will allow us to determine when a new bar may appear on the chart. This solution is applicable in a wide variety of situations. Understanding its development will help you grasp several important aspects. 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.
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Population optimization algorithms: Evolution Strategies, (μ,λ)-ES and (μ+λ)-ES

Population optimization algorithms: Evolution Strategies, (μ,λ)-ES and (μ+λ)-ES

The article considers a group of optimization algorithms known as Evolution Strategies (ES). They are among the very first population algorithms to use evolutionary principles for finding optimal solutions. We will implement changes to the conventional ES variants and revise the test function and test stand methodology for the algorithms.
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Larry Williams Market Secrets (Part 3): Proving Non-Random Market Behavior with MQL5

Larry Williams Market Secrets (Part 3): Proving Non-Random Market Behavior with MQL5

Explore whether financial markets are truly random by recreating Larry Williams’ market behavior experiments using MQL5. This article demonstrates how simple price-action tests can reveal statistical market biases using a custom Expert Advisor.
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Artificial Cooperative Search (ACS) algorithm

Artificial Cooperative Search (ACS) algorithm

Artificial Cooperative Search (ACS) is an innovative method using a binary matrix and multiple dynamic populations based on mutualistic relationships and cooperation to find optimal solutions quickly and accurately. ACS unique approach to predators and prey enables it to achieve excellent results in numerical optimization problems.
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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.
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Developing a Replay System (Part 49): Things Get Complicated (I)

Developing a Replay System (Part 49): Things Get Complicated (I)

In this article, we'll complicate things a little. Using what was shown in the previous articles, we will start to open up the template file so that the user can use their own template. However, I will be making changes gradually, as I will also be refining the indicator to reduce the load on MetaTrader 5.
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MQL5 Wizard Techniques you should know (Part 53): Market Facilitation Index

MQL5 Wizard Techniques you should know (Part 53): Market Facilitation Index

The Market Facilitation Index is another Bill Williams Indicator that is intended to measure the efficiency of price movement in tandem with volume. As always, we look at the various patterns of this indicator within the confines of a wizard assembly signal class, and present a variety of test reports and analyses for the various patterns.
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Developing a multi-currency Expert Advisor (Part 7): Selecting a group based on forward period

Developing a multi-currency Expert Advisor (Part 7): Selecting a group based on forward period

Previously, we evaluated the selection of a group of trading strategy instances, with the aim of improving the results of their joint operation, only on the same time period, in which the optimization of individual instances was carried out. Let's see what happens in the forward period.
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Sending Messages from MQL5 to Discord, Creating a Discord-MetaTrader 5 Bot

Sending Messages from MQL5 to Discord, Creating a Discord-MetaTrader 5 Bot

Similar to Telegram, Discord is capable of receiving information and messages in JSON format using it's communication API's, In this article, we are going to explore how you can use discord API's to send trading signals and updates from MetaTrader 5 to your Discord trading community.
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Creating a Trading Administrator Panel in MQL5 (Part III): Extending Built-in Classes for Theme Management (II)

Creating a Trading Administrator Panel in MQL5 (Part III): Extending Built-in Classes for Theme Management (II)

In this discussion, we will carefully extend the existing Dialog library to incorporate theme management logic. Furthermore, we will integrate methods for theme switching into the CDialog, CEdit, and CButton classes utilized in our Admin Panel project. Continue reading for more insightful perspectives.
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From Novice to Expert: Animated News Headline Using MQL5 (XI)—Correlation in News Trading

From Novice to Expert: Animated News Headline Using MQL5 (XI)—Correlation in News Trading

In this discussion, we will explore how the concept of Financial Correlation can be applied to improve decision-making efficiency when trading multiple symbols during major economic events announcement. The focus is on addressing the challenge of heightened risk exposure caused by increased volatility during news releases.
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Data label for time series mining (Part 5):Apply and Test in EA Using Socket

Data label for time series mining (Part 5):Apply and Test in EA Using Socket

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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The MQL5 Standard Library Explorer (Part 4): Custom Signal Library

The MQL5 Standard Library Explorer (Part 4): Custom Signal Library

Today, we use the MQL5 Standard Library to build custom signal classes and let the MQL5 Wizard assemble a professional Expert Advisor for us. This approach simplifies development so that even beginner programmers can create robust EAs without in-depth coding knowledge, focusing instead on tuning inputs and optimizing performance. Join this discussion as we explore the process step by step.
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Integrating MQL5 with data processing packages (Part 4): Big Data Handling

Integrating MQL5 with data processing packages (Part 4): Big Data Handling

Exploring advanced techniques to integrate MQL5 with powerful data processing tools, this part focuses on efficient handling of big data to enhance trading analysis and decision-making.
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Developing a Replay System — Market simulation (Part 16): New class system

Developing a Replay System — Market simulation (Part 16): New class system

We need to organize our work better. The code is growing, and if this is not done now, then it will become impossible. Let's divide and conquer. MQL5 allows the use of classes which will assist in implementing this task, but for this we need to have some knowledge about classes. Probably the thing that confuses beginners the most is inheritance. In this article, we will look at how to use these mechanisms in a practical and simple way.
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MQL5 Wizard Techniques you should know (Part 65): Using Patterns of FrAMA and the Force Index

MQL5 Wizard Techniques you should know (Part 65): Using Patterns of FrAMA and the Force Index

The Fractal Adaptive Moving Average (FrAMA) and the Force Index Oscillator are another pair of indicators that could be used in conjunction within an MQL5 Expert Advisor. These two indicators complement each other a little bit because FrAMA is a trend following indicator while the Force Index is a volume based oscillator. As always, we use the MQL5 wizard to rapidly explore any potential these two may have.
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MQL5 Wizard Techniques you should know (Part 07): Dendrograms

MQL5 Wizard Techniques you should know (Part 07): Dendrograms

Data classification for purposes of analysis and forecasting is a very diverse arena within machine learning and it features a large number of approaches and methods. This piece looks at one such approach, namely Agglomerative Hierarchical Classification.
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MQL5 Wizard Techniques you should know (Part 41): Deep-Q-Networks

MQL5 Wizard Techniques you should know (Part 41): Deep-Q-Networks

The Deep-Q-Network is a reinforcement learning algorithm that engages neural networks in projecting the next Q-value and ideal action during the training process of a machine learning module. We have already considered an alternative reinforcement learning algorithm, Q-Learning. This article therefore presents another example of how an MLP trained with reinforcement learning, can be used within a custom signal class.
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MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

MQL5 Wizard Techniques you should know (Part 66): Using Patterns of FrAMA and the Force Index with the Dot Product Kernel

The FrAMA Indicator and the Force Index Oscillator are trend and volume tools that could be paired when developing an Expert Advisor. We continue from our last article that introduced this pair by considering machine learning applicability to the pair. We are using a convolution neural network that uses the dot-product kernel in making forecasts with these indicators’ inputs. This is done in a custom signal class file that works with the MQL5 wizard to assemble an Expert Advisor.
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Reimagining Classic Strategies (Part 13): Taking Our Crossover Strategy to New Dimensions (Part 2)

Reimagining Classic Strategies (Part 13): Taking Our Crossover Strategy to New Dimensions (Part 2)

Join us in our discussion as we look for additional improvements to make to our moving-average cross over strategy to reduce the lag in our trading strategy to more reliable levels by leveraging our skills in data science. It is a well-studied fact that projecting your data to higher dimensions can at times improve the performance of your machine learning models. We will demonstrate what this practically means for you as a trader, and illustrate how you can weaponize this powerful principle using your MetaTrader 5 Terminal.
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Reimagining Classic Strategies (Part 14): Multiple Strategy Analysis

Reimagining Classic Strategies (Part 14): Multiple Strategy Analysis

In this article, we continue our exploration of building an ensemble of trading strategies and using the MT5 genetic optimizer to tune the strategy parameters. Today, we analyzed the data in Python, showing our model could better predict which strategy would outperform, achieving higher accuracy than forecasting market returns directly. However, when we tested our application with its statistical models, our performance levels fell dismally. We subsequently discovered that the genetic optimizer unfortunately favored highly correlated strategies, prompting us to revise our method to keep vote weights fixed and focus optimization on indicator settings instead.
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Developing a Replay System — Market simulation (Part 07): First improvements (II)

Developing a Replay System — Market simulation (Part 07): First improvements (II)

In the previous article, we made some fixes and added tests to our replication system to ensure the best possible stability. We also started creating and using a configuration file for this system.
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Neural Network in Practice: Secant Line

Neural Network in Practice: Secant Line

As already explained in the theoretical part, when working with neural networks we need to use linear regressions and derivatives. Why? The reason is that linear regression is one of the simplest formulas in existence. Essentially, linear regression is just an affine function. However, when we talk about neural networks, we are not interested in the effects of direct linear regression. We are interested in the equation that generates this line. We are not that interested in the line created. Do you know the main equation that we need to understand? If not, I recommend reading this article to understanding it.